University of Southern California Dissertations and Theses

Zero net energy institutional building

(USC Thesis Other)

Zero net energy institutional building

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content ZERO NET ENERGY INSTITUTIONAL BUILDING by Sukreet Singh A Thesis Presented to the FACULTY OF THE USC SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF BUILDING SCIENCE May 2012 Copyright 2012 Sukreet Singh ii ACKNOWLEDGEMENTS I would like to extend my deepest gratitude to my entire thesis committee for guiding and supporting me through the process of this study. My thesis chair, Marc Schiler has been the backbone of this thesis. His logical way of thinking and expertise in wide range of building science topics have been of great value to me throughout out my research. He has been invariably calm and thought through with me for possible ways to overcome numerous hurdles in this convoluted thesis. I really admire his enthusiasm and his ability to explain things clearly and simply which highly contributed to the success of this thesis. Marc, you are a great role model. I would like to express my very great appreciation to Peter Simmonds of IBE Consulting Engineers without whom this work could not have been completed. I am proud to record that I had the opportunity to work with such an exceptionally knowledgeable and experienced person like him. He served on my thesis with true passion and sincerity and imparted me with his mechanical engineering knowledge. This helped me understand the mechanical systems, calculations and engineering behind them which was utterly important considering my background from Architecture side and not engineering. Peter, I am grateful to you in every possible way. I am particularly grateful for the assistance given by Carol Fern who is a director of Energy Services at Facilities Management Services, USC. I must say that without her this thesis would not have ever gotten off the ground. She helped me figuring out the best possible case study for this thesis, providing me with all the possible documentation for the same. She assisted me for site visits explaining me the way in which the building is behaving, controls they have and schedules that they follow. She very graciously allowed iii full access to the energy management system and provided me with all the granular data that they had. These data were the absolute core of this study, and without it there would have been no study at all. Carol, it was a great pleasure working with you. My special acknowledgements go to the person who inspired me to explore this field, Greg Otto. He introduced me to this arena in the beginning of my graduate career as part of my Graduate Research Scholarship assignments. He took me to the official meetings and discussions which proved vital in understanding this subject which eventually helped me firming my thesis topic. Greg, you are a great person and a true mentor. I wish to acknowledge the help provided by Elisabeth Newell under whom I am currently doing my internship at GreenWorks Studio. She has been more than a mentor for me who has always supported me and encouraged me to perform at my best. The projects that I did with her at office gave me more confidence to pursue my thesis with much more vigor and enthusiasm. Elisabeth, you have been of a great value to me. I would like to thank Prof Murray Milne who introduced me to energy simulation softwares in one of his classes and inspired me to take one of my final projects to a higher degree of excellence. My thesis has evolved out of that experience with simulation softwares and encouragement provided by Prof Murray Milne. Murray, I am really indebted to you for all the knowledge that you have shared with me. I owe a great acknowledgement for couple of my very close friends, William Vicent and Deepa Chandrashekaran. I have learnt as much from them as from my Professors at USC. Both of them have been instrumental in increasing my knowledgebase and skills in building science arena and have helped me shape my career. Simon, Abhay, Morgan, iv Wonhee, Aishwarya, Andrea, Eve, Jay and Yilun, thanks for being supportive, loving, and caring friends. I would also like to thank all of my professors from the University of Southern California’s Masters of Building Science program, Karen Kensek, Murray Milne, Doug Noble, Goetz Schierle and Anders Carlson. All of your classes and teachings helped shape my interests in the study of building technology. My parents, grandparents and younger brother deserve special mention for their prayers and inseparable support throughout my graduate life. My father, Harleen Singh, who is renowned Architect in India, inspired me right from the childhood to excel in Architectural arena and my mother, Kuljeet Kaur, who is a scholar herself always encouraged me to research hard and enrich myself with extensive knowledge. My brother, Tarneet Singh, has been a part of my soul and has always encouraged me during my hard times. All my family members sincerely raised me with their caring and gentle love, and have always been a strong supporter of my decisions. Finally, I would like to express my gratitude to everyone who have helped me and supported me in bringing this thesis to light. v TABLE OF CONTENTS ACKNOWLEDGEMENTS .................................................................................................................... ii LIST OF FIGURES ............................................................................................................................ viii LIST OF TABLES ............................................................................................................................. xxix ABSTRACT .................................................................................................................................... xxxii CHAPTER ‐ 1: BACKGROUND INFORMATION ................................................................................... 1 1.1. Hypothesis........................................................................................................................ 2 1.2. Introduction ..................................................................................................................... 2 1.3. Zero Net Energy ............................................................................................................... 5 1.4. Benchmarking & Standards.............................................................................................. 7 1.5. Whole Building Energy Analysis ..................................................................................... 12 1.6. Calibration Simulation Approach ................................................................................... 13 1.7. Simulation Software ....................................................................................................... 16 CHAPTER ‐ 2: CASE STUDY ‐ VON KLEINSMID CENTRE ................................................................... 20 2.1. Why this building ........................................................................................................... 21 2.2. Site Location ................................................................................................................... 23 2.3. Climate Analysis ............................................................................................................. 23 2.4. Description of VKC ......................................................................................................... 26 2.5. Occupancy & Schedules ................................................................................................. 38 2.6. Utility Data ..................................................................................................................... 39 CHAPTER ‐ 3: VKC ANALYSIS........................................................................................................... 43 3.1. Immediate Site Context ................................................................................................. 44 3.2. Solar Shade Analysis....................................................................................................... 45 3.3. EUI & Comparison to Benchmarks ................................................................................. 46 3.4. ZNE Target ...................................................................................................................... 47 3.5. On‐Site Measurement .................................................................................................... 53 3.6. Lighting Power Density .................................................................................................. 57 3.7. Investigation Work ......................................................................................................... 57 3.8. Site Visit Notes ............................................................................................................... 58 vi CHAPTER ‐ 4: SIMULATION SOFTWARE & MODELING INPUT........................................................ 60 4.1. Choosing Simulation Software ....................................................................................... 61 4.2. Tedious Process of making model ................................................................................. 65 4.3. Design Builder Model ..................................................................................................... 71 4.4. Building Inputs ............................................................................................................... 74 4.5. Building Variables – Per Space Type .............................................................................. 80 4.6. Schedules ....................................................................................................................... 88 CHAPTER ‐ 5: LOAD BALANCE & PRELIMINARY CHECK OF MODEL ............................................... 91 5.1. Comparison to Utility Data & CEUS ............................................................................... 92 5.2. Manual Load Balance Calculations ................................................................................ 94 5.3. Envelope Loads from Design Builder ............................................................................. 97 5.4. Comparing Manual Calculations & Design Builder Outputs .......................................... 98 5.5. Final Improvements to Model & its Accuracy .............................................................. 104 5.6. Problems Faced During Simulations ............................................................................ 106 CHAPTER ‐ 6: BASELINE CASE ....................................................................................................... 108 6.1. Calibrated Model Error Margin .................................................................................... 109 6.2. 1 st Annual Simulation Attempt ..................................................................................... 110 6.3. 2 nd Attempt with Schedule Modification ..................................................................... 113 6.4. Baseline Model ............................................................................................................. 117 6.5. Conclusion .................................................................................................................... 120 CHAPTER ‐ 7 :HVAC ISSUES .......................................................................................................... 121 7.1. Original HVAC system .................................................................................................. 122 7.2. Modified HVAC system ................................................................................................ 123 7.3. Modeling of HVAC in Design Builder ............................................................................ 126 CHAPTER ‐ 8: FULL BUILDING CALIBRATION ................................................................................ 135 8.1. Chiller Adjustments ...................................................................................................... 136 8.2. Pumps .......................................................................................................................... 149 8.3. Air Handling Units ........................................................................................................ 149 8.4. Cooling Tower .............................................................................................................. 150 8.5. Heating ......................................................................................................................... 150 8.6. VKC Chiller Calibration ................................................................................................. 151 8.7. Full Building Calibration Process .................................................................................. 154 vii CHAPTER ‐ 9: CALIBRATED MODEL & GAS ISSUES ....................................................................... 165 9.1. Calibrated Model ......................................................................................................... 166 9.2. Comparison to VKC Model ........................................................................................... 171 9.3. Gas Issues ..................................................................................................................... 176 9.4. Conclusions .................................................................................................................. 183 CHAPTER ‐ 10: ENERGY EFFICIENCY MEASURES .......................................................................... 185 10.1. Pre‐M&V Plan ........................................................................................................... 186 10.2. Lighting EEMs ........................................................................................................... 187 10.3. Envelope EEMs ......................................................................................................... 193 10.4. HVAC EEMs .............................................................................................................. 200 10.5. Executive Summary .................................................................................................. 212 10.6. Analysis of all EEMs .................................................................................................. 220 CHAPTER ‐ 11: ZNE PROPOSAL ..................................................................................................... 222 11.1. Selection & Sequence of EEMs ................................................................................ 223 11.2. Executive Summary .................................................................................................. 236 11.3. ZNE Calculations ....................................................................................................... 244 11.4. Operational Cost Savings ......................................................................................... 246 11.5. Summary & Conclusions .......................................................................................... 247 11.6. Future Work ............................................................................................................. 250 BIBLIOGRAPHY ............................................................................................................................. 253 APPENDICES APPENDIX A: UTILITY INFORMATION ...................................................................................... 256 APPENDIX B: SCHEDULES ........................................................................................................ 259 APPENDIX C: INFORMATION OBTAINED FROM FMS .............................................................. 264 viii LIST OF FIGURES Figure 1: Measured Versus Proposed Savings Percentages ............................................................ 3 Figure 2: Site Location of VKC ........................................................................................................ 23 Figure 3: Temperature Range Graph ............................................................................................. 24 Figure 4: Wind Analysis .................................................................................................................. 24 Figure 5: Psychometric Chart ......................................................................................................... 25 Figure 6: ASHRAE Design Day Values ............................................................................................. 26 Figure 7: VKC Building ................................................................................................................... 27 Figure 8: Revit Model of VKC Building ........................................................................................... 27 Figure 9: Central Amphitheater (basement) .................................................................................. 28 Figure 10: Plant Beds around the building ..................................................................................... 28 Figure 11: VKC Basement Floor Plan .............................................................................................. 28 Figure 12: VKC First Floor Plan ....................................................................................................... 28 Figure 13: VKC Second Floor Plan .................................................................................................. 29 Figure 14: VKC Third Floor Plan ..................................................................................................... 29 Figure 15: Exterior of VKC .............................................................................................................. 29 Figure 16: Exterior of VKC .............................................................................................................. 29 Figure 17: Internal Finish ............................................................................................................... 30 Figure 18: Internal Finish ‐ Typical Classroom ............................................................................... 30 Figure 19: Air Handling Unit‐ 1, Courtesy of USC Facilities Management, 2011 ........................... 31 ix Figure 20: Air Handling Unit‐ 1 Amps, Courtesy of USC Facilities Management, 2011 ................. 31 Figure 21: Air Handling Unit‐ 3, Courtesy of USC Facilities Management, 2011 ........................... 32 Figure 22: Air Handling Unit‐ 4, Courtesy of USC Facilities Management, 2011 ........................... 32 Figure 23: Chiller & Cooling Tower Layout, Courtesy of USC Facilities Management, 2011 ......... 33 Figure 24: Lighting system inside library........................................................................................ 35 Figure 25: Lighting system inside library........................................................................................ 35 Figure 26: HID Fixtures ................................................................................................................... 35 Figure 27: HID Fixtures ................................................................................................................... 35 Figure 28: First Floor Plan showing the control possibilities ......................................................... 37 Figure 29: Second Floor Plan showing the control possibilities..................................................... 37 Figure 30: Third Floor Plan showing the control possibilities ........................................................ 38 Figure 31: Metered Gas Consumption of VKC ............................................................................... 41 Figure 32: Immediate surroundings of VKC (in yellow) ................................................................. 44 Figure 33: Solar Shade Analysis on 15th March ............................................................................. 45 Figure 34: Solar Shade Analysis on 15th June ................................................................................ 45 Figure 35: Solar Shade Analysis on 15th September ..................................................................... 45 Figure 36: Solar Shade Analysis on 15th Dec ................................................................................. 45 Figure 37: Energy Benchmarking: Energy Use Intensity (EUI) Comparison ................................... 46 Figure 38: VKC Roof plan showing the layout of PV Panels ........................................................... 49 Figure 39: Inputs for PV Watts ....................................................................................................... 50 Figure 40: Output (predicted generation) of PV Watts ................................................................. 51 Figure 41: ZNE Target (Based on Consumption) ............................................................................ 52 x Figure 42: ZNE target (Based on Energy Use Intensity) ................................................................. 52 Figure 43: FLIR Thermal Camera .................................................................................................... 53 Figure 44: Light Transmitter ........................................................................................................... 53 Figure 45: Kill‐A‐Watt Strip ............................................................................................................ 53 Figure 46: Power Quality Logger .................................................................................................... 53 Figure 47: SHGC Calculator ............................................................................................................ 53 Figure 48: Manual R‐Value Calculations ........................................................................................ 54 Figure 49: Manual R‐Value Calculations ........................................................................................ 54 Figure 50: ITS Manager .................................................................................................................. 55 Figure 51: Wall Box ........................................................................................................................ 55 Figure 52: Measuring Loads of Wall Box Component .................................................................... 56 Figure 53: Measuring Load of Projector ........................................................................................ 56 Figure 54: Thermal Image above False Ceiling............................................................................... 58 Figure 55: Thermal Image Looking at Diffuser ............................................................................... 58 Figure 56: Revit Model of VKC ....................................................................................................... 66 Figure 57: Ecotect Model of VKC ................................................................................................... 67 Figure 58: Design Builder Model of VKC ........................................................................................ 67 Figure 59: Location of Site & Weather Station, courtesy Weather Analytics, 2011 ...................... 70 Figure 60: Design Builder Model (South View) .............................................................................. 71 Figure 61: Design Builder Model (North View) .............................................................................. 71 Figure 62: Model Setting in Design Builder ................................................................................... 73 Figure 63: Layout of all spaces in VKC ............................................................................................ 74 xi Figure 64: Conditioned & Non Conditioned Spaces in VKC ........................................................... 75 Figure 65: Cross Section of VKC Walls ........................................................................................... 76 Figure 66: VKC Wall Properties ...................................................................................................... 76 Figure 67: Cross Section of Roof .................................................................................................... 76 Figure 68: VKC Roof Properties ...................................................................................................... 76 Figure 69: Cross Section of Typical Floor ....................................................................................... 77 Figure 70: VKC Typical Floor Properties ......................................................................................... 77 Figure 71: Cross Section of Basement Floor .................................................................................. 77 Figure 72: VKC Basement Floor Properties .................................................................................... 77 Figure 73: Cross Section of Retaining Wall .................................................................................... 78 Figure 74: VKC Retaining Wall Properties ...................................................................................... 78 Figure 75: Cross Section of Door .................................................................................................... 78 Figure 76: VKC Door Properties ..................................................................................................... 78 Figure 77: Design Builder Glass Inputs ........................................................................................... 79 Figure 78: Glazing Properties ......................................................................................................... 79 Figure 79: Initial Annual Electrical Comparison ............................................................................. 92 Figure 80:Initial Annual Gas Comparison ....................................................................................... 92 Figure 81: CEUS End Use (Colleges Category) ................................................................................ 93 Figure 82: Design Builder Predicted End Use ................................................................................. 93 Figure 83: Percentage of Fuel Consumed ...................................................................................... 93 Figure 84: EUI of Metered Data versus DB .................................................................................... 93 Figure 85: Coefficient of Variation of the root mean squared error (Pan, Huang & Wu 2007) .. 110 xii Figure 86: 1st Attempt Electrical Comparison ............................................................................. 111 Figure 87: 1st Attempt Electrical Comparison ............................................................................. 111 Figure 88: 1st Attempt Gas Comparison ...................................................................................... 111 Figure 89: 1st Attempt Gas Comparison ...................................................................................... 111 Figure 90: Electrical Consumption Closer Look ............................................................................ 112 Figure 91: Gas Consumption Closer Look .................................................................................... 112 Figure 92: CEUS End Use .............................................................................................................. 112 Figure 93: DB End Use for 1 st Attempt ......................................................................................... 112 Figure 94: EUI Comparison for 1st Attempt ................................................................................. 113 Figure 95: 1st Attempt consumption versus CEUS ...................................................................... 113 Figure 96: 2nd Attempt Electrical Comparison ............................................................................ 114 Figure 97: 2nd Attempt Electrical Comparison ............................................................................ 114 Figure 98: 2nd Attempt Gas Comparison .................................................................................... 114 Figure 99: 2nd Attempt Gas Comparison .................................................................................... 114 Figure 100: Electrical Energy End Use .......................................................................................... 115 Figure 101: Gas Consumption End Use ........................................................................................ 115 Figure 102: CEUS End Use ............................................................................................................ 116 Figure 103: DB End Use for 2nd Attempt..................................................................................... 116 Figure 104: EUI Comparison for 2nd Attempt ............................................................................. 116 Figure 105: 1st Attempt consumption versus CEUS .................................................................... 116 Figure 106: Baseline Model Electrical Comparison ..................................................................... 117 Figure 107: Baseline Model Electrical Comparison ..................................................................... 117 xiii Figure 108: Baseline Model Gas Comparison .............................................................................. 118 Figure 109: Baseline Model Gas Comparison .............................................................................. 118 Figure 110: Baseline Model Electrical End Use ............................................................................ 118 Figure 111: Baseline Model Gas End Use ..................................................................................... 119 Figure 112: CEUS End Use ............................................................................................................ 119 Figure 113: Baseline Model End Use ........................................................................................... 119 Figure 114: EUI Comparison for Baseline Model ......................................................................... 120 Figure 115: Baseline Consumption versus CEUS .......................................................................... 120 Figure 116: HVAC Distribution System......................................................................................... 122 Figure 117: Original Constant Volume Dual Duct System ........................................................... 123 Figure 118: Modified HVAC Systems ........................................................................................... 124 Figure 119: Modified HVAC System ............................................................................................. 125 Figure 120: Error Messages in Design Builder ............................................................................. 127 Figure 121: 1st Approach of Modeling HVAC System .................................................................. 128 Figure 122: Electrical Comparison ............................................................................................... 129 Figure 123: Electrical Comparison Data ....................................................................................... 129 Figure 124: Gas Comparison ........................................................................................................ 130 Figure 125: Gas Consumption Curve............................................................................................ 130 Figure 126: 1st HVAC Approach End Use ..................................................................................... 130 Figure 127: 1st HVAC Approach EUI Comparison ........................................................................ 130 Figure 128: 2nd Approach of Modeling HVAC System ................................................................ 132 Figure 129: 2nd Approach Electrical Comparison ........................................................................ 133 xiv Figure 130: 2nd Approach Gas Comparison ................................................................................ 133 Figure 131: 2nd Approach End Use .............................................................................................. 133 Figure 132: 2nd Approach EUI Comparison ................................................................................. 133 Figure 133: Electrical Energy based on end uses ......................................................................... 134 Figure 134: Snapshot of Chiller Consumption Spreadsheet ........................................................ 136 Figure 135: Chiller Electrical Consumption .................................................................................. 138 Figure 136: Chiller Properties in Design Builder .......................................................................... 139 Figure 137: Chiller Part Load Curve Study in MATLAB ................................................................. 141 Figure 138: Chiller Curve Slope Study .......................................................................................... 142 Figure 139: Snapshot of Step‐1 Slope Study Spreadsheet ........................................................... 142 Figure 140: Monthly Chiller Consumption (Step‐1) ..................................................................... 142 Figure 141: Snapshot of Step‐2 Exact Curve Spreadsheet ........................................................... 143 Figure 142: Monthly Chiller Curve Based on Exact Curve ............................................................ 143 Figure 143: Snapshot of Step‐3 Exact Curve with Proper Amps Spreadsheet ............................. 144 Figure 144: Monthly Chiller Consumption with Correct Curve and Amps .................................. 145 Figure 145: Chiller Energy Consumption Estimation Process ...................................................... 145 Figure 146: Energy Consumption Comparison for all Chiller Experiments .................................. 148 Figure 147: Energy Consumption Profiles for all Chiller Experiments ......................................... 148 Figure 148: Design Builder Inputs for Air Handling Units ............................................................ 150 Figure 149: Metered Chiller Consumption Comparison versus Model Predicted ....................... 151 Figure 150: Hourly Profile of 2010 Weather ................................................................................ 152 Figure 151: 2010 Hourly Weather Data ....................................................................................... 153 xv Figure 152: Design Builder Predicted Chiller Consumption and Monthly ODB Temperature ..... 153 Figure 153: Design Builder Predicted Chiller Consumption and Hourly ODB Temperature ........ 154 Figure 154: DB vs VKC Electrical Consumption ............................................................................ 156 Figure 155: DB vs VKC Electrical Consumption ............................................................................ 156 Figure 157: DB vs VKC Gas Consumption ..................................................................................... 156 Figure 158: Design Builder End Use ............................................................................................. 156 Figure 159: DB vs Measured Electrical End‐Use .......................................................................... 156 Figure 156: DB vs VKC Gas Consumption ..................................................................................... 156 Figure 160: DB vs VKC Electrical Consumption ............................................................................ 157 Figure 161: DB vs VKC Electrical Consumption ............................................................................ 157 Figure 163: DB vs VKC Gas Consumption ..................................................................................... 157 Figure 164: Design Builder End Use ............................................................................................. 157 Figure 165: DB vs Measured Electrical End‐Use .......................................................................... 157 Figure 162: DB vs VKC Gas Consumption ..................................................................................... 157 Figure 166: DB vs VKC Electrical Consumption ............................................................................ 158 Figure 167: DB vs VKC Electrical Consumption ............................................................................ 158 Figure 169: DB vs VKC Gas Consumption ..................................................................................... 158 Figure 170: Design Builder End Use ............................................................................................. 158 Figure 171: DB vs Measured Electrical End‐Use .......................................................................... 158 Figure 168: DB vs VKC Gas Consumption ..................................................................................... 158 Figure 172: DB vs VKC Electrical Consumption ............................................................................ 159 Figure 173: DB vs VKC Electrical Consumption ............................................................................ 159 xvi Figure 175: DB vs VKC Gas Consumption ..................................................................................... 159 Figure 176: Design Builder End Use ............................................................................................. 159 Figure 177: DB vs Measured Electrical End‐Use .......................................................................... 159 Figure 174: DB vs VKC Gas Consumption ..................................................................................... 159 Figure 178: DB vs VKC Electrical Consumption ............................................................................ 160 Figure 179: DB vs VKC Electrical Consumption ............................................................................ 160 Figure 181: DB vs VKC Gas Consumption ..................................................................................... 160 Figure 182: Design Builder End Use ............................................................................................. 160 Figure 183: DB vs Measured Electrical End‐Use .......................................................................... 160 Figure 180: DB vs VKC Gas Consumption ..................................................................................... 160 Figure 184: DB vs VKC Electrical Consumption ............................................................................ 161 Figure 185: DB vs VKC Electrical Consumption ............................................................................ 161 Figure 187: DB vs VKC Gas Consumption ..................................................................................... 161 Figure 188: Design Builder End Use ............................................................................................. 161 Figure 189: DB vs Measured Electrical End‐Use .......................................................................... 161 Figure 186: DB vs VKC Gas Consumption ..................................................................................... 161 Figure 190: DB vs VKC Electrical Consumption ............................................................................ 162 Figure 191: DB vs VKC Electrical Consumption ............................................................................ 162 Figure 193: DB vs VKC Gas Consumption ..................................................................................... 162 Figure 194: Design Builder End Use ............................................................................................. 162 Figure 195: DB vs Measured Electrical End‐Use .......................................................................... 162 Figure 192: DB vs VKC Gas Consumption ..................................................................................... 162 xvii Figure 196: DB vs VKC Electrical Consumption ............................................................................ 163 Figure 197: DB vs VKC Electrical Consumption ............................................................................ 163 Figure 199: DB vs VKC Gas Consumption ..................................................................................... 163 Figure 200: Design Builder End Use ............................................................................................. 163 Figure 201: DB vs Measured Electrical End‐Use .......................................................................... 163 Figure 198: DB vs VKC Gas Consumption ..................................................................................... 163 Figure 202: Combined Electrical Calibration Runs ....................................................................... 164 Figure 203: Combined Gas Calibration Runs ............................................................................... 164 Figure 204: Internal Gains (Monthly) ........................................................................................... 166 Figure 205: System Loads (Monthly) ........................................................................................... 166 Figure 206: Fuel Breakdown ........................................................................................................ 167 Figure 207: Total Fuel Consumption ............................................................................................ 167 Figure 208: Fabric & Ventilation .................................................................................................. 167 Figure 209: CO2 Production (Monthly) ........................................................................................ 168 Figure 210: Internal Gains ............................................................................................................ 168 Figure 211: System Loads ............................................................................................................ 169 Figure 212: Fuel Breakdown ........................................................................................................ 169 Figure 213: Total Fuel Consumption ............................................................................................ 169 Figure 214: Fabric and Ventilation ............................................................................................... 170 Figure 215: Inside and Outside Temperatures ............................................................................ 170 Figure 216: CO2 Production ......................................................................................................... 170 Figure 217: DB vs VKC predicted Electrical Consumption ........................................................... 171 xviii Figure 218: DB vs VKC predicted Electrical Consumption ........................................................... 172 Figure 219: DB vs VKC predicted Gas Consumption .................................................................... 172 Figure 220: DB vs VKC predicted Electrical Consumption ........................................................... 173 Figure 221: EUI Comparison ........................................................................................................ 173 Figure 222: Calibrated Model End Use ........................................................................................ 174 Figure 224: Calibrated Model Gas End Use ................................................................................. 175 Figure 223: Calibrated Model Electrical End Use ......................................................................... 175 Figure 225: Design Builder Predicted Heat Loss Estimation (Graphical) ..................................... 179 Figure 226: Design Builder Predicted Heat Loss Estimation (Data) ............................................. 179 Figure 227: Calibrated Model End Use ........................................................................................ 186 Figure 228: Electrical Comparison ............................................................................................... 189 Figure 229: Gas Comparison ........................................................................................................ 189 Figure 230: End Use Electrical Comparison ................................................................................. 189 Figure 231: End Use Gas Comparison .......................................................................................... 189 Figure 232: EEM predicted end use ............................................................................................. 189 Figure 233: EUI Comparison b/w EEM & Calibrated .................................................................... 189 Figure 234: Electrical Comparison ............................................................................................... 190 Figure 235: Gas Comparison ........................................................................................................ 190 Figure 236: End Use Electrical Comparison ................................................................................. 190 Figure 237: End Use Gas Comparison .......................................................................................... 190 Figure 238: EEM predicted end use ............................................................................................. 190 Figure 239: EUI Comparison b/w EEM & Calibrated .................................................................... 190 xix Figure 240: Electrical Comparison ............................................................................................... 191 Figure 241: Gas Comparison ........................................................................................................ 191 Figure 242: End Use Electrical Comparison ................................................................................. 191 Figure 243: End Use Gas Comparison .......................................................................................... 191 Figure 244: EEM predicted end use ............................................................................................. 191 Figure 245: EUI Comparison b/w EEM & Calibrated .................................................................... 191 Figure 246: Electrical Comparison ............................................................................................... 192 Figure 247: Gas Comparison ........................................................................................................ 192 Figure 248: End Use Electrical Comparison ................................................................................. 192 Figure 249: End Use Gas Comparison .......................................................................................... 192 Figure 250: EEM predicted end use ............................................................................................. 192 Figure 251: EUI Comparison b/w EEM & Calibrated .................................................................... 192 Figure 252: Electrical Comparison ............................................................................................... 194 Figure 253: Gas Comparison ........................................................................................................ 194 Figure 254: End Use Electrical Comparison ................................................................................. 194 Figure 255: End Use Gas Comparison .......................................................................................... 194 Figure 256: EEM predicted end use ............................................................................................. 194 Figure 257: EUI Comparison b/w EEM & Calibrated .................................................................... 194 Figure 258: Electrical Comparison ............................................................................................... 195 Figure 259: Gas Comparison ........................................................................................................ 195 Figure 260: End Use Electrical Comparison ................................................................................. 195 Figure 261: End Use Gas Comparison .......................................................................................... 195 xx Figure 262: EEM predicted end use ............................................................................................. 195 Figure 263: EUI Comparison b/w EEM & Calibrated .................................................................... 195 Figure 264: Electrical Comparison ............................................................................................... 196 Figure 265: Gas Comparison ........................................................................................................ 196 Figure 266: End Use Electrical Comparison ................................................................................. 196 Figure 267: End Use Gas Comparison .......................................................................................... 196 Figure 268: EEM predicted end use ............................................................................................. 196 Figure 269: EUI Comparison b/w EEM & Calibrated .................................................................... 196 Figure 270: Electrical Comparison ............................................................................................... 197 Figure 271: Gas Comparison ........................................................................................................ 197 Figure 272: End Use Electrical Comparison ................................................................................. 197 Figure 273: End Use Gas Comparison .......................................................................................... 197 Figure 274: EEM predicted end use ............................................................................................. 197 Figure 275: EUI Comparison b/w EEM & Calibrated .................................................................... 197 Figure 276: Electrical Comparison ............................................................................................... 198 Figure 277: Gas Comparison ........................................................................................................ 198 Figure 278: End Use Electrical Comparison ................................................................................. 198 Figure 279: End Use Gas Comparison .......................................................................................... 198 Figure 280: EEM predicted end use ............................................................................................. 198 Figure 281: EUI Comparison b/w EEM & Calibrated .................................................................... 198 Figure 282: Electrical Comparison ............................................................................................... 199 Figure 283: Gas Comparison ........................................................................................................ 199 xxi Figure 284: End Use Electrical Comparison ................................................................................. 199 Figure 285: End Use Gas Comparison .......................................................................................... 199 Figure 286: EEM predicted end use ............................................................................................. 199 Figure 287: EUI Comparison b/w EEM & Calibrated .................................................................... 199 Figure 288: Electrical Comparison ............................................................................................... 203 Figure 289: Gas Comparison ........................................................................................................ 203 Figure 290: End Use Electrical Comparison ................................................................................. 203 Figure 291: End Use Gas Comparison .......................................................................................... 203 Figure 292: EEM predicted end use ............................................................................................. 203 Figure 293: EUI Comparison b/w EEM & Calibrated .................................................................... 203 Figure 294: Electrical Comparison ............................................................................................... 204 Figure 295: Gas Comparison ........................................................................................................ 204 Figure 296: End Use Electrical Comparison ................................................................................. 204 Figure 297: End Use Gas Comparison .......................................................................................... 204 Figure 298: EEM predicted end use ............................................................................................. 204 Figure 299: EUI Comparison b/w EEM & Calibrated .................................................................... 204 Figure 300: Electrical Comparison ............................................................................................... 205 Figure 301: Gas Comparison ........................................................................................................ 205 Figure 302: End Use Electrical Comparison ................................................................................. 205 Figure 303: End Use Gas Comparison .......................................................................................... 205 Figure 304: EEM predicted end use ............................................................................................. 205 Figure 305: EUI Comparison b/w EEM & Calibrated .................................................................... 205 xxii Figure 306: Electrical Comparison ............................................................................................... 206 Figure 307: Gas Comparison ........................................................................................................ 206 Figure 308: End Use Electrical Comparison ................................................................................. 206 Figure 309: End Use Gas Comparison .......................................................................................... 206 Figure 310: EEM predicted end use ............................................................................................. 206 Figure 311: EUI Comparison b/w EEM & Calibrated .................................................................... 206 Figure 312: Electrical Comparison ............................................................................................... 207 Figure 313: Gas Comparison ........................................................................................................ 207 Figure 314: End Use Electrical Comparison ................................................................................. 207 Figure 315: End Use Gas Comparison .......................................................................................... 207 Figure 316: EEM predicted end use ............................................................................................. 207 Figure 317: EUI Comparison b/w EEM & Calibrated .................................................................... 207 Figure 318: Electrical Comparison ............................................................................................... 208 Figure 319: Gas Comparison ........................................................................................................ 208 Figure 320: End Use Electrical Comparison ................................................................................. 208 Figure 321: End Use Gas Comparison .......................................................................................... 208 Figure 322: EEM predicted end use ............................................................................................. 208 Figure 323: EUI Comparison b/w EEM & Calibrated .................................................................... 208 Figure 324: Electrical Comparison ............................................................................................... 209 Figure 325: Gas Comparison ........................................................................................................ 209 Figure 326: End Use Electrical Comparison ................................................................................. 209 Figure 327: End Use Gas Comparison .......................................................................................... 209 xxiii Figure 328: EEM predicted end use ............................................................................................. 209 Figure 329: EUI Comparison b/w EEM & Calibrated .................................................................... 209 Figure 330: Electrical Comparison ............................................................................................... 210 Figure 331: Gas Comparison ........................................................................................................ 210 Figure 332: End Use Electrical Comparison ................................................................................. 210 Figure 333: End Use Gas Comparison .......................................................................................... 210 Figure 334: EEM predicted end use ............................................................................................. 210 Figure 335: EUI Comparison b/w EEM & Calibrated .................................................................... 210 Figure 336: Electrical Comparison ............................................................................................... 211 Figure 337: Gas Comparison ........................................................................................................ 211 Figure 338: End Use Electrical Comparison ................................................................................. 211 Figure 339: End Use Gas Comparison .......................................................................................... 211 Figure 340: EEM predicted end use ............................................................................................. 211 Figure 341: EUI Comparison b/w EEM & Calibrated .................................................................... 211 Figure 342: End Use Comparisons of all EEMs ............................................................................. 213 Figure 343: Percentile Difference of each end use of EEM with calibrated model ..................... 213 Figure 344: Total Electrical Use for the Alternatives ................................................................... 214 Figure 345: Total Gas Use for Alternatives .................................................................................. 214 Figure 346: Lighting End Use for all alternatives ......................................................................... 215 Figure 347: Exterior Lighting End Use for all alternatives ............................................................ 215 Figure 348: Equipment End Use for all alternatives .................................................................... 216 Figure 349: Cooling End Use for all alternatives .......................................................................... 216 xxiv Figure 350: Heating End Use for all alternatives ......................................................................... 217 Figure 351: Fans End Use for all Alternatives .............................................................................. 217 Figure 352: Pumps End Use for all Alternatives ........................................................................... 218 Figure 353: End use for Domestic Hot Water .............................................................................. 218 Figure 354: Cooling Tower End Use for all Alternatives .............................................................. 219 Figure 355: Annual Operation Cost Savings for all alternatives .................................................. 219 Figure 356: Electrical Comparison of Final EEM .......................................................................... 226 Figure 357: Electrical Comparison of Final EEM .......................................................................... 226 Figure 358: End Use Electrical Comparison ................................................................................. 226 Figure 359: End Use Gas Comparison .......................................................................................... 226 Figure 360: EEM predicted end use ............................................................................................. 226 Figure 361: EUI Comparison b/w EEM & Calibrated .................................................................... 226 Figure 362: Electrical Comparison of Final EEMs ......................................................................... 227 Figure 363: Gas Comparison of Final EEMs ................................................................................. 227 Figure 364: End Use Electrical Comparison ................................................................................. 227 Figure 365: End Use Gas Comparison .......................................................................................... 227 Figure 366: EEM predicted end use ............................................................................................. 227 Figure 367: EUI Comparison b/w EEM & Calibrated .................................................................... 227 Figure 368: Electrical Comparison of Final EEMs ......................................................................... 228 Figure 369: Gas Comparison of Final EEMs ................................................................................. 228 Figure 370: End Use Electrical Comparison ................................................................................. 228 Figure 371: End Use Gas Comparison .......................................................................................... 228 xxv Figure 372: EEM predicted end use ............................................................................................. 228 Figure 373: EUI Comparison b/w EEM & Calibrated .................................................................... 228 Figure 374: Electrical Comparison of Final EEMs ......................................................................... 229 Figure 375: Gas Comparison of Final EEMs ................................................................................. 229 Figure 376: End Use Electrical Comparison ................................................................................. 229 Figure 377: End Use Gas Comparison .......................................................................................... 229 Figure 378: EEM predicted end use ............................................................................................. 229 Figure 379: EUI Comparison b/w EEM & Calibrated .................................................................... 229 Figure 380: Electrical Comparison of Final EEMs ......................................................................... 230 Figure 381: Gas Comparison of Final EEMs ................................................................................. 230 Figure 382: End Use Electrical Comparison ................................................................................. 230 Figure 383: End Use Gas Comparison .......................................................................................... 230 Figure 384: EEM predicted end use ............................................................................................. 230 Figure 385: EUI Comparison b/w EEM & Calibrated .................................................................... 230 Figure 386: Electrical Comparison of Final EEMs ......................................................................... 231 Figure 387: Gas Comparison of Final EEMs ................................................................................. 231 Figure 388: End Use Electrical Comparison ................................................................................. 231 Figure 389: End Use Gas Comparison .......................................................................................... 231 Figure 390: EEM predicted end use ............................................................................................. 231 Figure 391: EUI Comparison b/w EEM & Calibrated .................................................................... 231 Figure 392: Electrical Comparison of Final EEMs ......................................................................... 232 Figure 393: Gas Comparison of Final EEMs ................................................................................. 232 xxvi Figure 394: End Use Electrical Comparison ................................................................................. 232 Figure 395: End Use Gas Comparison .......................................................................................... 232 Figure 396: EEM predicted end use ............................................................................................. 232 Figure 397: EUI Comparison b/w EEM & Calibrated .................................................................... 232 Figure 398: Electrical Comparison of Final EEMs ......................................................................... 233 Figure 399: Gas Comparison of Final EEMs ................................................................................. 233 Figure 400: End Use Electrical Comparison ................................................................................. 233 Figure 401: End Use Gas Comparison .......................................................................................... 233 Figure 402: EEM predicted end use ............................................................................................. 233 Figure 403: EUI Comparison b/w EEM & Calibrated .................................................................... 233 Figure 404: Electrical Comparison of Final EEMs ......................................................................... 234 Figure 405: Gas Comparison of Final EEMs ................................................................................. 234 Figure 406: End Use Electrical Comparison ................................................................................. 234 Figure 407: End Use Gas Comparison .......................................................................................... 234 Figure 408: EEM predicted end use ............................................................................................. 234 Figure 409: EUI Comparison b/w EEM & Calibrated .................................................................... 234 Figure 410: Electrical Comparison of Final EEMs ......................................................................... 235 Figure 411: Gas Comparison of Final EEMs ................................................................................. 235 Figure 412: End Use Electrical Comparison ................................................................................. 235 Figure 413: End Use Gas Comparison .......................................................................................... 235 Figure 414: EEM predicted end use ............................................................................................. 235 Figure 415: EUI Comparison b/w EEM & Calibrated .................................................................... 235 xxvii Figure 416: Comparison of Electrical Consumption of all proposed EEMs .................................. 236 Figure 417: Comparison of Gas Consumption of all proposed EEMs .......................................... 236 Figure 418: Energy Consumption by all EEMs ............................................................................. 237 Figure 419: Total Electrical Consumption for Alternatives .......................................................... 238 Figure 420: Total Gas Use for Alternatives .................................................................................. 238 Figure 421: Lighting End Use for Alternatives.............................................................................. 239 Figure 422: External Lighting End Use for Alternatives ............................................................... 239 Figure 423: Equipment End Use for Alternatives ......................................................................... 240 Figure 424: Cooling End Use for Alternatives .............................................................................. 240 Figure 425: Heating End Use for Alternatives .............................................................................. 241 Figure 426: Fan End Use for Alternatives .................................................................................... 241 Figure 427: Pumps End Use for Alternatives ............................................................................... 242 Figure 428: Domestic Hot Water End Use for Alternatives ......................................................... 242 Figure 429: Cooling Tower End Use for Alternatives ................................................................... 243 Figure 430: Operational Cost Savings for Alternatives ................................................................ 243 Figure 431: EUI Comparison of Final EEM to Calibrated Model .................................................. 244 Figure 432: ZNE Calculations........................................................................................................ 245 Figure 433: End Use Comparison between Calibrated Model and ZNE version of VKC .............. 245 Figure 434: Cost Analysis ............................................................................................................. 246 Figure 435: Electrical Consumption Profiles of VKC from 2001 to 2011 ..................................... 257 Figure 436: Submittal of VKC Pumps, Courtesy FMS (USC) , 2011 .............................................. 271 Figure 437: Submittal of VKC Pumps, Courtesy FMS (USC) , 2011 .............................................. 272 xxviii Figure 438: Submittal of VKC Pumps, Courtesy FMS (USC) , 2011 .............................................. 273 Figure 439: Condensate Return Unit Submittal, Courtesy FMS (USC) , 2011 .............................. 274 Figure 440: Condensate Return Unit Submittal, Courtesy FMS (USC) , 2011 .............................. 275 Figure 441: Water Coils Submittal, Courtesy FMS (USC) , 2011 .................................................. 276 Figure 442: Air Filter used in VKC, Courtesy FMS (USC) , 2011 .................................................... 277 Figure 443: Variable Speed Drive installed at VKC, Courtesy FMS (USC) , 2011 .......................... 278 Figure 444: Variable Frequency Drive Specifications, Courtesy FMS (USC) , 2011 ...................... 279 xxix LIST OF TABLES Table 1: Zero Net Energy Definitions Based on NREL Definitions .................................................... 6 Table 2: Acceptable tolerance for monthly data calibration ......................................................... 16 Table 3 General Description of the building .................................................................................. 27 Table 4: Measured Plug Loads ....................................................................................................... 56 Table 5: Exterior Lighting Statistics ................................................................................................ 80 Table 6: Simulation Inputs for Classrooms .................................................................................... 81 Table 7: Simulation Inputs for Offices ............................................................................................ 82 Table 8: Simulation Inputs for Library Spaces ................................................................................ 83 Table 9: Simulation Inputs for Computer Labs .............................................................................. 84 Table 10: Simulation Inputs for Circulation Spaces ....................................................................... 85 Table 11: Simulation Inputs for Restrooms ................................................................................... 86 Table 12: Simulation Inputs for Mechanical Rooms ...................................................................... 87 Table 13: USC 2010 Calendar Schedule ......................................................................................... 88 Table 14Process of Third Experiment: ......................................................................................... 104 Table 15: Acceptable tolerance for monthly data calibration ..................................................... 109 xxx Table 16: Description of Chiller Experiments ............................................................................... 147 Table 17: End Uses of all Chiller Experiments .............................................................................. 147 Table 18: Manual Heat Loss Calculations .................................................................................... 178 Table 19: Heat Loss (By Component) Comparison b/w Manual Calculations & DB .................... 180 Table 20: Metered, Design Builder & eQuest predicted Gas Consumption ................................ 182 Table 21: End Use Consumption of all EEMs ............................................................................... 212 Table 23: End Use of all EEMs ...................................................................................................... 237 Table 24: Percentage Differences of all End Uses from Calibrated Model ................................. 237 Table 25: VKC Gas Consumption Based on Consumption Month ............................................... 256 Table 26: VKC Gas Consumption Based on Billing Month ........................................................... 256 Table 39: Electrical Consumption of VKC from 2001 to 2011 ...................................................... 257 Table 38: Fifteen Minute Interval Electrical Consumption (KW) as obtained from FMS ............. 258 Table 27: Schedule Used for Design Builder Simulation Model (Fractional) ............................... 259 Table 28: Schedule Used for Design Builder Simulation Model (Fractional) ............................... 260 Table 29: Schedule Used for Design Builder Simulation Model (Fractional) ............................... 261 Table 30: Schedule Used for Design Builder Simulation Model (Fractional) ............................... 262 Table 31: Schedule Used for Design Builder Simulation Model (Temperature) .......................... 263 xxxi Table 32: Areas of VKC Rooms on First Floor, Courtesy FMS (USC) , 2011 .................................. 264 Table 33: Areas of VKC Rooms on Second Floor, Courtesy FMS (USC) , 2011 ............................. 265 Table 34: Areas of VKC Rooms on Third Floor, Courtesy FMS (USC) , 2011 ................................ 266 Table 37: VKC Lighting Inventory (08/122/00) obtained from FMS, 2011 .................................. 267 Table 40: Air Balance Report of Air Handling Unit (AHU) ‐ 1 & 3, Courtesy FMS (USC) , 2011 ... 268 Table 41: Air Balance Report of Air Handling Unit (AHU) ‐ 2, Courtesy FMS (USC) , 2011 .......... 269 Table 42: Air Balance Report of Air Handling Unit (AHU) ‐ 4, Courtesy FMS (USC) , 2011 .......... 270 Table 43: Centralized Hot Water Details, Courtesy FMS (USC) , 2011 ........................................ 280 Table 44: Exhaust Fan Details, Courtesy FMS (USC), 2011 .......................................................... 281 Table 45: Supply Air Fan Details, Courtesy FMS (USC), 2011 ....................................................... 282 Table 46: Sump Pumps Details, Courtesy FMS (USC), 2011......................................................... 283 Table 47: Fire/House Pumps Details, Courtesy FMS (USC), 2011 ................................................ 284 xxxii ABSTRACT With the current rapid depletion of non-renewable resources to generate power, energy conservation and on site generation have become the most critical aspects of the equation. Buildings should be so designed or retrofitted in order to generate its own electricity and cater to its own demand. This thesis looks as the ways in which we can do a post occupancy analysis of an existing institutional building of about 95,000 square feet that was built in 1960’s in order to reduce usage and approach a Zero Net Energy goal. This case study building is Von Kleinsmid Centre (VKC) which is located at the heart of USC (University of Southern California). It is challenging to retrofit an existing institutional building because of its complexity and make it achieve a ‘Zero Net Energy’ goal. All the roadblocks, real life delays, software limitations that had to be overcome to achieve this result are explained in this thesis. The Zero Net Energy goal was achieved by calibrating energy model to the utility data of the building, providing various energy efficiency measures and generating on-site electricity. 1 CHAPTER - 1: BACKGROUND INFORMATION This Chapter gives an introduction to thesis topic, explains zero net energy concepts, briefs about Whole Building Energy Analysis and describes related terms and standards. A calibration simulation approach is discussed with the comparisons of various simulation softwares that are available in the market to carry out this task. 2 1.1. Hypothesis It is possible to achieve net zero energy goal for an existing institutional building by calibrating an energy model to the utility data of the building, providing various energy efficiency measures and generating on-site electricity. 1.2. Introduction For the last couple of decades, Whole Building Energy Simulation has played a very important role in building design, operation, diagnostics, evaluation and commissioning of buildings (Pan, Huang & Wu 2007). It has almost become an essential step for designing or to do post-occupancy analysis (Pan, Huang & Wu 2007). These simulations have helped designers to compare various design options and have guided them to more optimal and energy efficient designs. Today we are in the era when we need these simulations tools to actually guide us to take one step forward and help us design Net Zero Energy buildings (Marszal et al. 2011). With the current rapid depletion of non-renewable resources to generate power, energy conservation and on site generation have become the most critical aspects of the equation. Buildings should be so designed in order to generate its own electricity and cater to its own demand. However, only designing new Zero Net Energy buildings will not solve the problem. Out of total energy consumed by U.S. which is a major chunk (20%) of global energy consumed, minimalistic amount is consumed by new buildings and majority is been used by already existing buildings (Mazria 2009). We need to focus on achieving Zero Net Energy goal for existing buildings in order to reduce energy consumption drastically. 3 Many people ask why we need to focus on Zero Net Energy goals when LEED has come up with a certification process which is highly beneficial in energy reduction. This is a very good step in order to reduce the energy consumption. However, as per the 2008 report on ‘Energy Performance of LEED for New Construction Buildings’, one quarter of the LEED certified buildings use much more than their proposed usage. Some of the buildings even uses more energy than the code baseline itself (Turner & Frankel 2008). Figure 1: Measured Versus Proposed Savings Percentages The figure which is taken from the same report clearly illustrates that the buildings that even got platinum rating barely meets the proposed saving mark. Quite a few among platinum rated are using more energy than the code baseline. LEED has raised the issue but a lot more work is yet to be done. Even if the buildings look really energy efficient on paper at the time of design submission, the building doesn’t perform as it is expected. 4 Therefore, the Zero Net Energy goal is another parameter that aims for maximum efficiency and to take it one step ahead supports its own energy consumption. Keeping in mind the majority of energy consumption is by old buildings, an existing institutional building of around 95,000 sft which was built in 1960’s was chosen to be the case study for achieving the Zero Net Energy goal. It is challenging to retrofit an existing institutional building because of its complexity and make it achieve a ‘Zero Net Energy’ goal. Energy Plus and Design Builder are used in the Whole Building Design Simulation. The daily consumption of energy by the building was acquired from the Building Management System of the USC campus in addition to the monthly utility bills. A Whole Building Simulation model was made based on actual building drawings and specifications. Actual lighting power density, equipment power density values were calculated using the Inventory and some on-site measurements of plug loads. Various actual building schedules, namely occupancy, heating, cooling, lighting, ventilation were then utilized to make the model to behave as the actual building (Haberl & Bou-Saada 1998). Several iterations are completed in the model to finally calibrate it to the actual monthly utility bills. The model is further refined to match the daily consumption as acquired by BMS system. The model once calibrated is then repeatedly simulated with most logical modifications for conserving energy and reducing the net energy consumption of the building. Marginal returns are considered and optimized (Raftery, Keane & Donnell 2011). Alongside, site potential for creating renewable energy is explored. The potential energy generation is then estimated using PV Watts to estimate solar PV energy generated for the site. Finally, energy efficiency improvements when combined with On-Site energy 5 generation result in no net purchases from the electrical or gas grid on an annual basis. The calculations are shown to prove the final result. 1.3. Zero Net Energy Zero Net Energy is a very ambiguous term. The first step is to choose the correct definition that is to be followed and achieved. The second step is to define the process that is to be followed in order to achieve this goal. The third step is to identify the production source of renewable energy. 1.3.1. ZNE Definitions Currently, there are various definitions floating in the market that describes Zero Net Energy. This is because this generic term can be defined in various ways depending upon the boundary conditions and the metric to be followed. All these different definitions might be appropriate for different projects depending upon the project goals and the values of the design team and building owner. The designer might be more interested in site energy use for energy code requirements whereas the building owner might care more about energy costs. People who are concerned about pollution from power plants or from burning of fossil fuels would be interested in reducing emissions (Torcellini, Pless & Deru 2006) The National Renewable Energy Laboratory (NREL) has come up with four different definitions. These are net zero site energy, net zero source energy, net zero energy costs, and net zero energy emissions (Torcellini, Pless & Deru 2006). A brief description of these is illustrated below. 6 The symbol Ø in the above table shows the tentative amount of energy to be produced to achieve ZNE. More the Ø more on-site energy needs to be produced. 1.3.2. Energy Efficiency First, then On-Site Generation According to an ideal process and good ZNE definition, energy efficiency should be encouraged first, followed by the use of renewable energy sources available on site. In other words, site energy usage should be reduced through low-energy building technologies like day-lighting strategies, high-efficiency HVAC, natural ventilation, evaporative cooling etc. and only then resorting to on-site generation to cover up for the rest. These energy efficient measures are usually available for the full life of the building. However, these must have good persistence and should be constantly checked to make sure that they continue to save energy. Some of the on-site generation technologies available today include PV, solar hot water, wind, hydroelectric, and biofuels. All these renewable sources are favorable over conventional energy sources such as coal and natural gas. 1.3.3. Production Source On-Site Generation technologies can be classified into on-site and off-site production. Table 1: Zero Net Energy Definitions Based on NREL Definitions 7 On-Site production refers to those renewable technologies that are available within the building footprint and the site. Rooftop PV, solar heating, wind, parking based wind or PV systems are considered part of on-site production. Off-Site production refers to those renewable energy resources that are fetched from outside the boundary of the building site. Biomass, wood pellets, ethanol, or biodiesel can be imported from off site, or waste streams from on-site processes that can be used on-site to generate electricity and heat. We can even purchase off-site renewable energy sources. Utility-based wind, emissions credits, or other green purchasing options can be counted towards these (Torcellini, Pless & Deru 2006). There is a hierarchy that should be followed as per a good ZNE definition for renewable energy production. On-Site production within the building footprint is the first choice followed by energy generation within the site limits. Off-Site production fetched from outside the building site is the third choice followed by buying renewable credits (Torcellini, Pless & Deru 2006). 1.4. Benchmarking & Standards There are various standards and surveys in the market that can be used as benchmarks to compare the energy consumption of the case study building to that of other buildings of similar type in similar region. 1.4.1. Commercial Building Energy Consumption Survey (CBECS) One of the national sample surveys that collect information on all U.S. Commercial buildings is The Commercial Buildings Energy Consumption Survey (CBECS). It records energy-related building characteristics, their energy consumption and expenditures. 8 Buildings Use Description used in this survey are taken from a building activities defined by U.S. Energy Information Administration (EIA). The average Source Energy Use Intensity (EUI) and Site EUI are calculated in kBtu/sft as weighted averages across all commercial buildings of a given type in 2003 CBECS data set (The Commercial Buildings Energy Consumption Survey 2009). CBECS data even produces the average EUI per building. Average values are computed by calculating EUI for individual building first. Mean EUI for each category is then computed by applying the CBECS survey sample weights. This method gives an average EUI per building rather than average EUI per square foot (The Commercial Buildings Energy Consumption Survey 2009). 1.4.2. Architecture 2030 Challenge Buildings in today’s world are the major source of global demand for energy and materials which in turn produces greenhouse gases (GHG) as their by-product. The challenge today is to slow down the growth rate of GHG in order to address climate change and keeping global average temperature within reasonable limits (The 2030 Challenge 2010). In order to accomplish this, Architecture 2030 issued The 2030 Challenge asking the global architecture and building community to adopt certain targets in order to be ‘carbon neutral’ by 2030. A carbon-neutral building is a building that uses no fossil fuel, nor any greenhouse-gas-emitting energy to operate. It should not be confused by ‘Net Zero Energy’ building which must produce as much energy on site as it consumes (The 2030 Challenge 2010). 9 The challenge is to reduce the fossil fuel for all new buildings and major renovations to a percentage below the regional (or country) average for that building type. The percentages are as follows: 70% by 2015, 80% by 2020, 90% by 2025 and carbon-neutral by 2030 (The 2030 Challenge 2010). These targets may be accomplished by implementing innovative sustainable design strategies, generating on-site renewable power and/or purchasing (20% maximum) renewable energy (The 2030 Challenge 2010). A baseline was to be defined for these target goals. American Institute of Architects (AIA), the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), Architecture 2030, the Illuminating Engineering Society of North America (IESNA), and the U.S. Green Building Council (USGBC) and U.S. Department of Energy collectively agreed their common target goals as the national average energy consumption of existing U.S. commercial buildings as reported by the 2003 Commercial Building Energy Consumption Survey (CBECS) (The 2030 Challenge 2010). In other words, the percentile reductions for Architecture 2030 challenge is based on 2003 CBECS survey (The 2030 Challenge 2010). 1.4.3. California Commercial End-Use Survey (CEUS) The California Commercial End-Use Survey is a comprehensive study of commercial sector energy use. This survey is done for twelve common commercial building type categories. This survey comprises of end-uses of all these commercial building types. It is primarily designed to support the state's energy demand forecasting activities (California Commercial End-Use Survey 2008). 10 A stratified random sample was collected from the service areas of Pacific Gas and Electric, San Diego Gas & Electric, Southern California Edison, Southern California Gas Company, and the Sacramento Municipal Utility District. The sample was stratified by utility service area, climate region, building type, and energy consumption level (California Commercial End-Use Survey 2008). For each utility service area, fuel shares, floor stocks, electric and natural gas consumption, energy-use indices (EUIs), and 16-day hourly end-use load profiles were estimated for twelve common commercial building type categories (California Commercial End-Use Survey 2008). 1.4.4. International Performance Measurement & Verification Protocol (IPMVP) The International Performance Measurement and Verification Protocol (MVP) is a protocol that gives an overview of current best practice techniques available in order to verify the results of energy efficiency, water efficiency and renewable energy projects (IPMVP 2002). This is essential for facility operators in order to assess and improve facility performance. There are numerous energy conservation measures (ECMs) that are discussed in this protocol such as fuel saving measures, water efficiency measures, load shifting and energy reductions through installation or retrofit of equipment or modification of operating procedures (IPMVP 2002). 11 There are four M&V options mentioned in IPMVP that can be followed.  Partially Measured Retrofit Isolation “Savings are determined by partial field measurement of the energy use of the system(s) to which an ECM was applied; separate from the energy use of the rest of the facility. Measurements may be either short-term or continuous.” (IPMVP 2002)  Retrofit Isolation “Savings are determined by field measurement of the energy use of the systems to which the ECM was applied; separate from the energy use of the rest of the facility. Short-term or continuous measurements are taken throughout the post-retrofit period.” (IPMVP 2002)  Whole Facility “Savings are determined by measuring energy use at the whole facility level. Short-term or continuous measurements are taken throughout the post-retrofit period.” (IPMVP 2002)  Calibrated Simulation “Savings are determined through simulation of the energy use of components or the whole facility. Simulation routines must be demonstrated to adequately model actual energy performance measured in the facility. This option usually requires considerable skill in calibrated simulation.” (IPMVP 2002) 1.4.5. FEMP “The Department of Energy (DOE) Federal Energy Management Program (FEMP) facilitates the Federal Government's implementation of sound, cost-effective energy 12 management and investment practices to enhance the nation's energy security and environmental stewardship” (FEMP 2012). This gives us the M&V guidelines to calibrate the model. 1.5. Whole Building Energy Analysis 1.5.1. Role: Current Market Building energy simulation has played a very important role not only in building design, but also in the operation, diagnostics, evaluation and commissioning of buildings in the last two decades(Pan, Huang & Wu 2007). Whole Building Energy Analysis aid designers to compare various design options and make a realistic and effective choice. This in turn help them make more optimal and energy saving designs(Pan, Huang & Wu 2007). This even lead them to define various energy saving potentials and evaluate the energy saving effects of ECMs (energy conservation measures). There are many building energy simulation softwares available in the market nowadays to carry out this task. Energy simulation softwares that are widely used based on two simulation engines, namely DOE-2 and Energy Plus. Other softwares like TRNSSYS, IES are also used in the industry and have their own simulation engines. DOE-2 has dominated this industry for decades and is a widely used and accepted freeware building energy analysis program that can predict the energy use and cost for all types of buildings. This engine uses the description of the building layout, constructions, operating schedules, conditioning systems (lighting, HVAC, etc.) and utility rates provided by the user, along with weather data, to perform an hourly simulation of the building and to estimate utility bills (DOE-2 1998). 13 Energy Plus is the new generation of simulation engine present in the market. It has numerous advantages over DOE-2 and is suited to analyze building performances with non-normal building systems. Energy Plus like DOE-2 is also an hourly energy simulation engine and is based upon simultaneous load/system/plant simulation methodology (Pan, Zuo & Wu 2009). Conduction Transfer Functions (CTF) method is used in load calculations to calculate heat conduction through envelopes and then a heat balance method for zone load (Pan, Zuo & Wu 2009). No matter which software is used, the calibration of the simulation model is necessary and important for the accuracy and usability of energy simulation. The calibration process compares the results of the simulation with measured data and tunes the simulation until its results closely match the measured data. 1.5.2. Measurement: Energy Use Intensity Energy Use Intensity (EUI) is a unit of measurement that gives a common platform to compare various buildings. EUI measures the building’s energy use which is the energy consumed by the building relative to the size of the building. In order to calculate a building’s EUI, total energy consumed in one year (in kBtu) is divided by the total floor space of the building. In this unit of measurement, low EUI indicates good performance (Energy Star 2011). 1.6. Calibration Simulation Approach In order to achieve a Net Zero Energy building, one of the most elementary things to do is to calibrate the energy model to the actual building performance. It is only then that various Energy Conservation Measures (ECMs) can be devised on the model to estimate the energy reduction in the actual building. 14 1.6.1. Description of Calibration Process Calibrated simulation is an appropriate method to measure and determine energy and demand savings of ECMs and achieve Net Zero Energy Buildings. Calibrated simulation approach is defined in three standards or guidelines – ASHRAE Guideline 14-2002: Measure of energy and demand savings (ASHRAE Standards Committee, 2002), M&V Guidelines: Measurement and verification of federal energy projects (FEMP) (U.S. DOE, 2000), IPMVP (International Performance Measurement and Verification Protocol) (IPMVP, 2002). 1.6.2. Simulation Steps The calibrated simulation approach has the following steps: 1.6.2.1. Produce a Calibrated Simulation Plan The baseline scenario and post-retrofit scenario have to be specified, the simulation software has to be selected, and the tolerances of calibration indices have to be checked. (Pan, Huang & Wu 2007) 1.6.2.2. Collect data Various data are to be collected in order to start calibration process. The data includes building plans including geometry and construction materials, a minimum of 12 months historical utility data (preferably hourly data), information on lighting systems, plug loads, HVAC systems, building envelope and thermal mass, building occupants, other major energy-using loads and weather data for a typical year. The generic weather data available on energy plus or doe-2 website doesn’t work for calibration purposes. The hourly weather data must be obtained from the nearby weather station in order to make the simulation model replicate the actual behavior of the building for that year. On-site 15 surveys, spot and short-term measurements, interviews etc. might be considered for the collection purposes. (Pan, Huang & Wu 2007) 1.6.2.3. Input data and run model (Pan, Huang & Wu 2007) The collected data must be inputted correctly in the simulation model. Some of the list of inputs/outputs that should be checked by the simulator to minimize the simulation error is as follows: a) Building orientation b) HVAC system zoning c) External surface characteristics d) Lighting and plug load power densities and operating schedules e) HVAC system characteristics and operating schedules f) Plant equipment characteristics 1.6.2.4. Calibration of Simulation Model (Pan, Huang & Wu 2007) One of the following three approaches must be selected for calibration: a) Comparing model monthly usage predictions to monthly utility bill data. b) Comparing model monthly usage predictions to monthly utility bill data in combination with comparing model sub-system usage predictions to measured hourly data. c) Comparing model hourly usage predictions to hourly utility bill data. 16 1.6.2.5. Refine model (Pan, Huang & Wu 2007) If the statistical indices calculated during the previous step indicate that the model is not sufficiently calibrated, revise the model inputs, run the model, and compare its prediction to the measured data again. 1.6.3. Model Calibration Criteria A criterion for acceptable tolerances has been set by different guidelines in order to access the simulated model to be calibrated. (Pan, Huang & Wu 2007) Table 2: Acceptable tolerance for monthly data calibration INDEX ASHRAE 14 IPMVP FEMP ERRmonth ±5 % ±20 % ±15 % ERRyear ±10 % CV(RMSEmonth) ±15 % ±5 % ±10 % * ERR: Mean bias error * CV(RMSE): Coefficient of Variation of the root mean squared error The combination of ERR and CV(RMSE) can determine how well the model predicts whole-building energy usage. The lower the ERR and CV (RMSE), the better the calibration (IPMVP 2002) . 1.7. Simulation Software There are numerous simulation softwares available in the market. Every software has its own merits and demerits. A lot of them were experimented. 1.7.1. HEED One of the simulation software present in market is HEED. This software is extremely 17 user friendly and is very good for early stage energy modeling and quick results. It has good graphical outputs and provides a platform for quick comparisons. It can even model landscape around the buildings and takes it into account. However, it is not good with modeling complex geometries. The most depressing part of this software is that we can’t export the data in excel or any other file format. It doesn’t give any numeric output but only display graphs. This software is not good for calibration purpose as we need the data in detailed format. 1.7.2. BEopt It is tool that gives extremely informative and detailed output graphs. It is easy to do in- depth analysis in this software. However, the data entry is cumbersome especially while defining the properties of certain materials and model parameters. 1.7.3. eQuest It is one of the most widely used softwares in the industry. It has a great interface in the form of wizards and the detailed mode. It is really good for both early stage design analysis and post evaluation. Its drawing interface is not very user friendly. It can easily model rectangular shapes but fails miserably in curved surfaces and multiple curved surfaces. It has great interface to accommodate HVAC systems. The best part of eQuest is the parametric analysis tool which allows us to compare the results on separate or cumulative steps. This gives us a platform to compare the effect of changes we make in the model. The simulation run time is short. It simulates the model in a matter of minutes. The engine used is DOE-2 to run the simulation. One of the problems with this software is that the DHW systems can’t be model as much in depth as other HVAC systems. The in depth analysis of eQuest capabilities are mentioned in one of the papers 18 submitted by the author for SimBuild 2012 “Comparison of two different simulation softwares while calibrating the same building”. 1.7.4. Energy Pro This is an excellent tool if we need to do the compliance for a residential or a non- residential building. Although it is primarily used for Title-24 compliance, it is not limited to doing just that. It can generate reports for Green Point Rated, CHEERS Home Rating, ASHRAE 90.1 Performance. There are not a lot of flexibilities that are provided with respect to the HVAC equipment. 1.7.5. Ecotect Ecotect is an extremely useful tool. It has great graphical output capabilities. It is an excellent tool if coupled with Radiance or Daysim for the day-lighting purposes. It has the capabilities for doing solar gain analysis, acoustic analysis, comfort analysis and thermal analysis as well. However, it is not a very accurate thermal tool. 1.7.6. Vasari This is very promising software that Autodesk has recently released. The BIM (Building Information Modeling) model can directly be run in Vasari to produce extremely useful graphical outputs. The simulation time is quick and even takes into account the CFD (Computational Fluid Dynamics). However, the results are not as very promising yet. This is a great tool for the future. 1.7.7. Open Studio Open Studio can be used by coupling with Sketch-Up. It is extremely useful in early design stages. Sketch Up is renowned in this field of early design and acts as an interface to Open Studio. However, even if this software is a great tool but currently has a lot of 19 bugs. This is constantly getting updated with new features and bug fixes. Nonetheless, this is a great tool in the coming days. 1.7.8. Design Builder This is an extremely robust software which runs on the Energy Plus Engine. It has a nice interface that allows users to adapt quickly. This is apt software for high performance building design, simulation and visualization. The data can be easily extracted out of it in excel format. Highly detailed HVAC systems can now be modeled in the Version 3. It has great graphical outputs on various scales Annual, monthly, daily, hourly and sub hourly. CFD analysis can also be performed in this tool. 1.7.9. IES-VE-Pro This is robust software which is a complete Whole Building Analysis Tool. This is capable of doing thermal analysis, CFD and day lighting. However, it runs on its own engine ‘Apache’ and not Energy Plus. Highly detailed HVAC systems can be modeled in this software. Detailed output can easily be exported to excel and related formats. This even has a plug in for Sketch Up and Revit. Even though it has a lot of constraints, but is still very helpful as the model can directly be analyzed using the plug in. 1.7.10. AECOsim Energy Simulator This software has been developed by Bentley which provides a platform for interdisciplinary building design, analysis and simulation. This has been recently launched but is already very robust in nature. It automatically gives an option of creating standard ASHRAE 90.1 baseline and compares it to the building in question. The calculation formulas are explicitly shown. All calculations can be easily traced back and understood as to how the software is calculating all the results. 20 CHAPTER - 2: CASE STUDY - VON KLEINSMID CENTRE This chapter briefly talks about why Von Kleinsmid Centre was chosen as the case study building. Site context and background information collected about VKC from different sources is then discussed. 21 2.1. Why this building There was enormous amount of background research done before choosing VKC as the case study building. The process began with deciding not to want to put hobos in the building to measure data and analyzing it. One year of thesis is a very short span to accurately document and then analyze a building. The main intention was to use the BMS system to get the data and focus on important aspect of thesis instead of juggling around with fetching the data. Choosing a building within the University of Southern California (USC) campus was the next the logical step, keeping in mind the minimal connections in the outside world being an international student who just came to U.S. A thorough research was done for buildings that exist in all three campuses of USC. A number of meetings were held with the USC Sustainability Group in order to gain an insight on the data that can be procured for USC buildings. This group even directed to ‘USC Facilities Management’ website that had the log of all the buildings that they monitor (http://fmsmaps.usc.edu/mapguide6/ upcmaps /Web/cfm/bl_list_no.cfm). This was an excellent source that gave me an opportunity to get the basic information about each USC building with graphical photographs in one single place. A selection criterion was then made to pick a building out of those available on the provided website. The first criterion being that the building should be slightly envelope dominated which would allow me to play with more variables and make the process more interesting. A second judging criterion was the availability of information for that type of building. 22 A list of 20 favorite buildings was made that suited the first criteria. A meeting was scheduled to meet with USC Facilities Management Services (FMS) Department to discuss the second criteria. After a lot of discussions and explanations of my final goal with this study, selection was narrowed down to two options that suited both the criteria. First choice was the ‘Eli And Edy Broad Center For Regenerative Medicine’ and second choice being ‘Health Care Consultation Centre. Required plans for both buildings were taken from FMS and site visits were conducted in order to choose one of the two buildings. Both the buildings were in USC Health Sciences Campus. A lot of restrictions were felt in both buildings as main functions of buildings were predominantly labs. The second thing that was realized was the fact that even if the buildings have a lot of glazing all throughout the building, the primary driving force is the internal HVAC system which plays a very dominant role in Lab Buildings. Both of these buildings even if met both the selection criterions were very much internally dominated because of the kind of function it hosts. It was finally decided to be flexible with the first criteria but in addition added that the third criteria that the building shouldn’t be a lab building. A new list of buildings was made and another round of discussion with Carol Fern, Director of Energy Services at USC Facilities Management Services was fixed. This time we finally narrowed down to two buildings. First being Von KleinSmid Centre and second Taper Hall of Humanities. Both were in USC main campus and met all the three criterions. Both buildings had same amount of control over the building and amount of data availability was also similar. Finally, Von Kleinsmi d Centre was decided to be the case study building based on the two decisions. First, VKC had its own Chiller and not on USC district loop. This meant 23 that a sub metered data of chiller which is a main component of electricity consumption is available. Second being the layout of VKC which was a U-Shape interesting building. 2.2. Site Location VKC is located at the heart of USC with a tall tower upholding a globe. This building acts as an icon for USC and is a very prominent building. Figure 2: Site Location of VKC It is located on Trousdale Pkwy which is the main pedestrian boulevard in USC. 2.3. Climate Analysis The building is located in Los Angeles. However, in case of calibration we cannot use generalized data for Los Angeles Airport weather station. We need to have site specific data for the year the calibration is done. The weather data was acquired from ‘Weather Analytics’ which provides the data based on the exact building location. The climate was then studied using ‘Climate Consultant’. 24 2.3.1. Temperature Range Figure 3: Temperature Range Graph The temperature range graph shows that September was the hottest month in 2010 with high diurnal variations. The November month had maximum diurnal variation. 2.3.2. Wind Analysis Figure 4: Wind Analysis 25 The winds are primarily east west oriented with significant amount from south side as well. However, the speeds of winds are quite high from E, SE, S, SW & W. The temperature of winds are primarily between 32-75F. 2.3.3. Psychometric Chart Figure 5: Psychometric Chart As per the psychometric chart, only 11.7% of hours fell within comfortable zone belt in 2010. Major factors that impact the building in this type of weather conditions are sun shading, internal heat gain and passive solar direct gain High Mass. 2.3.4. Other Related Data The ASHRAE design data (98%, 99% & 99.6%) based on dry and wet bulb temperatures used by Design Builder to perform load calculations is shown below. This data is not fetched from the weather file but from the setting of preset location. If the location is not preset, the ASHRAE design data values can be taken from ASHRAE Handbook 2005. However, it has been verified that the preset design day values in Design Builder matches exactly to the ASHRAE handbook values for Los Angeles. 26 Figure 6: ASHRAE Design Day Values 2.4. Description of VKC The Von Kleinsmid Centre at the University of Southern California in Los Angeles, California was built in 1966. It is a three story brick structure with a prominent brick tower which has a tilted globe on the top. It primarily contains third floor offices and first and second floor classrooms. The basement comprises of library. The overall area of the building is 95,287 sft. 27 Figure 7: VKC Building Figure 8: Revit Model of VKC Building Table 3 General Description of the building Elements Description Building Era 1966 Location University Park Campus, USC Building Area 95,287 sft Architecture Shape Primarily U-shaped building with an open courtyard at the centre. L.P.D. Varies with space type E.P.D. Varies with space type Foundations The foundations are spread and poured concrete Basement Construction The basement is poured concrete. Super Structure The superstructure is mainly reinforced concrete and steel. Exterior Enclosure The exterior is predominantly brick construction Roofing Aggregate covered built up roof Interior Construction The interior comprises of offices, classrooms and library. Stairs Interior stairs are reinforced cast concrete Interior finishes The interior floor finishes are primarily vinyl flooring on classroom levels and in the library. Office areas are carpeted. Ceilings are a combination of acoustical tile and textured sheetrock. Conveying One 3,000 pound hydraulic, single entry 4-stop elevator serves the basement through third floors of building. 28 2.4.1. Site The ground around the VKC building are adequately landscaped and maintained with planting beds, mature trees and shrubbery. The site has a central amphitheater on the lower level surrounded by glass and overlooked by the library on the lower level. There is no dedicated parking directly associated with this structure. There is plaza and some sitting places. Figure 9: Central Amphitheater (basement) Figure 10: Plant Beds around the building 2.4.2. Building Plans The building plans were obtained from Facilities Management Services, USC. There are in total three floors above ground and one sub-surface. Figure 11: VKC Basement Floor Plan Figure 12: VKC First Floor Plan 29 Figure 13: VKC Second Floor Plan Figure 14: VKC Third Floor Plan 2.4.3. Exterior Structure The façade of the building is primarily brick and glass as like other buildings on USC campus. Overall, the building has high mass. The aggregate covered built-up roof over the third floor was reportedly installed in the mid-1990. The fixed exterior glazing is still intact the way it was installed in 1960’s. Figure 15: Exterior of VKC Figure 16: Exterior of VKC 2.4.4. Interior Finishes and Systems Plain painted wall and ceilings. All rooms have acoustical ceiling grids. The interior personal doors are generally old. There are 12 x 12 vinyl tile on first and second floors and 9 x9 vinyl tiles on stair landings and library in the lower level. Office on the third has carpeted floor. Restrooms also have ceramic tile finish. 30 Figure 17: Internal Finish Figure 18: Internal Finish - Typical Classroom 2.4.5. HVAC Four primary air handlers and some dedicated secondary air systems heat, cool and ventilate the building mechanically. Infrastructure steam is fed to one primary heat exchanger to generate heating hot water. Hot water is circulated to air handler coils for preheat and primary heat. Hot water is also circulated to reheat terminals. Chilled water is produced by two R22 Trane screw chiller with associated cooling towers. The cooling towers are not on the roof of VKC but rather on the roof of Waite Phillips Hall (adjacent building). Chilled water circulated within the air handler cooling coils, dehumidifies and cools air during the cooling season. The control system is primarily Pneumatic. These have direct digital controls (DDC) logic control temperature and ventilation. There are four roof-mounted exhaust fans that serve local restroom and other ventilation needs for VKC. One electric compressor (with integral air drier) supplies clean compressed air for the HVAC controls. Electrically driven, base-mounted, and in-line constant volume circulation pumps maintain pressures within the steel hydronic media 31 distribution piping network that has fiberglass and foam insulation (Courtesy Facilities Management Services, USC, 2011). The Building Management System (BMS) is Honey Well system. Some snapshots of that system is as follows: Figure 19: Air Handling Unit- 1, Courtesy of USC Facilities Management, 2011 Figure 20: Air Handling Unit- 1 Amps, Courtesy of USC Facilities Management, 2011 32 Figure 21: Air Handling Unit- 3, Courtesy of USC Facilities Management, 2011 Figure 22: Air Handling Unit- 4, Courtesy of USC Facilities Management, 2011 Over time the use of the original constant volume dual duct HVAC design has been migrated to a variable volume design. The original constant volume duct and air control dampers remain in service and are not optimal for currently modified VAV design. 33 The HVAC pumps were last replaced in mid 1990’s. The same is true of the heat exchanger and condensate handling equipment. Thermal media piping systems are mostly original. Exhaust fans are mid-1900’s installations (Courtesy Facilities Management Services, USC, 2011). Specification of the two chillers that are located in the east mechanical rooms is “Trane’s Centravac Rotary Liquid Chiller Model RTHA-180 (long shell), 160 tons cooling capacity, 3 pass evap, 55⁰F EWT & 45⁰F LWT, 384 GPM W/ 9.0 Ft HD, 2 Pass Condenser, 85⁰F ECWT & 95⁰F LCWT, 462 GPM w/ 8.0ft head, 114 KW motor, 162 amps. RLA Unit Mounted starter, 460 V – 3 PH – 60Hz. Refrigerant Charge (R-22) @ 605 lbs.” (Courtesy Facilities Management Services, USC, 2011). Figure 23: Chiller & Cooling Tower Layout, Courtesy of USC Facilities Management, 2011 Chilled water pumps installed are Bell & Gossett model no. 3E (series 1510), 384 GPM @ 100 ft head, 15 Hp(1750 rpm) ODP Motor, 400 V, 60 Hz, Eff @ 76.5%. 34 Condenser water pumps that connects chiller to cooling towers are Bell & Gossett model no. 3G (series 1510), 462 GPM @ 130 ft head, 25 Hp(1750 rpm) ODP Motor, 460 V, 60 Hz, Eff @ 74% (Courtesy Facilities Management Services, USC, 2011). Total CFM supplied by AC 1 is 7940 cfm as opposed to specified 7815 cfm. The motor is 20HP, 230V, 3 phase, 1750 rpm. The fan’s rpm is 1139. Total CFM supplied by AC-3 is 2865 cfm as opposed to specified 2960 cfm. The motor is 7.5 H.P., 230V, 3 phase, 1190 rpm. The rpm of fan is 1170. Total CFM supplied by AC-4 is 8040 cfm as opposed to specified 8485 cfm. The motor is 20 H.P, 230 V, 3 Phase, 1750 rpm. The fan’s rpm is 1064 rpm (Air Balance Report 1999) The AC-2 which serves full lower floor library supplies 26,200 cfm with a 25 HP, 3phase, 480V, 32 amp, 60 Hz VFD with an RPM of 1725 (Air Balance Report 1999). 2.4.6. Electrical 5kV electrical power enters the building through a three-pole oil switch that energizes one 480 volt fluid-filled pad transformer and one 208 volt, fluid-filled service transformer mounted as part of a central 208 volt substation. The contemporary and serviceable 480 volt substation powers the substation. Interior spaces are illuminated by energy-retrofitted fluorescent fixtures. These fixture have opaque lenses which distributes the lights uniformly. 35 Figure 24: Lighting system inside library Figure 25: Lighting system inside library Exterior lighting consists of high intensity discharge (HID) fixtures that are mounted beneath the overhangs at feature elevations, along with two spot-lighting clusters illuminating the tower. No automated control is available on these. Figure 26: HID Fixtures Figure 27: HID Fixtures Emergency power is supplied by a 1kW inverter system with wet cell batteries. Individual safety lighting like egress fixtures and exit signage have individual battery power storage. 36 2.4.7. Plumbing Infrastructure potable and fire water services supply domestic and fire suppression water supply networks. The building is not supplied with natural gas. Supply and drain piping are mostly concealed in structural chases and openings and cannot be readily observed. Supply piping is a combination of hard drawn copper and galvanized steel construction. Drain pipe is primarily cast-iron and is never replaced since the original construction of building in 1960’s. Domestic hot water is generated by a tube-in-tank style steam-powered hot water generator. This is a new system that was put in 1996. Plumbing base fixtures are mostly wall-hung design constructed of porcelain china or porcelain coated iron. Two groundwater removal sump pump systems are placed each in two mechanical rooms in the basement. One centralized duplex sewage ejector system is installed in the west mechanical room. 2.4.8. Thermostat & Other Controls in VKC First and Second floor which primarily consists of classrooms have individual thermostats and control mechanism. These thermostats are controlled remotely from Facility Management Services, USC. Some of the controls have been given to users who can vary the temperature set point up to 2°F. However, currently these controls are embedded under a case and not accessible to general public unless they know how to work around it. The room temperatures can be monitored offsite using Honeywell controls as shown in the snapshots below and adjusted as per need. The snapshots clearly show that FMS has a lot of control on the first two floors with thermostat in each room. 37 Figure 28: First Floor Plan showing the control possibilities Figure 29: Second Floor Plan showing the control possibilities 38 However, on the third floor which primarily consists of office spaces, control is limited. A lot of office spaces are collectively controlled by a single Thermostat instead of one thermostat per office. Figure 30: Third Floor Plan showing the control possibilities 2.4.9. Vertical Transportation There is 3000 pound hydraulic elevator located in the south tower that stops on the basement through third floor levels. 2.5. Occupancy & Schedules 2.5.1. VKC library The VKC library hours are similar for Fall & Spring. They vary in summer. During Fall & Spring, the library is open from 9am till 10pm on Monday through Thursday. The timings change to 9am till 5pm for Friday and Saturday. On Sunday it is open from noon 39 till 8pm. However, during summer time the library is open from 9am till 5pm from Monday through Friday and is closed on Saturday and Sunday. 2.5.2. Classrooms Classrooms are divided into new class rooms and old classrooms. The new classrooms are strictly opened when there is a class scheduled otherwise they are locked remotely. However, old classrooms are available for studies by students after regular class hours. Students study in these classrooms in small groups or individually till late in the night. During class hours, some classes use the AV equipment while others don’t. The schedule for that is fairly complicated and hard to track records for 2010. 2.5.3. Offices These are normally used during regular office hours. The schedules of these are easy to track. 2.5.4. HVAC AHU 1,3 and 4 which includes the chiller are in operation from 7am till 10pm Monday through Friday. On Saturday they are turned on from 7am till 6pm and on Sunday from 7am till 5pm. AHU 2 is operational from 8am till 5pm and is off on weekends. 2.6. Utility Data The Utility data was derived from FMS USC. This is easier said than done. It takes countless meetings and signing of confidential forms to get access to this data. Even with access to the data, it is normally thought that the more data available the better it is. However, no one brings up a point as to what exactly is ‘more’. Managing and extracting 40 useful data out of the expanse of data that BMS provides is a great challenge and very time consuming. It slows down the overall progress considerably. The electrical data that was received from BMS system was in a sub-hourly format. It was the most detailed data that could have been derived from this system. However, electrical consumption of each day in a sub-hourly format was in a separate excel file. It was as if managing 365 files was easy, each day in excel file had the sub-hourly data for all 164 buildings that FMS was monitoring. If the information for VKC was to be read, one had do go to the building number of VKC and then see the electrical consumption of that particular day. It was cumbersome and time intensive to manage such loads of data. The first logical attempt was to combine all the excel files and then use a filter in order to extract the information for only the required building. It was done using a code in CMD which enable combining of all the excel files to one single file. However, upon a closer examination it was realized that Microsoft Excel could only merge the first 89 days (till March) out of 365. With only 89 files it reached the maximum limit (over million) of rows in a single excel spreadsheet. This attempt ended up as a failure. This matter had to resort to experts in excel who developed a macro which could extract the electrical consumption of VKC from each of 365 spreadsheets and make a single spreadsheet. This approach finally worked. However, it was a challenge to extract the desired data out of the full set. Chiller consumption of VKC was also acquired from FMS. This data was easier to manage as an Excel spreadsheet only had the electricity consumption of VKC chillers in an hourly format. However, one thing that was overlooked was the fact that the data set 41 was incomplete in itself. Data was unavailable for October and November of 2010. This was due to the upgrade issue in BMS system during those months. The gas consumption sought from the FMS system took some time for them to gather. Once gas consumption graph was plotted to see the trend, an anomaly was found in the data. The gas consumption in February 2010 was drastically less as compared to January or March. Figure 31: Metered Gas Consumption of VKC The weather conditions were checked for that time to understand if that had an impact. That was not looking the case. A doubt was casted in the mind over the authenticity of data and its source. The doubts were expressed to the FMS department. It was then realized that this is the data with lowest confidence level relative to all the data of VKC that was received from FMS. First of all, there is no gas consumption as there is no gas that is supplied to this building. It is district steam that is send to this building, which by using steam exchanger 42 is converted to hot water. This hot water is then re-circulated to reheating coils and other purposes. There is a common meter that measures the amount of steam supplied to 3 buildings adjacent to each other. There is no active measuring of gas consumption in Therms at VKC. It is allocated from the total usage from the WPH boiler plant in the next building based on a model that was developed several years ago. A model that was developed some years back is still being followed and the gas consumption in Therms is estimated for each building inclusive of VKC. In other words there is no direct meter at VKC to measure the amount of steam and predict the gas usage. It was even decided that natural gas should be the least of my concern, since it is relatively small due to the small loads for the building. Given that it is also based on a model and not actually measured, it provides a relative profile good profile. However, it won’t be stressed hard to match exactly to the DB simulation model results. Approximate profile should be called a calibrated natural gas model. 43 CHAPTER - 3: VKC ANALYSIS The gathered data for VKC was analyzed to understand the site context and building better. Solar shade analysis, VKC benchmarking, on-site measurement were certain measures followed that are discussed in this chapter. In addition the ZNE target for VKC is discussed along with some site visit notes. 44 3.1. Immediate Site Context VKC is quite independent from the impact of surrounding buildings. It has two large open green spaces on both of its SW and SE sides. There is a high rise building on its north side which is inconsequential in terms of shading this building. Figure 32: Immediate surroundings of VKC (in yellow) The only building that might impact VKC is the Doheny Library which is on the south corner of the building. A detailed shadow impact study is done to understand the impact of that building on VKC. Other than that there are only trees in the vicinity of the building that might filter the solar radiation penetrating into the building. 45 3.2. Solar Shade Analysis Solar shade analysis was done to see much the surrounding buildings impact VKC. Figure 33: Solar Shade Analysis on 15th March Figure 34: Solar Shade Analysis on 15th June Figure 35: Solar Shade Analysis on 15th September Figure 36: Solar Shade Analysis on 15th Dec The study was done on 4 months spaced equally from each other namely March, June, September and December. Each graph shows the shadow pattern of buildings throughout that day. With this we can judge the overall shadow pattern and understand the effect on VKC (in red). 46 These graphs clearly illustrate that adjacent buildings have has no effect on VKC (in red) throughout the year. The two buildings in the north and on in south side of VKC have their own shading cycle which never shades VKC. However, this building shades its own parts due to U-Shaped building profile and deep overhangs. 3.3. EUI & Comparison to Benchmarks Figure 37: Energy Benchmarking: Energy Use Intensity (EUI) Comparison The building under consideration Von Kleinsmid Centre (VKC) is compared against various industry benchmarks to understand its current standing in comparison to them. According to CBECS ‘Commercial Buildings Energy Consumption 2003 Survey’ average EUI per building type is 120 kBtu/sft for Education – University category. California Commercial End Use Survey which is based on all addition of all end uses per category indicates that the EUI for ‘colleges’ category should be 74.50. However, one must keep in mind that these are very liberal and almost outdated goals. These just guide us to bare minimum that a building should not exceed. The era is moving towards more energy 47 efficient buildings. One of the parameter that gauges today’s performance is Architecture 2030 Challenge. The Architecture 2030 goal advocates for “carbon-neutral” buildings in 2030. It has based its baseline for the common targets goals as the national average energy consumption of existing U.S. commercial buildings as reported by the 2003 Commercial Building Energy Consumption Survey (CBECS) using kBtu/sq. ft.-yr as the metric. Energy Use Intensity of VKC Building is gauged against this standard. Currently VKC consumes 78.5 kBtu/sft. 60% of annual consumption is contributed by Electrical Consumption whereas rest 40% is contributed by Gas Consumption. In order to be at par with the Architecture 2030 (2015 Goal) which aims at 70% reduction from CBECS, VKC should be performing at 36 kBtu/sft which is 46% less than what it is currently consuming. This clearly shows that a lot of aggressive measures are required to achieve this goal. 3.4. ZNE Target Once the benchmark comparison is done, the next step is to set the Zero Net Energy target. This is a very important step as this will tell us how aggressive we need to get to achieve the ZNE target. There are several definitions of ZNE as discussed in chapter-1. Once the definition is finalized, the first step is to make VKC as energy efficient as possible and then offset the energy demand by On-Site generation. However, to set the target it is essential to get a rough estimate of On-Site energy generation potential. 3.4.1. Choosing the definition The Zero Net Energy definition that was chosen to move forward was based on ‘Site Energy’. This definition is mostly followed by the industry. This option is one of the most 48 rigorous options and need a lot of aggressive measures and more site generation. This means that it is necessary to offset all the energy consumed at Site Level. It is therefore best to minimize the energy usage as much as possible. Then offset the energy using renewable sources. 3.4.2. On Site Generation Potential The On-Site Generation Potential would give a minimum target is needed to be met in order to reach ZNE goal. The less on-site generation potential is used, better it is. This would mean smaller renewable plant size and lesser payback period. There is no mechanical equipment on the VKC roof which gives us full roof for generating renewable power through Solar PV. All AHU’s are located in basement and cooling tower is shared with Waite Phillips Hall (WPH) which is the adjacent tall building. Cooling Tower is located on the top of WPH. Now, in order to assess On-Site potential for VKC, PV panel layout was made on the VKC roof using racks arrangement. A typical PV panel of 5’ x 3’ size was considered for the layout. Four of such panels could be placed on a single rack (like Silver back Solar). These panels could be installed in either horizontal or vertical position depending upon the availability of space. The minimum distance was kept to be at least 5’ between two rows of racks so that the racks don’t shade each other. The only thing that was kept in mind was the same orientation for all the panels with same tilt. This is necessary for all of them to be working at their maximum potential. All the racks were placed at least 10 feet from the edge of the roof and the staircase. 49 Figure 38: VKC Roof plan showing the layout of PV Panels A total of 367 racks could be placed on the roof each having 4 PV panels. Therefore, the power generating PV panels count goes to 1468. Assuming each panels generate average 305 W, the DC rating of the system becomes 1468 x 305 = 447. 74KW. (DC rating = No. of Panels x KW per panel) 50 Figure 39: Inputs for PV Watts 51 Figure 40: Output (predicted generation) of PV Watts 52 3.4.3. Setting the target Having calculated the maximum site potential, the next step was to set the ZNE target. This was important in order to gauge the reduction required in the current energy consumption to achieve ZNE target. Figure 41: ZNE Target (Based on Consumption) A minimum of 72% energy reduction is required in order to achieve Net Zero Energy goal. In terms of EUI, minimum of 55.85 kBtu/sft of reduction is required. Figure 42: ZNE target (Based on Energy Use Intensity) 53 3.5. On-Site Measurement There were various investigation tools that were taken on loan from Southern California Edison’s Tool Lending Library and from the library of Prof. Marc Schiler. These tools greatly helped with measuring plug loads, solar heat gain co-efficient, visible transmittance and with some detective work inside the building. The tools that were used are as follows: Figure 43: FLIR Thermal Camera Figure 44: Light Transmitter Figure 45: Kill-A-Watt Strip Figure 46: Power Quality Logger Figure 47: SHGC Calculator 54 3.5.1. R-Value Estimation The R-Value of the walls/floors/roofs was calculated manually using the thermal properties of building & insulating materials, values of which were taken from Appendix E of the book ‘Mechanical and Electrical Equipment for Building’. Figure 48: Manual R-Value Calculations Figure 49: Manual R-Value Calculations This was required to verify the values produced by the simulation software when we specify the same materials of walls/floors/roofs construction. 3.5.2. Plug Load Estimation Plug load estimation is an important criteria especially if the building is dominated by newly renovated classrooms. 3.5.2.1. Basic Equipment in Classrooms. The classrooms in VKC are quite technically sound and have latest and most up to date technology built in. The only visible equipments are a projector at the ceiling and a wall box in a corner of a room. 55 Figure 50: ITS Manager Figure 51: Wall Box The wall box is so designed that it is hung from the wall and takes minimal space on the ground. All the classroom functions are embedded in it starting from DVD player, sound controls, light controls to AV camera control. The wall box is mainly run through ‘System-5’ which is a major component of the system. Lorenzo Bernardi, a manager at ITS Learning Environments gave the permission to have a look and take photographs of the system. He opened the wall box in order to show me the full system inside it. 3.5.2.2. Calculating Power Consumption by these equipments. Another set of permission was required in order to use my borrowed tools from SCE to measure the power consumption of these systems. Once that was taken, ‘P4320 Kill-A- Watt’ & ‘Fluke Power Quality Logger’ was used to measure the electrical consumption of the circuit and individual items. Managers namely Bert Riddick, Karan Jani, Bryan Morrison and some other people for ITS Learning Environments gave the permission and helped out in this endeavor. 56 Figure 52: Measuring Loads of Wall Box Component Figure 53: Measuring Load of Projector Measured readings were taken from several class rooms and all of them were pretty close. The final averaged values for each appliances were: Table 4: Measured Plug Loads Access IP Camera 1 -2 W System 5 20-21 W Circuit Board 2-3 W DVD (stand by) 1 W DVD (working Mode) 15 W Projector – Standby Mode 15-17 W Projector – Working Mode 310-315 W These measured wattages were later clubbed under three equipment categories for classroom having their respective schedules. These schedules were based on the current operation of the building. 57 3.5.3. Glazing Properties – SHGC & VLT The glazing properties of the glass ware measured using Light Pocket Detector & SHGC Calculator which helped in determining the Visible Light Transmittance and Solar Heat Gain values respectively. Light Pocket Detector was borrowed from Prof. Schiler’s Library whereas SHGC calculator was borrowed from SCE Tool Lending Library. Same glass type was used throughout the building. There was no difference between the glazing’s based on orientation. The visible transmittance values recorded were in the range of 53.6 to 54.5. The reflectance values recorded were in the range of 6.2 to 6.6. SHGC calculator constantly gave the reading as clear glass. As per the manual, this meant that there is no low-e coating on the glass and the SGHC value is higher than 65.5. 3.6. Lighting Power Density Lighting Power Density was calculated using the inventory provided by FMS. The inventory was verified by a site walk and manual counting of fixtures. The inventory was divided per room basis with the relative number of fixtures that each room had. Areas of the room were taken from the drawings that were procured from FMS. The total lighting power consumed by the room was then divided by the total area to get the Lighting Power Density. This gave the electrical usage at the peak time. 3.7. Investigation Work Investigation work was done using another tool borrowed from SCE library which is FLIR thermal camera. Investigation work was done to identify the hot and cold deck of HVAC system and to figure out possible thermal breaks or leakages in the building. 58 Figure 54: Thermal Image above False Ceiling Figure 55: Thermal Image Looking at Diffuser The investigation was even done to find if the diffusers were actually working. Only predictable leakages were found. However, the HVAC had some weird things going on which were discovered later. The whole building should have had a dual duct system having both hot and cold deck; however the thermal camera didn’t have both at quite a few places. Initially, at this stage it was thought that it is something wrong on our part but later found out the complexity of the situation. 3.8. Site Visit Notes There were a lot of site visits that had to be conducted. It was not a very big and tedious task as the site was within the University. A number of visits were conducted to this building; self-study was done in VKC library and classrooms to understand the functionality of the building and the behavior of users. A number of regular students and staff members were also interviewed. Some of the findings are described below.  There are no operable windows in the building which sometimes makes the air stale especially during the weekends when students are studying till late. 59  Corridor lights are ‘on’ 24x7. There are no sensors in corridors and no one takes the trouble to switch them off during non-occupied hours.  All lights are switched on in the library as soon as the library is opened irrespective of the time of day.  All the classrooms in the east wing are new classrooms where as the west wing are still old classrooms.  There are 6 vending machines and 9 water fountains that add to the plug loads of the building.  Sometimes of the year, film shooting takes place in this building which might consume a lot of energy.  Full library is on two HVAC zone, one with perimeter controls near the glazing and second for the deep inside space. Very limited thermostat controls. As per the description of the librarian, if the outside temperature is 90F, the library is freezing cold. It is probably because of the location of thermostat near the glazing.  The envelope of building itself hardly provides resistance to the outside conditions.  There are no controls in the students lounge on the third floor as the thermostat is in one of the offices and that is generally locked after office hours. This provides discomfort as they are unable to change the temperature locally even though the users have very less flexibility. 60 CHAPTER - 4: SIMULATION SOFTWARE & MODELING INPUT This chapter briefly describes the selected simulation software and reason for choosing the same. The differences of two widely used simulation software are discussed followed by the process of making simulation model and the difficulties faced by them. 61 4.1. Choosing Simulation Software The main challenge was to choose the ‘whole building simulation tool’ to finally take on the mammoth task of Zero Net Energy goal. Various simulation softwares were experimented as discussed in Chapter-1. There were two simulation softwares that were finally selected. First was eQuest (based on DOE-2 engine) which is freely available and highly used in the professional market especially in California. Second was Design Builder which is based on Energy Plus engine and gaining a lot of market. A thorough analysis was done to study both softwares in depth to finally choose one out of the two. Some of the differences observed are mentioned below. These differences are important to understand the functionality of each software tool. More detail about the differences can be found in the paper that is currently been submitted in SimBuild 2012 by the author “Comparing different simulation softwares while calibrating the same building”. 4.1.1. Calculation Method  Design Builder: thermal balance method  eQuest: weighing factor method 4.1.2. Calculation Time  Design Builder: depends on complexity set on model. It can take much more time compared to eQuest.  eQuest: faster (quick) 62 4.1.3. Temperature Both eQuest and Design Builder have only one user defined temperature per zone. 4.1.4. Load Calculations Design Builder uses an integrated simulation methodology that solves for heat and mass balance for each surface, and calculates space loads and building systems simulation at the same time step. “Zone,” “system,” and “plant” talk and provide feedback to each other for each time step of simulation. In this case, an energy balance equation is written for each enclosing surface in addition to an equation for room air that allows the net instantaneous sensible load to be calculated for space air. (Wadell and Kaserekar 2010) Non-linear processes like air convection, solar gain, and radiation from interior surfaces are taken into account as the net energy transfer to each inside surface. This energy must be exactly balanced by heat conducted to or from those surfaces. This resulting variable surface and air temperatures are solved by energy balance equations leading to net heating and cooling loads for the zone. On the other hand eQuest assumes that all processes modeled are independent of each other and linear in operation. Heat gains are calculated independently from various sources and then added together to obtain the total cooling load. (Hunn 1996) While calculating the load, instantaneous heat gains for the zone are calculated using the fixed user specified zone temperature. Non-linear processes like convection or radiation are approximated linearly. Transfer coefficients are constant, and no dynamic heat flow is calculated. In the case of solar gains, eQuest uses a user-defined fraction multiplier for all opaque objects and interior surfaces to calculate the incident direct and diffused solar radiation in the space. By default, 60% is absorbed by the floor and the remaining 40% is 63 distributed to the remaining surfaces based on their areas. Once the cooling load is calculated, weighting factors are applied to the zone materials to estimate the energy stored that would be released later to the space. Only one set of weighting factors is used over the entire simulation period. (Hunn 1996, Wadell and Kaserekar 2010) 4.1.5. Design Conditions Design Builder has preset ASHRAE Handbook recommended outside dry bulb and wet bulb temperatures required to calculate heating (99.6% and 99% coverage) and cooling loads (99.6%, 99%, 98% coverage) for all locations in the Design Building location template. It even has a typical dry bulb range that it uses to calculate hourly dry bulb temperatures for the 24 hour design period. While calculating cooling loads, Design Builder gives an option of choosing the design month and date to be a design day. However, Design Builder does not use outside dry bulb (ODB) and outside wet bulb (OWB) temperatures of that date and month from the weather file but uses ASHRAE defined outside temperature to calculate the load. The schedules of the chose design day are also not followed to calculate the load. Summer and winter day design schedules are described clearly while making the schedule for each function in building. While calculating loads, Design Builder just uses its own schedule irrespective of the fact that design day chosen might be a holiday or a weekend. The only way that loads get affected by choosing different design days or months is due to radiant transfer of heat. Different amounts of solar gains get transferred inside the space either directly through windows or by radiant fraction from the walls because of the different solar angles in different months. Solar gains through windows, roof, and ground are the main contributors to this. 64 eQuest gives two options to the user. Either the user can define the design days based on ASHRAE Handbook data to help eQuest determine the peak loads for system sizing, or eQuest will automatically calculate peak loads and size HVAC systems using the weather file. If using the user defined data, the design day input tab needs to be in the project component tree which results later on in the generation of design day report (LS-A space peak load summary report) within the D2SIM. eQuest provides an opportunity to either set one day as the design day or set the range of days out of which eQuest can calculate peak loads and size the system while using user- input design day option. 4.1.6. Sizing of Systems Design Builder uses algebraic energy and mass balance equations combined with steady state component models to simulate HVAC systems. It provides four options for calculating loads and sizing systems. These options are ASHRAE, variable air volume (VAV), fan coil unit (FCU) and unitary DX. These four options do not have much impact on sensible cooling requirement of the space but do affect design flow CFM required and latent cooling. These parameters collectively lead to different cooling loads. As a methodology, peak loads, and moving averages for the system is calculated using zone sizing and outside weather conditions for each sizing period. Then the system sizing calculations are performed. On the other hand, eQuest does not give any type of Design Builder options, but does give an option to calculate loads based on coincident or non-coincident parameters. According to coincident parameter, supply-flow is sized using the peak value of sum of 65 loads of the zones on the system (Hirsch J. 2010). However, non-coincident parameter sizes the supply-flow using the sum of peak loads of the individual zones. 4.1.7. Choosing the Final Simulation Software – Design Builder Design Builder was finally chosen keeping in mind the latest Energy Plus engine that it runs on. The overall data output options both graphical and excel format, accurate calculations methods and results, preset ASHRAE design values, compatibility with gbXML, better interface, detailed HVAC option were some other dominant reasons for choosing this UK based software over eQuest. 4.2. Tedious Process of making model This section describes the difficulties that were faced while modeling the VKC model and remedies that were sought in finally making an accurate model. The problems faced with using an accurate weather file are also described in the latter half of this section. 4.2.1. Importing Model It was a very tough task of making the VKC model keeping in mind the floor area it has. The model was kept really basic in terms of massing to avoid interoperability issues. Only outer shell of VKC was made in Revit. In other words, the original model, created in Revit Architecture, was kept very simple in terms of massing and consisted of only the major exterior walls and no interior partitions. This was done after previous failures due to incompatibility issues between Revit and Design Builder. The things like cornices and other related things that are not related to energy calculations were not modeled. 66 Figure 56: Revit Model of VKC Special care was taken to verify that all the walls touched the roof in Revit model, or else when exported in simulation software the “zone” is not properly recognized leading to error in simulation. “Rooms” (enclosed spaces in Revit) were added to the layout and named before exporting. The Revit file was exported as gbXML file format and then imported in Design Builder which is the simulation software that was used for calibration. Initially, it appeared that it was a complete waste of time to have created the model in Revit as none of the objects were transferred properly to Design Builder. It looked like all the model was to be made again in DB as it would take equal amount of time to rectify gbXML file. However, a work-around was found; by transferring the model first to Ecotect then creating a gbXML file, the building model was able to go into Design Builder. The transfer of gbXML file was not clean but much better than direct conversion to Design Builder. However, many adjustments had to be made. All the punctures in the model in the form of windows and doors were verified and adjusted as needed. The cut 67 out in the basement had to be totally remade in Ecotect. The extended solar shades at the roof level had to be reconstructed as well. Figure 57: Ecotect Model of VKC Once the gbXML was corrected properly, it was then exported again to DB. The outer shell transferred pretty well this time except that some windows were missing and had to be redrawn in design builder. Figure 58: Design Builder Model of VKC 68 Once minor modifications were made, the internal partition walls were created in Design Builder to further detail out the model based on zoning plans that are discussed later in the chapter. Overall, the transfer of the gbXML file from Revit to Design Builder through Ecotect was not clean but much better than a direct conversion to Design Builder. It was observed later that even though central open courtyard in the basement was correctly imported as geometry but was being treated as ground and not as an open space by Design Builder. The openings could not be modeled on the courtyard facing walls as the adjacency was modeled as ground conditions and not as exterior wall. After more exploration of Design Builder capabilities, the adjacencies of courtyard walls were modified as exterior walls and openings could then be modeled in the geometry. 4.2.2. Weather Data The building is located in Los Angeles. However, in case of calibration we cannot use generalized data for Los Angeles Airport weather station. We need to have site specific data for the year the calibration is done. The weather data was acquired from a company called ‘Weather Analytics’ which provides the weather data based on the exact building location. This process of acquiring data was not as simple as it seems. It took a lot of time with back and forth exchange of data to finally get what was required. There was initially some delay to give the data from their side as there was some system upgrade going on during that time. Once I finally received the link to download the data, it didn’t work in my system. It was later understood that the link is not opening by direct clicking on it; it had to be pasted separately in the browser in order to open it and initiate the download. 69 Once everything settled in and given data was tried, it was realized that the full TMY file was given which is constructed from 30 years of data and not of a particular year that was required. Later, it was told that they only have 2009 data at present and don’t have 2010 data due to some discrepancy in 2010 data. 2009 was not of much use as simulation model was to be calibrated for recent 2010 year. However after a couple of weeks, 2010 weather data (.EPW) was finally received. This was one of the very first files that they took out from their newly organized 2010 data. It was asked to bring to their notice if any problem was faced. They will help with troubleshooting. The problems indeed occurred. The weather file provided didn’t let simulation happen. It was then realized that the .STAT was required in addition to .EPW (Energy Plus Weather) file which was currently not implemented into the delivery of data by Weather Analytics in their new data set. The build-in converter in Design Builder was tried to convert .EPW file to .STAT file but that gave another error. This clearly stated that the weather file provided had a bug of some kind which is constantly crashing DB and not letting the simulation happen. The matter was reported back to ‘Weather Analytics’ and they confirmed that there were some bugs in all the data sets that were released during the time it was received from them. They re-ran VKC site and gave new weather files which were promised to be bug free. This new weather file finally worked. Conversion from .EPW file into .STAT file was successful using DB internal calculator in order to move forward with the simulations. However, this joy only lasted for few weeks. While simulating the September month which was the hottest month in 2010 and had even recorded 113F in downtown LA on Sep 27 2010, the weather file didn’t show those numbers. This casted doubt on the viability of the data that was provided as there were press releases that confirmed Sep27 70 2010 to be the hottest day of the year and the weather data didn’t show the same temperature. These doubts were expressed to Weather Analytics. They figured out the problem and came back with reasoning. They sent a reference image with the possible explanation for the discrepancy. Figure 59: Location of Site & Weather Station, courtesy Weather Analytics, 2011 As per the image, VKC site is the ‘yellow tower’ and the closest weather station is the blue triangle. The weather station (blue triangle) tracked a temperature of about 108F that day at 11am and VKC showed 105F at about 9am (based on computer calculations). It is slightly different but their files are constructed by integrating the weather for the NOAA grid area (outlined in red in the image) and the closest weather station (blue triangle). VKC is at the far end of the adjacent NOAA grid and may actually be slightly overly influenced by the balance of the grid which is mostly away from downtown. A link was finally received that had the output directly from the weather station which is in 71 downtown and is only 5 km away from my site. That weather file was used ever since and luckily didn’t run into any other problems. However, a slight glitch about the final weather file was found while writing a publication paper for SimBuild 2012 on ‘Comparing two simulation softwares while calibrating the same building’. The weather file didn’t contain the header section. In traditional .epw files, location, geographical coordinates, heating, and cooling design day information are contained in the header. However, the missing header in the weather file did not give any problems in Design Builder simulations as it does not require design day information from the weather file for calculating loads. The tabs and design day information are already defined based on ASHRAE separately from the weather file. 4.3. Design Builder Model Making the design builder model took an immense amount of time and effort. There were numerous other problems that were faced during the process. Some were so intense that the answers were sought from Design Builder Support Team. Some of the problems faced in the process of building this model are discussed below. Figure 60: Design Builder Model (South View) Figure 61: Design Builder Model (North View) One of the first problems faced was due to the plenum spaces within the building. It constantly gave errors if the gbXML imported in DB had false ceilings. Finally, false 72 ceilings were removed before importing in DB which brought the clean model but with wrong volume of space. Now, it was important to understand the best way to model a plenum which is not used for distributing supply air or for collecting return air. The confusions were if we need to model plenum as a separate zone or it can be defined as air gaps in the construction. The latter is what was finally done as directed by DB support team. Another problem faced was an error message that constantly cropped up for couple of spaces in VKC. The error was "The cooling load has been calculated as zero - do u want to switch off cooling in this zone?” It was not coming as a warning but as an error message. This was confusing and all inputs were checked for those spaces. DB support team when contacted said that it is just a request for more information from DB and not an error. They accepted that lately they have been receiving lots of clarifications on this aspect. They would update it in their newer version. Naming convention used within Design Builder (DB) created a lot of confusion. Even though 2010 weather data was being used for simulations, Design Builder constantly kept on converting it to the 2002 while displaying results. There was no possible explanation that could be thought off. The Design Builder Support Team then clarified that this is a normal behavior in Design Builder. The DB weather tool automatically sets the year field to 2001 for all records of the weather data. This is done to ensure that daily, hourly and sub-hourly data generated by Energy Plus is correctly synchronized with the DB graphic display. 73 4.3.1. Settings used for calibration at Building Level The broad settings are needed to be set up right in the beginning of simulation process. The sub settings under main settings are also very important to be set in the beginning. These settings actually guide DB to the kind and complexity of inputs that are to be brought in front of users. Figure 62: Model Setting in Design Builder All the setting subheads namely scope, construction and glazing data, gains data, timing, HVAC, natural ventilation, cost were carefully understood by reading the Design Builder help file before settling on appropriate setting tab. However, the changes in setting happen in the due course when more options are needed. As an instance, the HVAC setting was initially kept as compact but changed to detailed in the latter part of thesis as more flexibility was required in HVAC options. 74 4.4. Building Inputs Once the broad settings are set, the next step is to make sure all the inputs are entered correctly. The modeler needs to ensure that the model is not loaded with unnecessary information but has all essential information that is needed for an accurate simulation. 4.4.1. Zoning Of Building The very first step was to do zoning of building. Various adjacent spaces of like functions were clubbed together to form a single zone. This step is extremely essential to help reduce the simulation time considerably while still maintaining the accuracy. Figure 63: Layout of all spaces in VKC 75 4.4.2. Conditioned and Non Conditioned Spaces The next step after zoning of various functions is to make sure that the model corresponds to the exact zoning of air conditioning as well. Only those areas should be conditioned in model that is actually getting conditioned in the building. Figure 64: Conditioned & Non Conditioned Spaces in VKC The whole building is conditioned by four Air Handling Units (AHU) located in basement. Each AHU serve their respective wing. The color coding has been done in the figure above to show the areas that are served by their respective AHU’s. The places like restrooms, mechanical rooms, staircases, partial corridors, that are not conditioned in actual building has been assigned as non-conditioned spaces in model 76 4.4.3. Construction This section describes all the construction inputs that are used for modeling purposes. 4.4.3.1. Walls Figure 65: Cross Section of VKC Walls Figure 66: VKC Wall Properties 4.4.3.2. Roof Figure 67: Cross Section of Roof Figure 68: VKC Roof Properties 77 4.4.3.3. Floor Slab Figure 69: Cross Section of Typical Floor Figure 70: VKC Typical Floor Properties 4.4.3.4. Basement Ground Floor Figure 71: Cross Section of Basement Floor Figure 72: VKC Basement Floor Properties 78 4.4.3.5. Basement Retaining Wall Figure 73: Cross Section of Retaining Wall Figure 74: VKC Retaining Wall Properties 4.4.3.6. Door Figure 75: Cross Section of Door Figure 76: VKC Door Properties 79 4.4.4. Openings Figure 77: Design Builder Glass Inputs Total Solar Transmission (SHGC) = 0.62 Direct Solar Transmission = 0.48 Light Transmission = 0.57 U-Value – 1.018 Btu / °F ft 2 hr Basement has an open courtyard with glazing on all four sides. DB couldn’t model the windows in the basement walls and hence the whole wall was given a glass property. The U-Value given to this glass wall was 0.906 Btu / °F ft 2 hr. Figure 78: Glazing Properties 80 4.4.5. Air Tightness & Ventilation Model infiltration has been modeled to 0.7 air changes per hour. 4.5. Building Variables – Per Space Type There are a lot of building variables that have to be inserted in the model that are estimated, calculated or measured. These all variables are listed out per space typology to document all the simulation inputs. Exterior lighting which doesn’t form a part of any zone was added separately in lighting template. The statistics of exterior lights installed are shown below. Table 5: Exterior Lighting Statistics The assumptions and calculated values based on different zones that were input in the simulation model are described in the tables below. The zones that are covered are classrooms, offices, computer labs, corridors, library, mechanical room and restrooms. Some of them are conditioned and others not. 81 Table 6: Simulation Inputs for Classrooms Density (people/sft) 0.05 Metabolic Rate Standing/Walking Schedule Computers (W/sft) 0.37 Laptops by students & to teach class Schedule During Class + After Class ‐ Old CM Office Equip (W/sft) 0.86 Intermittant Load Schedule 1/3 regular classes (DVD+Projector+Laptop) Miscellaneous (W/sft) 0.09 Constant Loads (Camera, Projector Schedule 24 x 7 Stand By, System 5, DVD Stand By Process Load (W/sft) NIL Schedule NIL Consumption Rate(gal/sft/day) 0.003681 Schedule Cooling SetPoint Temp (F) 72 Set Back Temp (F) 85 Operation Schedule Heating SetPoint Temp (F) 68 Set Back Temp (F) 55 Operation Schedule Natural Ventilation Nat. Vent Set Point (F) NIL Max in‐out delta T NIL Mechanical Ventilation Mech. Vent. Set Point (F) NIL Max in‐out delta T NIL Lighting Target Illuminance (fc) 30 LPD (W/sft) 1.1 Ventilation Fresh Air Min Fresh Air (cfm/person) 15 Mech Vent per area (cfm/min‐sft) NIL Occupancy Gains DHW Environmental Control 82 Table 7: Simulation Inputs for Offices Density (people/sft) 0.01 Metabolic Rate Standing/Walking Schedule Computers (W/sft) NIL Schedule NIL Office (W/sft) 1.5 Typical Office Load Schedule M‐F (9am ‐ 5pm) Miscellaneous (W/sft) NIL Schedule NIL Process Load (W/sft) NIL Schedule NIL Consumption Rate(gal/sft/day) 0.009093 Schedule Cooling SetPoint Temp (F) 72 Set Back Temp (F) 85 Operation Schedule Heating SetPoint Temp (F) 68 Set Back Temp (F) 55 Operation Schedule Natural Ventilation Nat. Vent Set Point (F) NIL Max in‐out delta T NIL Mechanical Ventilation Mech. Vent. Set Point (F) NIL Max in‐out delta T NIL Lighting Target Illuminance (fc) 50 LPD (W/sft) 1 Ventilation Fresh Air Min Fresh Air (cfm/person) 15 Mech Vent per area (cfm/min‐sft) NIL Occupancy Gains DHW Environmental Control 83 Table 8: Simulation Inputs for Library Spaces Density (people/sft) 0.02/0.01 (reading/stacks) Metabolic Rate Standing/Walking Schedule Computers (W/sft) 1 Laptops, Printer Schedule occupancy sch. Desktop Office (W/sft) NIL Schedule NIL Miscellaneous (W/sft) NIL Schedule NIL Process Load (W/sft) NIL Schedule NIL Consumption Rate(gal/sft/day) 0.000589 Schedule Cooling SetPoint Temp (F) 72 Set Back Temp (F) 85 Operation Schedule Heating SetPoint Temp (F) 68 Set Back Temp (F) 55 Operation Schedule Natural Ventilation Nat. Vent Set Point (F) NIL Max in‐out delta T NIL Mechanical Ventilation Mech. Vent. Set Point (F) NIL Max in‐out delta T NIL Lighting Target Illuminance (fc) 30 LPD (W/sft) 1.1 Ventilation Fresh Air Min Fresh Air (cfm/person) 15 Mech Vent per area (cfm/min‐sft) NIL Occupancy Gains DHW Environmental Control 84 Table 9: Simulation Inputs for Computer Labs Density (people/sft) 0.05 Metabolic Rate Standing/Walking Schedule Computers (W/sft) 2.4 Desktop for students use Schedule With Occupancy Office Equip (W/sft) NIL Schedule NIL Miscellaneous (W/sft) NIL Schedule NIL Process Load (W/sft) NIL Schedule NIL Consumption Rate(gal/sft/day) NIL Schedule NIL Cooling SetPoint Temp (F) 72 Set Back Temp (F) 85 Operation Schedule Heating SetPoint Temp (F) 68 Set Back Temp (F) 55 Operation Schedule Natural Ventilation Nat. Vent Set Point (F) NIL Max in‐out delta T NIL Mechanical Ventilation Mech. Vent. Set Point (F) NIL Max in‐out delta T NIL Lighting Target Illuminance (fc) 30 LPD (W/sft) 1.1 Ventilation Fresh Air Min Fresh Air (cfm/person) 20 Mech Vent per area (cfm/min‐sft) NIL Occupancy Gains DHW Environmental Control 85 Table 10: Simulation Inputs for Circulation Spaces Density (people/sft) 0.01 Metabolic Rate Standing/Walking Schedule Computers (W/sft) NIL Schedule NIL Office (W/sft) NIL Schedule NIL Miscellaneous (W/sft) 0.2 Vending Machines Schedule 24x7 Process Load (W/sft) NIL Schedule NIL Consumption Rate(gal/sft/day) NIL Schedule NIL Cooling SetPoint Temp (F) 72 Set Back Temp (F) 85 Operation Schedule Heating SetPoint Temp (F) 68 Set Back Temp (F) 55 Operation Schedule Natural Ventilation Nat. Vent Set Point (F) NIL Max in‐out delta T NIL Mechanical Ventilation Mech. Vent. Set Point (F) NIL Max in‐out delta T NIL Lighting Target Illuminance (fc) 20 LPD (W/sft) 0.6 Ventilation Fresh Air Min Fresh Air (cfm/person) 15 Mech Vent per area (cfm/min‐sft) NIL Gains Occupancy DHW Environmental Control 86 Table 11: Simulation Inputs for Restrooms Density (people/sft) 0.01 Metabolic Rate Standing/Walking Schedule Computers (W/sft) NIL Schedule NIL Office Equip (W/sft) NIL Schedule NIL Miscellaneous (W/sft) 0.2 Hand Dryers‐1400W Schedule approx 40 times a day Process Load (W/sft) NIL Schedule NIL Consumption Rate(gal/sft/day) Schedule Cooling SetPoint Temp (F) NIL Set Back Temp (F) NIL Operation Schedule NIL Heating SetPoint Temp (F) NIL Set Back Temp (F) NIL Operation Schedule NIL Natural Ventilation Nat. Vent Set Point (F) NIL Max in‐out delta T NIL Mechanical Ventilation Mech. Vent. Set Point (F) Yes Max in‐out delta T Lighting Target Illuminance (fc) 15 LPD (W/sft) 0.6 Ventilation Fresh Air Min Fresh Air (cfm/person) 10 Mech Vent per area (cfm/min‐sft) NIL Occupancy Gains DHW Environmental Control 87 Table 12: Simulation Inputs for Mechanical Rooms Density (people/sft) 0.0003 Metabolic Rate Standing/Walking Schedule Computers (W/sft) NIL Schedule NIL Office Equip (W/sft) NIL Schedule NIL Miscellaneous (W/sft) 0.2 Schedule HVAC Sch Process Load (W/sft) NIL Schedule NIL Consumption Rate(gal/sft/day) NIL Schedule NIL Cooling SetPoint Temp (F) NIL Set Back Temp (F) NIL Operation Schedule Heating SetPoint Temp (F) NIL Set Back Temp (F) NIL Operation Schedule NIL Natural Ventilation Nat. Vent Set Point (F) NIL Max in‐out delta T NIL Mechanical Ventilation Mech. Vent. Set Point (F) NIL Max in‐out delta T NIL Lighting Target Illuminance (fc) 15 LPD (W/sft) 0.6 Ventilation Fresh Air Min Fresh Air (cfm/person) 10 Mech Vent per area (cfm/min‐sft) NIL Occupancy Gains DHW Environmental Control 88 4.6. Schedules Schedules play an important role in the accuracy of a simulation model. There are different types of schedules that are to be defined for different spaces. The first category is ‘fraction of full load’ which includes occupancy, lighting and equipment schedules. The schedules are input in fraction of time when they are operational. Domestic Hot Water is based on occupancy schedule. In VKC, these schedules were make for all 7 different type of zoning functions. Second category is ‘temperature’ which defines the operation of HVAC systems. The schedule directs HVAC systems to run under set point or setback mode. In VKC, AHU - 1,3,4 are operated at same schedule whereas AHU-2 has independent Schedule. A lot of complications were faced to input these schedules in design builder. Being an institutional building, it has such a varied schedule throughout the year. Detailed ‘compact mode’ is used to input these schedules which are based on coding and required precise inputs. Table 13: USC 2010 Calendar Schedule USC Schedule 2010 Holidays From To 1‐Jan 10‐Jan Winter Recess 18‐Jan Martin Luther King's Birthday 15‐Mar 21‐Mar Spring Break 15‐Feb Presidents' Day 1‐May 4‐May Study Days 14‐May Commencement Day 5‐May 12‐May Exams 31‐May memorial Day 5‐Jul Independence Day 19‐May 10‐Aug Summer Session 6‐Sep Labor Day 25‐Nov Thankgiving 23‐Aug 3‐Dec Fall Session 26‐Nov Thankgiving 4‐Dec 7‐Dec Study Days 8‐Dec 15‐Dec Exams 16‐Dec 31‐Dec Winter Recess 89 Overall, the schedules were based on the USC Schedule described above. In addition, ooccupancy sschedule was formed using the data that was obtained from ‘USC Classroom Scheduling’ department. A list consisting of classes and their respective timings held at VKC was obtained from them. This list even had the number of students currently enrolled in the classes. Considering the diversity factor and assuming 90% students regularly attended the class, a formidable occupancy schedule was made during the class hours. Continuous monitoring of the building during non-class hours was done by spending considerable time in the building. Various activity patterns, number of occupants in each class were noted to finally understand the occupant behavior. Equipment usage within the class is not directly proportional to the number of classes and its duration. All classes don’t use the AV equipment. A recorded list of equipment usage was obtained from ‘Information Technology Services’ department of USC. ITS department keeps a log when the equipments were used and for which classes. This was helpful to determine the intermittent load for classrooms which formulates to the majority of classroom equipment load. Furthermore, the current classrooms very prominently have been divided into new and old classrooms. The east wing predominantly has new classrooms which are remotely closed by ITS department once the classes are over. However, the old classrooms are open all night for all students to study after regular class hours. The list of old and new classrooms were taken from ITS department. The occupancy behavior in these zones varies drastically because of this small distinction. The different schedule was made for each type. 90 HVAC Schedule was obtained from Facilities Management Services at USC for both In Session and summer hours of operation. Clearly, VKC has different functions and every function has different schedule at different time of the year, it resulted in varied schedules to be formed. Please refer to Appendix-B for detailed schedule inputs to Design Builder. 91 CHAPTER - 5: LOAD BALANCE & PRELIMINARY CHECK It is a common tendency for a novice to think that once the inputs have been put in the simulation model, it would behave perfectly. However, this is not how it works. It is extremely important to verify the workability of model. A quick check must be run to analyze the model and find inputs that were overlooked or not put in accurately enough for it to behave properly. This chapter illustrates the design day load balance verification of Design Builder outputs using excel spreadsheet, thumb rules and actual tonnage installed. The lessons learnt in the process are also discussed. 92 5.1. Comparison to Utility Data & CEUS The model with the inputs discussed in the previous chapter was run under annual simulation to understand how accurate the model is at this stage. This would basically lead to the decision whether there is any need to verify the load balance and prelim check of model. The comparisons were done with two parameters. One of the comparisons was to compare the Design Builder consumption to the actual monthly utility bills. The second comparison was done by comparing the end use to that specified by California End Use Survey (CEUS). Figure 79: Initial Annual Electrical Comparison Figure 80:Initial Annual Gas Comparison This comparison with monthly utility data clearly illustrate that the simulation model as this stage is nothing less than crap. The monthly electrical consumption as shown by design builder model is at least four to five times more than actual measured utility data. The gas consumption as predicted by design builder is nowhere in any co-relation to what is actually measured for the building. 93 Figure 81: CEUS End Use (Colleges Category) Figure 82: Design Builder Predicted End Use The second comparison further strengthens the notion that all the hard work till this stage has not yielded concrete results. A lot of work is yet to be done. The end use consumption was quite clearly unbalanced. The CEUS results are quite balance for this category of building. However, DB is quite unexpectedly dominated by room electricity and others are not quite in proportion as well. Figure 83: Percentage of Fuel Consumed Figure 84: EUI of Metered Data versus DB The findings from the above comparisons clearly illustrated that there is a need to check all the inputs, verify load balance graph and bring the model within reasonable accuracy before heading for full year simulation. 94 5.2. Manual Load Balance Calculations To understand heat balance outputs of Design Builder, a reasonable benchmark was needed for verification purposes. A manual calculation was carried out in the form of an Excel spreadsheet to predict the steady state design load on summer and winter design days for each zone in the model. The steady state gains calculated by the spreadsheet are coupled with the envelope loads calculated by Design Builder to get the final tonnage of cooling per space. The same inputs that were used for steady state manual calculations were put in the Design Builder Model. The final tonnage predicted by Design Builder model was then compared to the one calculated manually. This comparison enabled me to understand and verify the proper workability of the model. Both the models were then compared against a general thumb rule of 500sft/ton and 400 cfm/ton. The results were expected to be around these parameters. One more criteria was used for final verification. The final calculated tonnage should be in the range of 161 tons which is the current installed chiller tonnage and not wildly off. 5.2.1. Excel Spreadsheet The Excel spreadsheet is divided into cooling and heating load calculations. Spreadsheet is so organized that in the row side we have all the different spaces of the building with their assigned square footages in front of each. All the columns then are catering to different variable associated with those spaces to find the loads. 5.2.1.1. Load Balance – Cooling Cooling Load Calculation takes into account many more variables than heating calculations. This is mainly because of the peak cooling load is calculated during day time with occupancy. There are a lot of variables in the form of lighting, equipment, 95 occupancy in addition to envelope gains. All the loads except envelope loads are calculated using this spreadsheet. Envelope loads using this spreadsheet are really difficult to predict as the gains would change every hour based on the direction of sun all thorough out the year. A lot more equations of heat transfer, thermal conductivity are required to calculate that which is left for energy plus simulation engine to calculate. The columns of the spreadsheet have some user inputs coupled with some formulas to finally predict the cooling load. The user inputs are floor to floor height, occupation density, ventilation method (per person/per square foot), ventilation rate (per person/per square foot), toilet exhaust, kitchen exhaust, minimum air changes per hour (ACH), sensible load per person, lighting power density and equipment power density. These user inputs are then coupled with formulas as mentioned below (Grondzik et al. 2011): People = Occupancy Density x Floor Area Minimum Ventilation for Occupants (cfm) = People x Ventilation rate per person/per sft Minimum Outside Air (cfm) = Maximum of Min Ventilation for Occupants/ Toilet Exhaust/ Kitchen Exhaust. Sensible Load from People (Btu/h) =People x Sensible Load per person Total Lighting Load (Btu/h) = LPD (w/sft) x Area x 3.41 Total Equipment Load (Btu/h) = EPD (w/sft) x Area x 3.41 The load from equipment, lighting and people when coupled with design builder envelop loads gives us the total cooling load for the building. 96 Manual Calculations for Lighting Power Density that are shown in Chapter 3 were used to calculate load balance. Likewise, Equipment Power Density was determined using the information gathered by metering manually all the equipments in the classroom as described in Chapter 3 were used for this analysis. 5.2.1.2. Load Balance - Heating These calculations were relatively easier than cooling loads as there are less variable and are a steady state heat loss. The heating loads peaks during the night time when there is no effect of sun, lights, occupancy, equipment considered for calculations. The two main formulas that were used to calculate heating load were: Equation 1: Conductive Heat Transfer through assemblies (Grondzik et al. 2011): Heat Loss (Q) = U-Value (U) x Area (A) x Temperature Difference ( ΔT) Equation 2: Ventilation (or air infiltration) (Grondzik et al. 2011): Heat Loss (Q) = 1.08 CFM DT 4 Where (Q=Btu/h; A=square feet; T=degrees F) The first equation was used to calculate conductive heat transfer through ceiling, floor, wall, windows & doors. These calculations when added together make the bulk part of heating load required. Another parameter which is heat loss through infiltration was calculated using the second equation. Before using that equation, the required ventilation rate was calculated based on ASHRAE 62.2 standards. CFM = (Occupancy x 7.5 CFM/occupancy) + (0.01 CFM/sft x Area) (Grondzik et al. 2011) 97 The final heat loss was calculated in Btu/hour to verify the outputs from design builder. The areas used for these calculations were taken from the design builder model itself so that there is no discrepancy in inputs and a viable comparison is made to DB output. 5.3. Envelope Loads from Design Builder Envelope loads were required to be calculated using advanced energy plus simulation engine to determine the envelope gain from the building. This is a complex calculation mechanism due to variable solar gains. This calculated envelope load was then added to the spreadsheet to calculate the final cooling load and tonnage to verify the sizing of systems by design builder. Quite obviously, we are unable to verify the envelope gains calculated by design builder for cooling sizing purpose. But, we are confident for the architectural inputs based on Architectural drawings and manually verified R-Values as shown in earlier chapter. Therefore, we can bank upon design builder to calculate correct envelope gains. Envelope loads calculated by Design Builder is based on design day schedule and design conditions specified for Los Angeles by ASHRAE Fundamentals handbook. The design temperatures used to calculate cooling loads were based on 99.6% coverage based on dry-bulb temperature. The values are: Max dry-bulb temperature (F) = 85.1 Coincident wet-bulb temperature (F) = 76.1 Min dry-bulb temperature (F) = 64.4 98 The calculations were based on sun’s angle during August as this the hottest month in Los Angeles as per ASHRAE Fundamentals handbook 2005. 5.4. Comparing Manual Calculations & Design Builder Outputs The same inputs put in the manual spreadsheet and Design Builder yielded different results. The manual calculations were slightly undersized whereas Design builder calculations were vastly oversized if judging criteria was kept to be 500sft/ton. The manual calculations yielded about 580 sft/ton whereas Design Builder yielded 230 sft/ton. This added to a major difference when multiplied with total area of the whole building. It was clear by comparing manual calculated design day loads and Design Builder predicted loads that there is a major discrepancy between the two. This difference confirmed that Design Builder was in general over predicting the loads. The reasons of this discrepancy were unclear as the inputs to both manual spreadsheet and Design Builder model was the same. The only thing that was sounding logical was that there is some error in Design Builder inputs. But, various questions arose in order to find the error. Where to start finding the error? What is the variable that is causing this discrepancy? Is it only one variable or set of different variables that is leading to these outputs? The two way approach was taken to unravel this mystery. Firstly, the spaces that were highly out of sync with the thumb rule were single out. There spaces were seen with utmost curiosity to find out the problems and hiccups. On the second hand, various experiments were done to see the impact of each parameter that was inserted in design 99 builder on cooling load. This would even give the insight on how design builder calculate all loads. To begin with the first approach cited above was a failure as almost all the spaces were out of sync to general thumb rule. This made it clear that some major input is wrongly cited. For the second approach, three types of experiments were carried out. The first one dealt with all the inputs in the Activity, Lighting & HVAC template of design builder. There were 75 simulations done to understand each parameter. Second and third experiments were specifically dealt understanding the effect of various inputs that pops up once we are on ‘Cooling Design’ tab in order to calculate cooling loads. Sizing of HVAC systems in order to understand how it actually calculates loads and what parameters affect it were the highlights of second and third studies. 5.4.1. First Experiment It took me 75 Simulations to understand how each input parameter in different DB tabs contributes to calculation of loads. The learning from this exercise is recorded below. 5.4.1.1. HVAC Tab  HVAC Templates doesn't matter, unless you select template as no cooling. That is the one that concerns with heating only or with natural ventilation.  In Cooling Load Calculations, quite expectedly DHW & Heating tabs don’t contribute.  If we ‘uncheck’ cooling, there won’t be any cooling load calculated for that zone.  Type of mechanical ventilation and ‘check/uncheck’ affects the loads.  Equipment COP, supply air temp, fuel type, auxiliary energy doesn't affect loads. 100  A schedule does matter while calculating loads. 5.4.1.2. Lighting Tab  Set the ‘General Lighting’ input to W/sft instead of W/sft/fc by going to settings of Design Builder.  There is very small difference if we calculate cooling load using ‘General Lighting’ or ‘Task Lighting’ as primary inputs. This is probably because of schedules.  Lighting template doesn’t matter.  Luminaries ‘Type’ whether suspended or recessed affects the total load calculated. If all luminaries are suspended the entire heating load generated from luminaries is counted towards space load. However, for recessed luminaries the load is partially distributed to plenum.  Lighting control in the room affects the loads. A setting if changed from linear to 3-stepped reduces the load tremendously. Continuous dimming or multi-step dimming harvests a much higher amount of daylight when there is little daylight in the space. 5.4.1.3. Activity Tab  Occupancy Density as expected affects the total cooling load.  Lowering the cooling set point increases cooling load, decreases latent load (if set dynamically) and in turn affects occupancy load.  Variation in set-back temperature doesn’t affect cooling load as expected. Cooling load is calculated at peak time using set-point temperature and not setback temperature. Setback temperature might affect in annual simulations. 101  Increase in Metabolic Activity increases cooling load as the sensible load would increase.  Increase in Minimum Fresh Air (cfm/person) increases the cooling load as more infiltration happens.  There is no effect of DHW consumption rate, natural ventilation and mechanical ventilation on load calculations.  There is no effect of ‘Target Illuminance’ on load calculations. This was an unexpected event. It was expected this would reduce lighting consumption and reduce gain. But apparently this place a different role than lighting power density. It was later understood that this option only has an effect when we are trying to save energy by harvesting natural daylight. It is only above this Illuminance level that the artificial light would be turned off or dimmed. 5.4.1.4. General  Design Builder by default calculates Latent heat gains as Dynamic load. It takes into account the metabolic activity of the occupants in a space and derives the latent load for its calculations. We can change either keep it as is or change it to fixed fraction to tally with manual calculations.  Set up your own activity template for different functions in the building instead of modifying each parameter individually like LPD, EPD etc per zone. This will save tremendous amount of effort and time.  If one gets an error “Cooling Load has been calculated as zero - do u want to switch off cooling in this zone". There can be two reasons. Either it genuinely 102 doesn’t have a cooling load or your schedule is not correct. Check schedule before taking any step. 5.4.2. Second Experiment Another experiment was done to understand the effect of various inputs that pops up once we are on ‘Cooling Design’ tab in order to calculate cooling loads. This became necessary when it was noticed that Design Builder gives an option for choosing the date and month to be your design day. This was particularly disturbing as other simulation softwares don’t work on the same mechanism. Design day is considered to be a hypothetical day which is based on the hottest month provided as per ASHRAE handbook. This data provided by ASHRAE handbook is normally collected based on years of data and not just one day that we can insert as required by the “cooling design” tab in DB. The summary of learning is recorded below:  Loads Change with different Design Day selected.  Design Day follows its own schedule and not of any particular custom day which is been termed as Design Day. Summer Day Design Schedule and Winter Day Design Schedule are mentioned clearly while making the schedule for each function in building. While calculating loads, Design Builder just uses its own schedule irrespective of the fact that design day chosen might be a holiday or a weekend.  Design Day uses (%) coverage based on dry-bulb temperature as per ASHRAE handbook irrespective of the month and date we choose to be a design day. The 103 outside dry bulb temperature of that month from the weather file doesn’t have any impact on cooling loads.  Loads get affected by choosing different days and months because of solar gain penetrating and affecting the building varies. This is the only variable that changes with choosing different month or day as ‘Design Day’. Solar gain through windows, roof and ground are main contributors to bring forward this change. After this experiment, one thing that got clear was that Design Builder has a different way of calculating cooling loads compared to other simulation software like eQuest. Design Builder calculates maximum load on a particular day peaking at different timings of the day for different zones. However, eQuest calculates peak cooling load for a space from full range of 365 days. We need to make sure we are using the hottest month as specified by the ASHRAE handbook to calculate the loads. This difference has been explained more explicitly in Section 4.1 of this thesis and the paper written by author for SimBuild 2012 “Comparing different simulation softwares while calibrating the same building”. 5.4.3. Third Experiment This experiment was done to understand various settings for HVAC in design builder. Some of the highlights of the study were:  HVAC templates don’t affect cooling loads.  Simple or Compact HVAC setting doesn’t affect cooling loads.  ‘None’ Template for HVAC system doesn’t affect cooling loads.  Switching off Mechanical Ventilation affects Loads Calculations. 104  Sizing Methods (ASHRAE/VAV/FCU/Unitary DX) does affect the loads calculation. Table 14Process of Third Experiment: SimulationTesting Observations 1st Set Simple HVAC, Sizing Method AHRAE 1 Changed HVAC System from Dual Duct VAV to CV DX sytem (HVAC‐Simple) No Change in Cooling Loads 2Changed HVAC System to CV DX system No Change in Cooling Loads 3Changed HVAC System to VAV No Change in Cooling Loads 4Changed HVAC System to VAV with Terminal Reheat No Change in Cooling Loads 5Changed HVAC System to Split + Separate Mechanical Vent No Change in Cooling Loads 2nd Set Compact HVAC, Sizing Method AHRAE 6 Changed Simple HVAC System to Compact HVAC System with CV DX system No Change in Cooling Loads 7Changed CV DX to Split + Mech Vent. No Change in Cooling Loads 3rd Set Compact HVAC, Sizing Method AHRAE 8None Template with Heating, Cooling, Mech Vent On No Change in Cooling Loads Switched off Mechanical Ventilation Total Cooling ‐ Slight Decrease Design Flow CFM reduced by half Sensible Cooling ‐ slight decrease Latent Cooling ‐ Increased 1.5 times 4th Set Compact HVAC, Sizing Method VARIATION Sizing Method ‐ VAV Total Cooling ‐ Slight Increase (2541 to 2603 kbtu/h) Design Flow CFM reduced by half (263003 to 144717) Sensible Cooling ‐ almost same(2494 to 2499 kbtu/h) Latent Cooling ‐ Increased 2 times (47 to 103.7 kbtu/h) Sizing Method ‐ FCU Total Cooling ‐ Slight Increase (2541 to 2555 kbtu/h) Design Flow CFM reduced by half (263003 to 144775) Sensible Cooling ‐ almost same (2494 to 2505 kbtu/h) Latent Cooling ‐ almost same (47 to 49.5 kbtu/h) 12 Sizing Method ‐ Unitary DX Energy Plus Error Message 10 11 9 5.5. Final Improvements to Model & its Accuracy The three experiments discussed above enabled an understanding of the behavior of Design Builder; inputs that impact loads and the mistakes that were made which impacted the simulation model to behave weirdly. Some of the main realizations through this process are listed below. 105 5.5.1. 1 st Realization: It was realized during the simulating process that solar gains were being showed during night time instead of day time. Simulation weather file was verified if that was the same weather file as obtained from Weather Analytics and didn’t make any mistake in choosing one. However, that was not the case. Hourly Weather file (.EPW) being not the problem, other inputs like the site location of the site were verified. It was found out that it was an incorrect time zone under the location template of the building. Correcting that solved this problem. 5.5.2. 2 nd Realization: One of the biggest things that was realized was the fact that in the Design Builder versions 2.1 and above the general lighting gains are defined in Watts per square foot per foot candle (W/sft/fc) instead of generally adopted Watts per square foot (W/sft). The design builder help mentions that this method has advantage over the previous method. ‘Actual lighting level is associated with the lighting system type without the need to refer to the activity and hence Illuminance requirement. So if a particular lighting system type is installed throughout a building but the building has a range of activities, it will usually be possible to enter the lighting W/m2/100lux value once only at building level, set the activity for each zone and still get realistic lighting gains.’ (Design Builder Help) This is an improvement only before the building is built. However, when calibrating an existing building, this becomes a huge problem. This small unit conversion was overlooked and lighting ended up dominating all the end uses. This increase in lighting consumption even led to higher cooling load which in turn increased the tonnage. This clearly reflected in the annual electrical consumption shown 106 in the beginning of this chapter. Once the units were changed from W/sft/fc to W/sft, the DB output results appeared to be much more realistic. These experiments and various key realizations helped in finally improving the model and bring it within reasonable range to thumb rules and manual calculations. By this point, it was convincing enough that the loads are correct and the model is ready to be simulated on annual basis. However, one thing that must be noted is that the HVAC systems were defaulted to preinstalled CV Dual Duct template while sizing the system. Any HVAC inputs were not put as it was not required at this step. This exercise was just for load balancing. 5.6. Problems Faced During Simulations There were some problems that were faced in addition to the realizations discussed above. One of the problem faced was that the ‘Templates’ that are created in DB don’t get update automatically once we make changes in it. It is still required to go to each space and press Apply in order to bring the change. Initially a lot of simulations were run totally ignorant of this fact and the results were similar. It was quite frustrating to finally figure out a small glitch in DB. There was not any full model data report available in DB v3 in which all the inputs could be compared at one place. However, it was later discovered that a CSV report could be generated that had some summary of zones. Though, this is not an extensive list of inputs but is still fruitful to look at. Lastly, there was a feature that was found missing in DB was the comparison tool within DB. All the data must be exported from DB in order to compare different simulation 107 data. This step is extremely important to assess the impact of each change with respect to previous ones. These parametric runs can help in comparing the load reduction values, savings in different parametric runs and comparison on a single screen. 108 CHAPTER - 6: BASELINE CASE Once the required changes were made and the loads of VKC buildings were verified and cross checked with rules of thumb and manual calculations, it was time to move ahead for annual simulations. This chapter briefly describes the process to achieve the baseline model that was close enough to the actual building energy consumption. This baseline was to be established within certain error margin as discussed below. 109 6.1. Calibrated Model Error Margin Before jumping into annual simulation, it was important to understand the acceptable tolerances for calibration that are accepted by various standards and protocol. These tolerances are a range within which the simulation model is considered to be calibrated. As discussed in first chapter, the acceptable tolerances for monthly data calibration are as follows (IPMVP 2002) (FEMP 2012)(ASHRAE 14): Table 15: Acceptable tolerance for monthly data calibration INDEX ASHRAE 14 IPMVP FEMP ERRmonth ±5 % ±20 % ±15 % ERRyear ±10 % CV(RMSEmonth) ±15 % ±5 % ±10 % * ERR: Mean bias error * CV (RMSE): Coefficient of Variation of the root mean squared error CV (RMSE) (Coefficient of Variation of the Root Mean Squared Error) measures the differences between simulation model predicted values and values actually metered. A lower value indicates higher quality and less variance ( Noesis Energy 2012). A decision was to be made as to which standard or protocol shall be followed in order to move forward with calibrations. ASHRAE 14 was chosen as the standard to go forward with considering the fact that this standard is widely accepted. Coefficient of Variation of the root mean squared error (CV_RMSE) was chosen as monthly error analysis would be more accurate than annual error analysis. 110 The formula used to calculate this error is as follows: Figure 85: Coefficient of Variation of the root mean squared error (Pan, Huang & Wu 2007) 6.2. 1 st Annual Simulation Attempt A baseline model was to be created to carry out further calibrations. The model discussed in the beginning of Chapter-5 was completely out of sync with the monthly utility data. The end use consumption was clearly unbalanced. Now, once the inputs were verified, load balance corrected and model was within reasonable accuracy, the first simulation run was done. 111 6.2.1. Electrical Usage Comparison to Utility Data & Error Analysis Figure 86: 1st Attempt Electrical Comparison VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 101620.08 1.26 feb'10 91999.39 90577.17 1.27 mar'10 108408.35 99291.79 8.17 apr'10 110059.49 96219.64 12.40 may'10 113358.07 107234.11 5.49 jun'10 103089.41 109995.19 6.19 jul'10 113854.01 112046.86 1.62 aug'10 119151.50 111751.17 6.63 sep'10 124537.59 109234.79 13.71 oct'10 139019.75 117271.40 19.49 nov'10 118898.35 104484.76 12.92 dec'10 93709.65 95613.60 1.71 Electrical Comparison Figure 87: 1st Attempt Electrical Comparison This DB predicted electrical usage when compared with monthly utility data confirmed that the model has significantly improved. As far as the error analysis is concerned, only October month (red zone) looked above 15% CV(RMSE) error. 6.2.2. Gas Usage Comparison to Utility Data & Error Analysis Figure 88: 1st Attempt Gas Comparison VKC Building (kBtu) DB Model (kBtu) CV(RMSE) jan'10 459253.29 1130.70 177.06 feb'10 207718.03 1007.49 79.89 mar'10 383274.08 1167.32 147.68 apr'10 348558.03 1081.94 134.30 may'10 191202.99 1143.97 73.46 jun'10 127401.98 1158.53 48.79 jul'10 118808.11 1274.23 45.43 aug'10 186130.48 1280.76 71.44 sep'10 213447.34 1221.99 82.02 oct'10 255229.75 1110.68 98.21 nov'10 310264.78 1098.48 119.49 dec'10 303582.29 1190.82 116.87 Gas Comparison Figure 89: 1st Attempt Gas Comparison The DB predicted gas usage was completely out of sync with that of measured utility gas consumption for VKC. By the look of it, DB predicted gas usage is almost zero. 112 6.2.3. Closer Look Figure 90: Electrical Consumption Closer Look Figure 91: Gas Consumption Closer Look The Electrical & Gas consumption predicted by DB was analysed more closely. It was seen that even if the electrical consumption was very much within the ASRAE defined error margin, but was not following the exact pattern of electrical consumption. This created doubts on the schedules entered in Design Builder. Seconldly, it was noticed that the gas consumption for Design Builder was almost a linear line when seen in more detail. This was a clear signal that something is really off in heating inputs. 6.2.4. End Use Comparison with CEUS Figure 92: CEUS End Use Figure 93: DB End Use for 1 st Attempt The predicted end uses were compared to the California End Use Survey (CEUS) to understand the end use relationship. This strengthned that the fact that there is hardly any heating in the building which could be possible in reality. 113 6.2.5. EUI Comparison Figure 94: EUI Comparison for 1st Attempt Figure 95: 1st Attempt consumption versus CEUS The results when compared using Energy Use Intensity (EUI) clearly illustrated that the electrical EUI is very close to actual however gas EUI is nowhere near reality. It was evident from all the above graphs that the DB model has really improved from the model described in Chapter-5. However, this success was only limited to electrical component and not for gas consumption. Therefore, this model can’t be called as a baseline model unless some inputs are verified and related improvements are made. 6.3. 2 nd Attempt with Schedule Modification The schedule input in the DB was thoroughly checked and couple of mistake were found. Firstly, there was some error in the inputs of some consequent months which made the DB predicted electrical consumption not follow the exact curve of utility bills. This error was corrected. Making these changes exposed the irritating coding inputs of DB with compact schedule option. Using this option, it is necessary that the exact formatting is followed as prescribed in DB. A lot of time was wasted deciphering one glitch. A date by mistake was written without space (Dec15) instead of prescribed by DB with space between alphabets and numeric (Dec 15). 114 Secondly, some heating set points and activity templates were set for some of the spaces that were overlooked before. 6.3.1. Electrical Usage Comparison to Utility Data & Error Analysis Figure 96: 2nd Attempt Electrical Comparison VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 868242379.84 777953.98 feb'10 91999.39 770861371.63 690699.13 mar'10 108408.35 877671160.61 786398.44 apr'10 110059.49 834122508.79 747372.29 may'10 113358.07 888286342.32 795906.44 jun'10 103089.41 924634818.29 828488.11 jul'10 113854.01 964953985.93 864609.14 aug'10 119151.50 961943141.85 861906.32 sep'10 124537.59 929196072.68 832556.31 oct'10 139019.75 951342907.39 852389.47 nov'10 118898.35 866526963.66 776402.54 dec'10 93709.65 867771688.16 777540.53 Electrical Comparison Figure 97: 2nd Attempt Electrical Comparison The DB predicted electrical consumption that was very close to the actual building consumption was suddenly out of sync. This result was very counter-intuitive. The predicted energy was 10,000 times more than the actual building consumption. 6.3.2. Gas Usage Comparison to Utility Data & Error Analysis Figure 98: 2nd Attempt Gas Comparison VKC Building (kBtu) DB Model (kBtu) CV(RMSE) jan'10 459253.29 8871882000.00 3428711.46 feb'10 207718.03 12010800000.00 4641967.43 mar'10 383274.08 15605620000.00 6031259.65 apr'10 348558.03 17878610000.00 6909759.77 may'10 191202.99 17589450000.00 6798063.29 jun'10 127401.98 15412190000.00 5956599.89 jul'10 118808.11 15691230000.00 6064449.23 aug'10 186130.48 15633770000.00 6042215.52 sep'10 213447.34 14855720000.00 5741496.84 oct'10 255229.75 17534910000.00 6776959.41 nov'10 310264.78 17183970000.00 6641303.52 dec'10 303582.29 22875800000.00 8841138.46 Gas Comparison Figure 99: 2nd Attempt Gas Comparison The DB predicted gas consumption graph just inversed. Initially the heating was almost zero and now it was so high that the building gas consumption looked like zero. 115 6.3.3. Actual vs DB Predicted Electrical Energy based on end uses Figure 100: Electrical Energy End Use The electrical end uses were then plotted and compared to the total metered VKC consumption. It clearly suggested that pumps, fans and cooling was highly overestimated. 6.3.4. Actual vs DB Predicted Gas Consumption based on end uses Figure 101: Gas Consumption End Use Similarly, Gas related end uses were plotted and compared to the VKC consumption. DHW was hardly seen and heating was dominating and was over estimated. 116 6.3.5. End Use Comparison with CEUS Figure 102: CEUS End Use Figure 103: DB End Use for 2nd Attempt While seeing all the end uses together, clearly gas was highly overestimated followed by ventillation. 6.3.6. EUI Comparison Figure 104: EUI Comparison for 2nd Attempt Figure 105: 1st Attempt consumption versus CEUS While comparing the EUI, DB was highly over estimating the electrical and gas consumption. Clearly, actual VKC consumption is almost negligible as compared to Design Builder predicted consumption. 6.3.7. Problem Encountered & Remedy The above comparisons pointed out that something went drastically wrong in the model while trying to improve the baseline. All the changes were seen from utmost care to figure out this drastic change. After lot of investigation, it was realized that this problem 117 was caused due to Non-Air-conditioned spaces. The set point and setback temperatures were set as ‘0’ in the activity template as these spaces don’t contribute towards cooling. However, it was overlooked to check off cooling and heating in this zone. This made the cooling system to work constantly throughout the year to achieve zero set point. This in turn triggered heating system to balance out over cooling in the space resulting in very high electrical and gas consumption. 6.4. Baseline Model The problem discussed above was corrected and full year simulation was run again. This time it was finally some reasonable results and the model was considered to be the baseline model to carry out further calibrations to exactly match electrical and gas consumption along with appropriate end uses and chiller consumption. This would be carried out further fine tuning the model. 6.4.1. Electrical Usage Comparison to Utility Data & Error Analysis Figure 106: Baseline Model Electrical Comparison VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 116725.29 12.28 feb'10 91999.39 113016.76 18.83 mar'10 108408.35 128949.56 18.41 apr'10 110059.49 117272.57 6.46 may'10 113358.07 117343.82 3.57 jun'10 103089.41 123304.54 18.12 jul'10 113854.01 129643.58 14.15 aug'10 119151.50 135247.01 14.42 sep'10 124537.59 145459.09 18.75 oct'10 139019.75 145021.75 5.38 nov'10 118898.35 129343.70 9.36 dec'10 93709.65 109711.72 14.34 Electrical Comparison Figure 107: Baseline Model Electrical Comparison Correcting the schedules input in design builder really improved the profile of DB predicted electrical usage to that of actual measured. The changes in schedule made energy consumption for four months go out of acceptable error. However, matching the 118 profile was a better sign. It was known that further fine tuning of model would bring it within acceptable error limits. 6.4.2. Gas Usage Comparison to Utility Data & Gas Use Profile Figure 108: Baseline Model Gas Comparison Figure 109: Baseline Model Gas Comparison DB predicted gas consumption looked better than before. Upon closer look of the DB predicted curve (red) in isolation, it was a curve with high consumption during winter months and less consumption during summer months. This looked very positive than the first attempt of baseline which was a straight line. 6.4.3. Actual vs DB Predicted Electrical Energy based on end uses Figure 110: Baseline Model Electrical End Use 119 The electrical end uses when compared to total metered values looked very balanced. This was a very positive sign. 6.4.4. Actual vs DB Predicted Gas Consumption based on end uses Figure 111: Baseline Model Gas End Use The heating and DHW end uses were now visible even though were very low quantitatively. 6.4.5. End Use Comparison with CEUS Figure 112: CEUS End Use Figure 113: Baseline Model End Use The end uses for baseline looked quite balanced, but it was clear that a lot of tuning was yet to be done. 120 6.4.6. EUI Comparison Figure 114: EUI Comparison for Baseline Model Figure 115: Baseline Consumption versus CEUS The Electrical EUI was quite comparable whereas Gas EUI was still out of sync and need more tuning. 6.5. Conclusion The baseline model with basic inputs was finally ready to move forward with. However, it must be noted that it was only electrical and equipment summary that was very precise as an input at this time. The HVAC system was defaulted to Constant Volume Dual Duct system and auto sized as that was the original preliminary system in VKC. Considering the fact that the cooling loads and heating loads were verified by manual calculations or thumb rule earlier, the DB predicted energy consumption must be very close to actual consumption. 121 CHAPTER - 7 :HVAC ISSUES This chapter briefly describes the evolution of HVAC system of VKC and the complexities it created. The 55 years history of VKC was underestimated. The building evolved from the 1960’s and many renovations and changes happened over that time. The changes that impacted the calibration process are discussed in this chapter. 122 7.1. Original HVAC system The original HVAC system was a constant volume dual duct system. Two chillers running in sequential were connected to four air handlers. Each air handler had its own region of operation as described in picture below. Figure 116: HVAC Distribution System The first air handler served all three floors of the west wing of VKC. The second air handler served all areas of basement and third air handler served all the floors of north wing. The fourth air handler served all the floors in the east wing. All these systems were constant volume dual duct system. A typical section for all the wings is shown below. 123 This simple sectional system was repeated in all the three wings of the building. This straight forward system was easily modeled in Design Builder using compact mode. The baseline model was based on this. However, there were a lot of changes that happened over the time in VKC. These changes didn’t happen in one go but happened in piecemeal. This resulted in many changes that were either not connected to each other or were limited due to shortage of funds creating a big confusion. 7.2. Modified HVAC system One of the major changes that happened was to replace both chillers in 1995. This was easier to understand and grasp. However, the most difficult change was found in the air handling units. Slowly and steadily the constant volume duct system was modified in some areas to serve as variable volume with reheat. This meant that Variable Frequency drive has been attached to the AHU’s. One of the ducts from dual duct supply and return Figure 117: Original Constant Volume Dual Duct System 124 system were blocked and was serving VAV with reheat system. However, the problem lay in the fact that this kind of change was not consistent for any floor or any wing. This is what made the system even more difficult to understand and model. Sections of modified system are illustrated below. Figure 118: Modified HVAC Systems In the north wing, the original system was followed in the first floor. The dual ducts go to the first floor mixing boxes. However, on the second and third floor, heating ducts were blocked off and only cooling duct was going to the space and gets connected to VAV boxes with reheat coils. This initially created confusion as to viability of this option as one floor needs constant volume and other variable volume from the same air handler. It was later realized that all AHU’s have Variable Frequency Drive (VFD) attached to it. This meant there was a control checker to keep the constant air flow for first floor. In the west wing, the scenario was totally opposite. The third floor had the original system in which dual ducts go all the way to the third floor mixing boxes. However, on the first and second floor heating ducts were blocked off and only cooling duct was going 125 to the space getting connected to the VAV boxes with reheat coils. These reheat coils are hot water coils. The HVAC system in east wing follows the same pattern as west wing. Third floor is the original dual duct system where as first and second floor are based on VAV with reheating. However, this wing has its own story to tell. Some parts of this wing have heating coils based on electric resistance and not hot water. This adds to the complexity of the HVAC system being followed. This complex relationship is best understood when we plot the spaces with different HVAC system on floor plans. These floor plans are shown below. Figure 119: Modified HVAC System 126 The AHU-2 for basement is the only AHU which didn’t upgrade to variable volume and is functioning as per original planning. The HVAC layout on the first floor is the worst of all the floors. It has 3 different types of systems operating. 7.3. Modeling of HVAC in Design Builder Once the HVAC system of VKC was understood, the next challenge was to explore the possibility of inputting the HVAC system of such complexity in DB and run simulations. 7.3.1. Compact Mode – Failure The HVAC compact mode that was used till now in all the simulations looked like falling short to model such complex system. There was lot of limitations that were faced in this mode. Major limitation of this system was that only CAV or VAV or Unitary Multizone system could be defined per building. It was not possible to choose CAV at building level and make it VAV at zone level. Only liberty that is possible is that Fan Coil and Unitary single zone systems can be added at any zone without concern for the selection at the building level. Considering these limitations, it became necessary to use the HVAC detailed mode in DB to accurately model the systems. However, it was a huge risk to shift to this mode as this feature was recently added to Design Builder and was still improving with time. There was not even any help document available in order to understand the system deeply. 7.3.2. Detailed Mode After experimenting and self-learning, the detailed mode was understood better. The HVAC system was to be made from the beginning using line relationships. New HVAC 127 connections could be made by using any number of systems and attaching to any spaces. This mode gave a lot of flexibility in HVAC designing. There were two options provided in the detailed mode. In the first option, the HVAC schedules and set points could be used as had already been defined in the model. In the second option, the HVAC schedules and all the set points had to be defined again using set point manager. Even though the second option gave a possibility of more detailed inputs, the first one was preferred and used. Running simulations in Detailed Mode was not easy. A lot of errors cropped up and it took a lot of time to figure out the problems. Some of the errors messages are shown below. Figure 120: Error Messages in Design Builder After lot of experiments and practice it was learned that even if detailed mode gave a lot of flexibility, it couldn’t model two systems from the same AHU. An AHU can either behave as variable volume or constant volume but not both as in VKC. This limitation couldn’t be overcome and had to model a system which would be nearest to the existing system. 128 7.3.3. 1 st Approach for modeling in Detailed Mode The first approach that was taken to model this complicated system was to model the modified HVAC systems based on three different types of systems implemented in VKC serving their associated rooms. This meant not the following original design of AHU’s serving their respective wings of VKC. Figure 121: 1st Approach of Modeling HVAC System 129 The HVAC systems that were modeled were constant volume dual duct system, VAV with reheat and multi-zone system. These systems were connected to the spaces that were being served by this system irrespective of whichever wing (north/west/east). This is even shown in the modified floor plan discussed earlier in the chapter. The zone with electric reheat was served by same VAV with reheat system as rest of them but had a reheating coil as electric resistance at zone level. The Design Builder HVAC detailed mode snapshot is shown below which describes the arrangement of various HVAC system and corresponding connections. It was expected that this combination is the best possible way to depict the complicated HVAC system installed in VKC. However, after comparing the DB predicted consumption with that of actual metered consumption it didn’t sound as convincing as before. Some of the comparisons made are shown below. 7.3.3.1. Electrical Usage Comparison to Utility Data & Error Analysis The electrical consumption drastically increased and all values went 40-50% off. This was a great setback as electrical consumption looked very much calibrated before switching to detailed mode. VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 156685.14 48.08 feb'10 91999.39 150382.00 52.32 mar'10 108408.35 174002.60 58.78 apr'10 110059.49 161400.17 46.01 may'10 113358.07 165904.28 47.09 jun'10 103089.41 163740.51 54.35 jul'10 113854.01 173536.13 53.48 aug'10 119151.50 180753.22 55.20 sep'10 124537.59 191395.98 59.91 oct'10 139019.75 190920.13 46.51 nov'10 118898.35 166131.91 42.33 dec'10 93709.65 147086.97 47.83 Electrical Comparison Figure 122: Electrical Comparison Figure 123: Electrical Comparison Data 130 7.3.3.2. Gas Usage Comparison to Utility Data & Gas Consumption Curve The Design Builder depicted energy consumption still stayed low when compared to actual metered gas consumption. This was another shock as this consumption was expected to match more of actual metered with using detailed mode. However, the DB predicted gas curve had a better shape than before. It made more sense in order to drop in September and October unlike some previous results. 7.3.3.3. Design Builder Predicted End Use & EUI Comparison The mystery of more electrical consumption was solved once the end uses were plotted. Ventilation itself was taking 41% of total electrical consumption making EUI shoot up to 75.20 kBtu/sft-yr. Figure 124: Gas Comparison Figure 125: Gas Consumption Curve Figure 126: 1st HVAC Approach End Use Figure 127: 1st HVAC Approach EUI Comparison 131 It was then understood that the fans and pumps were doing a much greater job in blowing air through all three different wings and at different floors based on the layout that was created in the detailed interface. Even though this layout depicted the actual layout closely, it had overlooked the actual mechanism of supply and return air flows. Another layout and system was then developed which would be able to overcome this problem. 7.3.4. 2 nd Approach of Modeling in Detailed Mode The second approach was to keep the original HVAC distribution layout and simplify the HVAC systems to VAV with reheat. All the AHU’s had VFD’s and the systems were mostly working as VAV’s. Almost all the dual ducts were blocked off and single duct with reheat at terminals was been followed. Based on these two reasons, it made more sense to change the HVAC type instead of complex distribution system. Four AHU’s were modeled out of which three are VAV with reheat systems and one multi-zone system serving their original rooms. This layout in detailed interface served better when compared with actual metered consumption unlike previous attempt. The results were comparatively closer to actual metered values. The DB HVAC layout is shown below. 132 Figure 128: 2nd Approach of Modeling HVAC System 133 7.3.4.1. Electrical & Gas Usage Comparison to Utility Data The DB predicted electrical consumption was closer to actual consumption in this way of modeling. Gas usage was still not in sync with the actual consumption. There still exists a large discrepancy. 7.3.4.2. Design Builder Predicted End Use & EUI Comparison The end use pie chart looked comparatively better than the first case. There were still some tunings to be done to the HVAC system to bring it closer to the actual usage. EUI graph looked comparatively better as well. Figure 129: 2nd Approach Electrical Comparison Figure 130: 2nd Approach Gas Comparison Figure 131: 2nd Approach End Use Figure 132: 2nd Approach EUI Comparison 134 7.3.4.3. Actual vs DB Predicted Electrical Energy based on end uses This chart shows that the fans and pumps are still high but better than earlier approach. After comparing DB estimated values to the actual consumption, it was decided that the second approach much better represents the actual complex system. One must note that this decision was taken based on default HVAC systems inputs and the decided layout. The HVAC systems were still on auto-size mode. Once the approach was decided, this exact HVAC system description was added to the model in order to bring it close to the actual system. This process is discussed in the next chapter. Figure 133: Electrical Energy based on end uses 135 CHAPTER - 8: FULL BUILDING CALIBRATION Once the approach of modeling HVAC in Design Builder was finalized, the model was made more accurate in order to resemble the actual systems. This chapter discusses the adjustments that were made to default HVAC values in order to calibrate the model within acceptable limits. 136 8.1. Chiller Adjustments Chiller is one of the major load of the electrical consumption which varies highly based on different climatic conditions. One must note that the exterior temperature has a massive impact on chiller consumption as the R-Values of envelope are very low. There were two chillers modeled in parallel supplying cold water to 4 Air Handling Units. Part load curve was obtained from Trane for that specific chiller model and the coefficients were inserted in Design Builder. The detailed hourly Amps, supply temperature and return temperature values were obtained from Facilities Management Services, USC. The power consumption of the chiller was calculated based on this information and compared to the power consumption estimated by Design Builder. 8.1.1. Actual VKC Chiller Consumption Actual VKC Chiller consumption was calculated using hourly data on chilled water supply and return temperatures obtained from Facilities Management Services, USC. There was Amps information obtained in addition to temperatures. Date Time VKC_Chwp 3Amps VKC_Chwp 2Amps VKC_ComChw SupTemp VKC_ComChw RetTemp Delta-T gpm Tons of Cooling KW/Ton KW/Ton with safety factor KW consumed by Chiller 1/1/2010 12:00:00 AM -0.78 -0.49 62.57 64.07 1.5 384 24.00 0.71 0.75 17.95 1/1/2010 1:00:00 AM -0.78 -0.49 63.33 64.58 1.25 384 20.00 0.71 0.75 14.96 1/1/2010 2:00:00 AM -0.78 -0.49 63.37 64.87 1.5 384 24.00 0.71 0.75 17.96 1/1/2010 3:00:00 AM -0.78 -0.49 63.99 65.07 1.08 384 17.28 0.71 0.75 12.93 1/1/2010 4:00:00 AM -0.78 -0.49 64.16 65.67 1.51 384 24.16 0.71 0.75 18.07 1/1/2010 5:00:00 AM -0.78 -0.49 64.53 65.67 1.14 384 18.24 0.71 0.75 13.65 1/1/2010 6:00:00 AM -0.78 -0.49 64.96 66.18 1.22 384 19.52 0.71 0.75 14.60 1/1/2010 7:00:00 AM -0.78 -0.49 64.96 66.46 1.5 384 24.00 0.71 0.75 17.96 Figure 134: Snapshot of Chiller Consumption Spreadsheet A column was added in the spreadsheet to calculate constantly varying ‘Difference in Temperature’ ( ∆T). A constant volume pump is installed in VKC which gave a constant 137 value of flow in GPM (Gallons per Minute). Varying ‘Tons’ of cooling could then be calculated by: Tons of Cooling = (gpm * delta T) / 24 However, we need to convert tonnage into KW in order to calculate the electricity consumed by the chiller. This could be done if we knew the efficiency of chiller in KW/ton. KW/ton is the ratio of energy consumption in kW to the rate of heat removal in tons at the rated condition. The lower the value of kW/ton the more efficient the system. (The Engineering ToolBox 2011) kW/ton = Pc / Er (The Engineering ToolBox 2011) where Pc = energy consumption (kW) Er = heat removed (ton) The Chiller Motor (kW) and Chiller Tonnage was obtained from VKC Mechanical drawings. These values were 114kW & 160 tons respectively. These were divided to calculate kW/ton which turned out to be 0.71. A derate factor of 5% was used considering lower efficiency of chiller because of age. This reduced the efficiency of the chiller to 0.75 kW/ton. This kW/ton value was then multiplied with the variable tonnage calculated earlier in the spreadsheet to get the energy consumed (kW) by the chiller on hourly basis. The pivot table was used to manage such a vast data and plot it on the graph. 138 Design Builder accepts the efficiency in COP (Coefficient of Performance) and not in kW/Ton as an input. COP is a unit-less figure and higher the COP more efficient the system. COP is the ratio between useful energy acquired and energy applied and can be expressed as: COP = E u / E a (The Engineering ToolBox 2011) E u = useful energy acquired (Btu in imperial units) E a = energy applied (Btu in imperial units) kW/ton value was converted to COP by using the formula described below: COP = 12 / (KW/ton) / 3.412 (The Engineering ToolBox 2011) However, there was a small glitch as the chiller data provided by FMS didn’t have recorded readings for about 7-8 weeks in the latter half of the 2010. When inquired for the missing report numbers, it was informed that the system was getting upgraded and no data was recorded during that span of time. The available data was then normalized to predict the actual consumption. Figure 135: Chiller Electrical Consumption 139 Once gone through this process, the results looked promising till the time a major error in approach was highlighted by Peter Simmonds. It was realized that while calculating these values, load of chiller (tonnage) was reducing based on consumption but the efficiency was constant. This meant that the chiller is working at its maximum efficiency all the time which is not the case in the real world. A part load curve was required in order to accurately calculate the energy consumption by the chiller. The curve which is based on Carnot Cycle principles was not available. This process was halted till this problem could be resolved. Different possibilities were looked into to solve this problem and are discussed below. 8.1.2. Chiller Template in Design Builder One of the easier ways was to check in the Design Builder preset templates and find the matching part load curve. In the Design Builder detailed mode, there are about 100 different type of chillers from which we can choose the one that is installed in VKC. Figure 136: Chiller Properties in Design Builder It has the chillers from York, Trane, Carrier, McQuay in the default template list. In each template, complete information of each chiller is given inclusive of part load curves, 140 temperature curves etc. However, the specific Trane model that is installed in VKC was not available in the default template list. But, the list had a chiller which was a close match to the one installed in terms of typology and tonnage. Even if this one is close enough, it couldn’t be used. The reason being that part load and temperature curves would still be different for model. It was now realized that the part load curves were not only important to calculate the actual electrical consumption by VKC chiller but also to simulate the same chiller in Design Builder. 8.1.3. Part Load Curves The attempt which turned out to be a failure led to another idea of contacting the Trane Vendors to get the required curves. In order to get the precise part load curves, Trane vendor was contacted through Mr. Nabil Mikhail who is the head of Mechanical Engineering Department at Harley Ellis Devereaux (An Architectural Firm in LA) and a good friend. Trane engineers gave the part load curves of the specific chiller model installed in VKC using the serial number. This proved to be a big breakthrough. The part load curve was a quadratic equation with the following coefficients and range: Coefficients: Coefficient 1: 0.305765, Coefficient 2: -0.154808; Coefficient 3: 0.848454 Range: Minimum X 0.3 and Maximum X = 1.01 141 This curve coefficients once obtained were studied in MATLAB to understand the form of curve. Jing Pu, a graduate student at USC in Electrical Engineering department helped in this process. Figure 137: Chiller Part Load Curve Study in MATLAB Once the part load curve was obtained, it was now important to first modify the calculated Actual Energy consumption of VKC and then update the chiller information in Design Builder. It was only then we could move ahead with calibration of chiller. 8.1.4. Modification to Actual VKC Chiller Consumption Considering the non-engineering background of author, some of these part load curve phenomenon took some time to digest. Various steps were taken and the spreadsheet was corrected in a piecemeal manner and not in a single shot. 8.1.4.1. Step 1: Slope The first modification to the spreadsheet was made by using the slope of the curve. The first and last co-ordinate was joined together to roughly estimate the performance of chiller. The slope of the line calculated was as 0.842. 142 Figure 138: Chiller Curve Slope Study Initially tons of cooling were directly multiplied by fixed kW/ton value to calculate the energy consumption (kW) used by chiller. However, once this curve was obtained the following formula was used to calculate energy consumption: Energy Consumption = (kW/ton) x (% of Total Load) x slope Date Time VKC_Chwp 3Amps VKC_Chwp 2Amps VKC_ComChw SupTemp VKC_ComChw RetTemp Delta-T gpm Tons of Cooling KW/Ton KW consumed by Chiller - Slope 0.842 1/1/2010 12:00:00 AM -0.78 -0.49 62.57 64.07 1.5 384 24.00 0.71 9.00 1/1/2010 1:00:00 AM -0.78 -0.49 63.33 64.58 1.25 384 20.00 0.71 7.50 1/1/2010 2:00:00 AM -0.78 -0.49 63.37 64.87 1.5 384 24.00 0.71 9.00 1/1/2010 3:00:00 AM -0.78 -0.49 63.99 65.07 1.08 384 17.28 0.71 6.48 1/1/2010 4:00:00 AM -0.78 -0.49 64.16 65.67 1.51 384 24.16 0.71 9.06 1/1/2010 5:00:00 AM -0.78 -0.49 64.53 65.67 1.14 384 18.24 0.71 6.84 Figure 139: Snapshot of Step-1 Slope Study Spreadsheet Figure 140: Monthly Chiller Consumption (Step-1) 143 Once the kW consumtion per hour was calculated, pivot table was used to create a graph of monthly electrical consumption of chiller. This was more accurate than the using a constant efficiency (kW/ton) of chiller but still not accurate enough to predict the reality. 8.1.4.2. Step 2: Exact Curve On the second step, kW/ton value that was been used for all the calculations was not considered directly but indirectly. The curve value was embedded in the kW column itself. That column acted as ‘y’ of the quadratic equation and tons as ‘x’. Date Time VKC_Chwp 3Amps VKC_Chwp 2Amps VKC_ComChw SupTemp VKC_ComChw RetTemp Delta-T gpm Tons of Cooling kW by Chiller - Chiller Curve 1/1/2010 12:00:00 AM -0.78 -0.49 62.57 64.07 1.5 384 24.00 34.78 1/1/2010 1:00:00 AM -0.78 -0.49 63.33 64.58 1.25 384 20.00 35.45 1/1/2010 2:00:00 AM -0.78 -0.49 63.37 64.87 1.5 384 24.00 34.78 1/1/2010 3:00:00 AM -0.78 -0.49 63.99 65.07 1.08 384 17.28 36.01 1/1/2010 4:00:00 AM -0.78 -0.49 64.16 65.67 1.51 384 24.16 34.75 Figure 141: Snapshot of Step-2 Exact Curve Spreadsheet This proved to be a much more accurate step as the part load curve was fully integrated in the calculation process. The monthly electrical consumption of chiller was then plotted to get a visual sense. Figure 142: Monthly Chiller Curve Based on Exact Curve 144 Even though everything was accurate, there were some questions arising on the data. The cycle of chiller consumption was not visible. It looked like the chiller was working everyday which shouldn’t be the case in reality in climate like Los Angeles. The expected difference in January and September chilled water consumption was not visible. This created doubt that there is something else being overlooked. 8.1.4.3. Step 3: Exact Curve with Proper Amps Once the data was accessed again, it was realized that another very important parameter was overlooked. If the Chilled water Amps were positive, then only chilled water was being provided. In all the previous cases, the tons were converted to KW whether or not the Amps were positive or negative. These missing links lead to higher consumption of electricity which was not the case in reality. Figure 143: Snapshot of Step-3 Exact Curve with Proper Amps Spreadsheet There were a lot of instances as even described above that the kW consumed by Chiller was actually ‘0’ which were making a lot of difference. Finally, a monthly consumption graph was plotted to see the pattern using the pivot table. 145 Figure 144: Monthly Chiller Consumption with Correct Curve and Amps This time the graph pattern looked correct. There was enough difference in the winter and summer months and looked accurate. 8.1.4.4. Combined Process of finding actual chiller consumption Figure 145: Chiller Energy Consumption Estimation Process 146 All the process of calculating actual chiller electrical consumption was plotted together to see the pattern change and the change brought by each step. The electrical consumption that was calculated initially using a constant efficiency of chiller was quite high. The part load curve predicted even more the efficiency dropped and the chiller was not performing at the optimal efficiency. However, while using the slope of curve it was more near reality. Finally after correcting the Amps, the profile as well as the amount of energy consumed looked perfect. 8.1.5. Calibrating the Chiller Once the actual consumption of the chiller was calculated accurately, the next step was to accurately model the chiller in Design Builder. 8.1.5.1. Part Load Curves The part load curves as obtained from Trane and used in calculations discussed above were entered in Design Builder. The coefficients and range was accurately entered along with COP, entering condenser fluid temperature and leaving chilled water temperatures. 8.1.5.2. Control System – Sequential/Uniform The controls of both chillers were kept sequential as operated in the VKC. First range is set as minimum of zero and maximum of 7,00,000 Btuh in which only first chiller is working. The second range is set as minimum of 7,00,000 Btuh and maximum of infinity in which both chillers are working in parallel. 8.1.5.3. Identifying Factors affecting Chiller energy consumption An experimental model was made in detailed mode to understand the effects of various inputs on the chiller consumption which eventually helped in calibrating the VKC model. The details of the runs are described below along with observations. 147 Table 16: Description of Chiller Experiments Run‐1 Run‐2 Run‐3 Run‐4 Run‐5 Run‐6 Run‐7 Cooling SP deccreased from 70 to 72 Fans, Pumps, Chiller, Heating, C.T. Reduced Chiller COP reduced from 5.5 to 4 Fans Same; Chiller major increase; CT inc; Pump very slight increased HVAC Economized (Enthalpy) ‐ Removed Chiller Consumption & Cooling Tower Increased, Heating Reduced Deafault Pressure Rise of Fan reduced from 2.4 to 1 System Fans Decreased, Chiller & CT slightly decreased, Heating Slightly Increased Chiller: Leaving CWT from Chiller reduced from 44 to 36; Entering Cooling Tower Fluid Temp reduced from 85 to 70 No Difference Details Comments Detailed Mode with Simple Inputs Plug Loads & Lights diffret end use even if same inputs Detailed Mode with Simple Inputs, climate LA Day lighting control were switched ON causing above diff The table and graph below shows all the end uses. Table 17: End Uses of all Chiller Experiments Second run increased the energy consumption by 15.6% as the daylight controls saved lot of energy. Third run in which the economizer was removed increased the consumption by 10%. Fourth run saved energy as the pressure rise of fan was reduced. Fifth run didn’t produce either increase or decrease in consumption. Sixth run much expectedly saved about 10% of energy when the cooling set point was decreased from 70 to 72. As the last run, chiller COP was reduced which increased the consumption by 9%. 148 These runs were then graphically plotted to understand the impact of each end use in the overall contribution to increase or decrease in energy consumption. Figure 146: Energy Consumption Comparison for all Chiller Experiments Different runs had different impact on different end uses. These can be clearly understood by the graph above. Figure 147: Energy Consumption Profiles for all Chiller Experiments 149 Run-3 in which economizer was introduced and Run-7 in which COP of chiller was changed were the runs that changed the monthly profile of chiller. Other runs just increased or decreased the electrical consumption with a constant value throughout the year. This knowledge proved vital in calibrating the Design Builder Chiller to actual chiller which would be discussed later in chapter. 8.2. Pumps The chilled water pump, condenser pump and boiler pump were exactly matched for flow rates, power consumption and head. All pumps were set to constant speed but intermittent control type. This power consumption of the pump was calculated using an online tool from engineering toolbox. (http://www.engineeringtoolbox.com/pumps-power-d_505.html) Design Builder calculates total efficiency of pump using the following formula: Total Efficiency(%)=Rated Volume Flow Rate * Rated Pump Head/Rated Power Use*100 8.3. Air Handling Units The CFM at Air Handling Units were noted from the Air Balance Report and put accurately in Design Builder with the same efficiency and Pressure Rise of fans. The default Pressure rise of fan was 2.4 which was then changed to 1 after confirming it from Facilities Management Services, USC. Carol Fern from FMS checked it from the Honeywell system to give the values. 150 Figure 148: Design Builder Inputs for Air Handling Units Economizer control type was selected to be Differential Enthalpy with outdoor dry bulb temperature low limit as 50F and high limit as 70F. This meant that the economizer would function only when the outside dry bulb temperature is between 50F and 70F. There is no heat recovery on the system. 8.4. Cooling Tower Cooling tower is located on the adjacent building to VKC which is Waite Philips Hall. The electrical consumption of cooling tower is not added in the electrical consumption for VKC. Therefore, this was left to default. This consumption is then subtracted later on from the VKC annual electrical consumption. 8.5. Heating There is district heating in VKC for both heating and domestic hot water purpose. There is a heat exchanger that converts that steam to hot water. Most efficient boiler was used to replicate district heating. 151 8.6. VKC Chiller Calibration After verification of VKC loads and correct information entered in Design Builder model related to air handing units, cooling tower, cooling coils; it was estimated that the chiller would exactly calibrate to the calculated actual consumption. It indeed was very close except one anomaly which is discussed below. 8.6.1.1. Monthly Basis Comparison Figure 149: Metered Chiller Consumption Comparison versus Model Predicted The profile of both VKC chiller’s actual electrical consumption and Design Builder predicted consumption was quite close except in the month of April. All the ranges except April were within acceptable error margin based on CV (RMSE). No acceptable reasons could be thought of this discrepancy in April. The lighting, equipment and occupancy schedules entered in Design Builder were checked for the month of April but there was no reduction of usage. This meant that this reduction is not because of internal loads. The pattern of outside temperature was then studied as discussed below. 152 8.6.1.2. Comparison to ODB temperature – Profile Matching Average Outside dry bulb temperatures on monthly and hourly scale were plotted to understand the general pattern of climate at different hours of the day and at different months. The chart was obtained from the .STAT weather file when opened in Microsoft Excel. This chart gives the average temperature per hour for all different months of 2010. The chart was color coded with blue as the coldest and red as hottest temperatures. An hourly profile of 2010 weather is shown in the picture below this chart. Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0:01‐ 1:00 54.14 54.68 56.3 55.76 59.18 63.32 65.48 65.12 65.84 64.4 54.86 53.6 1:01‐ 2:00 53.96 54.14 55.94 55.4 58.64 63.32 65.48 65.12 65.66 63.86 54.14 52.88 2:01‐ 3:00 53.24 53.78 55.22 55.22 58.46 63.32 65.48 64.94 65.3 63.5 53.6 52.34 3:01‐ 4:00 52.88 53.96 54.86 54.5 57.02 61.88 63.86 62.78 63.14 63.14 53.6 52.16 4:01‐ 5:00 52.52 53.78 54.86 55.22 59.54 63.32 64.94 64.58 64.04 63.32 53.96 51.62 5:01‐ 6:00 52.88 53.96 56.3 57.56 61.88 65.12 67.1 68 67.28 64.22 54.5 51.44 6:01‐ 7:00 54.32 55.94 60.26 60.08 64.58 67.28 69.26 71.78 71.6 66.74 58.28 53.06 7:01‐ 8:00 58.1 59.36 63.68 63.32 66.92 69.62 72.5 75.02 75.02 69.62 62.06 56.12 8:01‐ 9:00 62.42 61.52 66.02 65.48 69.62 71.96 75.02 78.26 78.08 71.42 64.58 59.54 9:01‐10:00 65.12 64.04 68.36 66.02 69.62 71.96 74.12 77.9 78.98 73.04 67.46 61.7 10:01‐11:00 66.2 65.48 69.08 67.82 70.52 73.76 76.28 79.52 80.06 73.94 68.72 63.32 11:01‐12:00 67.1 65.84 69.44 67.64 71.42 73.76 76.1 79.34 80.24 74.48 69.26 64.22 12:01‐13:00 67.82 65.84 69.44 66.92 70.7 73.94 76.28 79.16 80.42 74.12 69.26 64.76 13:01‐14:00 67.28 65.48 69.08 66.38 70.34 73.76 75.92 78.62 79.16 73.22 68.72 64.22 14:01‐15:00 66.02 64.4 68 65.48 69.62 73.4 75.38 78.08 78.26 71.6 67.1 62.96 15:01‐16:00 63.32 62.24 65.66 62.96 66.56 70.16 71.42 74.3 74.3 69.44 64.04 60.8 16:01‐17:00 60.62 60.44 63.86 61.7 65.48 68.36 70.7 71.78 72.14 67.82 62.42 59 17:01‐18:00 59.36 59.18 61.52 60.44 63.14 66.38 68.54 69.08 70.52 66.92 61.16 57.74 18:01‐19:00 58.1 58.46 61.16 59.18 62.24 65.12 67.28 67.64 69.8 66.38 60.08 56.48 19:01‐20:00 57.38 57.74 60.08 58.82 61.34 64.76 66.92 66.74 68.54 66.02 59.18 55.76 20:01‐21:00 57.02 56.84 58.82 58.46 60.98 64.58 66.56 66.38 68.18 65.3 57.74 55.22 21:01‐22:00 56.3 56.48 58.82 57.74 60.44 63.86 65.66 65.48 66.92 64.94 57.74 55.22 22:01‐23:00 55.4 55.94 58.1 57.02 59.72 63.68 65.66 65.66 66.92 64.76 56.84 54.68 23:01‐24:00 54.68 55.4 57.02 56.66 59.54 63.32 65.66 65.48 66.02 64.58 55.4 53.96 Figure 150: Hourly Profile of 2010 Weather Y-Axis has hourly times whereas X-Axis has monthly information. These two axis when read together gives a rich knowledge of the hottest month and hour. 153 Figure 151: 2010 Hourly Weather Data It was clear from these charts that average temperture is higher in March and May as compared to April. End of september had the highest temperature. The profile of Design Builder predicted chiller consumption was then compared to the profile of Outside Dry Bulb temperature as shown below. Figure 152: Design Builder Predicted Chiller Consumption and Monthly Outside Dry Bulb Temperature Both the profiles exactly matched. The average monthly temperature increased in March, reduced in April and then increased from May onwards. The electrical consumption predited by Design Builder is also following the same path. 154 Figure 153: Design Builder Predicted Chiller Consumption and Hourly Outside Dry Bulb Temperature The average daily comparison further confirmed that ODB and chiller consumption has a similar relationship. The red vertical line in the above chart show the starting and ending date of Daylight Saving Time. After all these observation, it was then inferred that the Design Builder predicted electrical consumption profile is accurate. There must have been more cooling during that month in VKC than required or the economizer was not functioning to its optimum capacity. The chiller model was accepted to be calibrated. 8.7. Full Building Calibration Process All the adjustments to the model discussed earlier in the chapter or calibration of chiller were not done at once. There were more than 60 annual simulation runs that were done to reach the calibrated model. Former part of runs was done with ‘compact HVAC’ mode and latter with ‘Detailed HVAC’ mode. It was a constant process of learning and improvement. All the runs created cannot be described here, therefore only select models that really made a difference in the path of calibration are discussed. The runs 155 shown below are clubbed together to show a significant change in a single step of run which was not how it was calibrated. A lot of single changes were made to understand the impact of each change. But for clarity and succinctness in the Thesis they are combined together. However, the time spent on simulating these models shouldn’t be undermined. Design Builder is based on Energy Plus and Thermal Balance Method which is really time intensive per full year simulation. In addition to time, there is a lot of frustration that a modeler has to go through in order to make the model behave the way modeler wants it to behave. 156 8.7.1. RUN-1: Base Model + Modifications in Compact HVAC mode These results are from the baseline model as discussed in Chapter 6 with some modifications done in default HVAC system under ‘Compact Mode’. Figure 154: DB vs VKC Electrical Consumption VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 107513.13 4.02 feb'10 91999.39 108621.63 14.90 mar'10 108408.35 125725.91 15.52 apr'10 110059.49 114747.25 4.20 may'10 113358.07 112765.04 0.53 jun'10 103089.41 104093.29 0.90 jul'10 113854.01 108807.71 4.52 aug'10 119151.50 117296.40 1.66 sep'10 124537.59 135307.56 9.65 oct'10 139019.75 135183.88 3.44 nov'10 118898.35 119135.02 0.21 dec'10 93709.65 98984.55 4.73 Total 1339111.64 1388181.36 Electrical Comparison Figure 155: DB vs VKC Electrical Consumption The results were quite close but the HVAC system was not detailed enough to depict the reality. It was just a single default constant volume dual duct system serving full VKC. VKC Building (kBtu) DB Model (kBtu) CV(RMSE) jan'10 459253.29 73177.46 149.21 feb'10 207718.03 46934.22 62.14 mar'10 383274.08 30892.70 136.19 apr'10 348558.03 31849.27 122.40 may'10 191202.99 23123.79 64.96 jun'10 127401.98 14921.08 43.47 jul'10 118808.11 13604.94 40.66 aug'10 186130.48 10420.60 67.91 sep'10 213447.34 13226.46 77.38 oct'10 255229.75 22839.34 89.82 nov'10 310264.78 45318.41 102.40 dec'10 303582.29 95845.57 80.29 Gas Comparison Figure 157: DB vs VKC Gas Consumption Gas comparisons were awry with the error varying from 40% to 150%. Figure 158: Design Builder End Use Figure 159: DB vs Measured Electrical End-Use Figure 156: DB vs VKC Gas Consumption 157 8.7.2. RUN-2 The model was changed to default Design Builder ‘Detailed Mode’ of HVAC system as discussed in Chapter-7. Four AHU’s were modeled as per original HVAC VKC plan. Figure 160: DB vs VKC Electrical Consumption VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 142465.59 35.34 feb'10 91999.39 138041.18 41.26 mar'10 108408.35 158505.74 44.89 apr'10 110059.49 146939.04 33.05 may'10 113358.07 149049.77 31.98 jun'10 103089.41 146467.56 38.87 jul'10 113854.01 154326.58 36.27 aug'10 119151.50 161121.86 37.61 sep'10 124537.59 171474.06 42.06 oct'10 139019.75 171326.58 28.95 nov'10 118898.35 151164.65 28.91 dec'10 93709.65 133314.13 35.49 Total 1339111.64 1824196.75 Electrical Comparison Figure 161: DB vs VKC Electrical Consumption The electrical consumption went quite high as compared to VKC consumption. The error which was within 10% was now ranging from 28% to 48% error. VKC Building (kBtu) DB Model (kBtu) CV(RMSE) jan'10 459253.29 78131.12 147.30 feb'10 207718.03 48598.89 61.50 mar'10 383274.08 30345.53 136.40 apr'10 348558.03 32984.02 121.97 may'10 191202.99 26547.21 63.64 jun'10 127401.98 18551.86 42.07 jul'10 118808.11 15978.71 39.74 aug'10 186130.48 13234.22 66.82 sep'10 213447.34 10317.04 78.51 oct'10 255229.75 20172.49 90.85 nov'10 310264.78 48876.37 101.02 dec'10 303582.29 101303.40 78.18 Total 3104871.15 445040.86 Gas Comparison Figure 163: DB vs VKC Gas Consumption Gas comparisons were still awry with the error varying from 40% to 150%. Ventilation became the predominant end-use and was main anomaly Figure 164: Design Builder End Use Figure 165: DB vs Measured Electrical End-Use Figure 162: DB vs VKC Gas Consumption 158 8.7.3. RUN-3 Exact details of pumps were inserted in Design Builder model. Pumps were made intermittent with a defined pump schedule. Figure 166: DB vs VKC Electrical Consumption VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 127691.21 22.10 feb'10 91999.39 124854.16 29.44 mar'10 108408.35 143983.79 31.88 apr'10 110059.49 133248.92 20.78 may'10 113358.07 134015.83 18.51 jun'10 103089.41 130788.36 24.82 jul'10 113854.01 138289.65 21.90 aug'10 119151.50 143478.75 21.80 sep'10 124537.59 154029.37 26.43 oct'10 139019.75 156205.42 15.40 nov'10 118898.35 136216.76 15.52 dec'10 93709.65 116822.68 20.71 Total 1339111.64 1639624.91 Electrical Comparison Figure 167: DB vs VKC Electrical Consumption The electrical consumption reduced and looked much closer to metered value with maximum error of 32%. But more work need to be done to bring it under 15%. VKC Building (kBtu) DB Model (kBtu) CV(RMSE) jan'10 459253.29 82455.40 145.63 feb'10 207718.03 52002.59 60.18 mar'10 383274.08 33970.61 135.00 apr'10 348558.03 36982.03 120.42 may'10 191202.99 31076.53 61.89 jun'10 127401.98 23077.81 40.32 jul'10 118808.11 20708.69 37.91 aug'10 186130.48 17972.03 64.99 sep'10 213447.34 13432.85 77.30 oct'10 255229.75 24641.11 89.12 nov'10 310264.78 52366.02 99.68 dec'10 303582.29 107080.80 75.95 Total 3104871.15 495766.47 Gas Comparison Figure 169: DB vs VKC Gas Consumption Gas consumption remained unaltered. Overall ventilation end use decreased from 37% to 31% which was a positive sign. Figure 170: Design Builder End Use Figure 171: DB vs Measured Electrical End-Use Figure 168: DB vs VKC Gas Consumption 159 8.7.4. RUN-4 Economizer with Differential Enthalpy was added in all AHU’s. AHU default fan ‘Pressure Rise’ was reduced from 2.5 to 2 and 1 for supply and return fan respectively. Figure 172: DB vs VKC Electrical Consumption VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 110687.66 6.87 feb'10 91999.39 109148.14 15.37 mar'10 108408.35 127862.88 17.43 apr'10 110059.49 117607.62 6.76 may'10 113358.07 121599.48 7.39 jun'10 103089.41 120994.33 16.04 jul'10 113854.01 128445.18 13.08 aug'10 119151.50 133223.47 12.61 sep'10 124537.59 143656.44 17.13 oct'10 139019.75 145868.40 6.14 nov'10 118898.35 120126.72 1.10 dec'10 93709.65 98465.69 4.26 Total 1339111.64 1477686.01 Electrical Comparison Figure 173: DB vs VKC Electrical Consumption This proved to be a very vital step in bringing close the predicted and metered electrical consumption. Only Feb, Mar, June and Sep were slightly out of 15% error margin. VKC Building (kBtu) DB Model (kBtu) CV(RMSE) jan'10 459253.29 83073.59 145.39 feb'10 207718.03 52328.08 60.06 mar'10 383274.08 34087.56 134.96 apr'10 348558.03 37129.17 120.36 may'10 191202.99 31095.14 61.88 jun'10 127401.98 23084.23 40.32 jul'10 118808.11 20696.37 37.92 aug'10 186130.48 17979.31 64.99 sep'10 213447.34 13414.87 77.31 oct'10 255229.75 24611.98 89.13 nov'10 310264.78 52868.38 99.48 dec'10 303582.29 107966.10 75.60 Total 3104871.15 498334.78 Gas Comparison Figure 175: DB vs VKC Gas Consumption Gas consumption continued to be awry. Ventilation end use reduced even further bringing the model close to calibration. Figure 176: Design Builder End Use Figure 177: DB vs Measured Electrical End-Use Figure 174: DB vs VKC Gas Consumption 160 8.7.5. RUN-5 Exact specification of chiller was inserted with accurate tonnage, part load curve, COP and controls of chiller. Figure 178: DB vs VKC Electrical Consumption Figure 179: DB vs VKC Electrical Consumption The Design Builder looked quite calibrated to the metered value with only one month (September) slightly out of ASHRAE defined 15% error margin. Figure 181: DB vs VKC Gas Consumption Gas consumption slightly increased bringing one step closer to calibrated gas model. Cooling load slightly reduced and heating increased slightly. Figure 182: Design Builder End Use Figure 183: DB vs Measured Electrical End-Use Figure 180: DB vs VKC Gas Consumption 161 8.7.6. RUN-6 Precise Design Supply Air Flow rates taken from Air Balance report for each AHU were entered; KW of supply and return fans was matched; corridors LPD were adjusted. Figure 184: DB vs VKC Electrical Consumption Figure 185: DB vs VKC Electrical Consumption The September month which was initially out of sync seemed to be within a range. However, October and November were slightly out of 15% range. Figure 187: DB vs VKC Gas Consumption Gas consumption increased slightly more bringing it closer to metered consumption. Cooling and ventilation end uses reduced slightly where as heating increased. Figure 188: Design Builder End Use Figure 189: DB vs Measured Electrical End-Use Figure 186: DB vs VKC Gas Consumption 162 8.7.7. RUN-7 Chiller controls and minimum outside air requirement were adjusted; cooling set point was set as 70F; cooling coil inlet and outlet water temperature were set as 45F & 55F Figure 190: DB vs VKC Electrical Consumption Figure 191: DB vs VKC Electrical Consumption The electrical consumption in general increased but still very much within the ASHRAE defined 15% error margin Figure 193: DB vs VKC Gas Consumption Gas consumption was almost same as the previous run. Surprisingly, cooling tower consumption increased and chiller consumption reduced. Figure 194: Design Builder End Use Figure 195: DB vs Measured Electrical End-Use Figure 192: DB vs VKC Gas Consumption 163 8.7.8. RUN-8 Set Point Manager was adjusted to Warmest option; model infiltration set to 0.7 ACH; Economizer ODB low and high limit were set; Domestic Hot water values were adjusted. Figure 196: DB vs VKC Electrical Consumption Figure 197: DB vs VKC Electrical Consumption These fine tunings brought the model well within ASHRAE defined 15% error margin for all the months of the year. Figure 199: DB vs VKC Gas Consumption Design Builder predicted Gas consumption was still out of sync. End-uses looks quite decent for an institutional building. Figure 200: Design Builder End Use Figure 201: DB vs Measured Electrical End-Use Figure 198: DB vs VKC Gas Consumption 164 8.7.9. Combined Runs The dotted black line in the graphs shown below is the actual metered consumption and solid black line is of the run of almost calibrated model. Figure 202: Combined Electrical Calibration Runs Figure 203: Combined Gas Calibration Runs This graph above shows the electrical & gas profile estimated by DB for all runs. 165 CHAPTER - 9: CALIBRATED MODEL & GAS ISSUES This chapter first describes annual, monthly, daily and hourly electrical and gas consumptions along with end-uses, system loads and internal gains of the calibrated model. Afterwards this chapter focuses on unaccomplished Gas calibration and looks into different possibilities that could be inferred out of this situation and possible verification of results. 166 9.1. Calibrated Model The outputs of calibrated model are shown below in monthly, daily and hourly profile. 9.1.1. Design Builder Outputs – Monthly Profile There were monthly profiles that were plotted from Design Builder for different parameters. These parameters were internal gains, system loads, fuel breakdown, total fuel consumption, fabric & ventilation and CO2 production. These graphs give a clear idea how the calibrated model is behaving. Figure 204: Internal Gains (Monthly) Figure 205: System Loads (Monthly) 167 Figure 206: Fuel Breakdown Figure 207: Total Fuel Consumption Figure 208: Fabric & Ventilation 168 Figure 209: CO2 Production (Monthly) 9.1.2. Design Builder Outputs – Daily Profile There were daily profiles that were plotted from Design Builder in addition to monthly profiles for certain parameters. These parameters were internal gains, system loads, fuel breakdown, total fuel consumption, fabric & ventilation and CO2 production. These graphs give a clear idea how the calibrated model is behaving. Figure 210: Internal Gains 169 Figure 211: System Loads Figure 212: Fuel Breakdown Figure 213: Total Fuel Consumption 170 Figure 214: Fabric and Ventilation Figure 215: Inside and Outside Temperatures Figure 216: CO2 Production 171 9.1.3. Design Builder Outputs – Hourly Profile These charts could not be generated yet as Design Builder crashes all the time hourly reports were requested. This is one limitation that is realized in Design Builder. The building modeled is huge with over 50 zones. The design builder takes over 6 hours to simulate once and requires very high RAM in order to process such a huge model. 9.2. Comparison to VKC Model The calibrated model had two facets. The electrical consumption predicted by Design Builder was calibrated to the actual usage within 10% error for all the months and with annual percentage difference of only 2.45%. However, the calibration of gas consumption predicted by Design Builder to that of VKC actual usage was unaccomplished. Figure 217: DB vs VKC predicted Electrical Consumption 172 VKC Building (KWh) DB Model (KWh) CV(RMSE) jan'10 103026.08 97882.31 4.61 feb'10 91999.39 98758.99 6.06 mar'10 108408.35 116514.88 7.26 apr'10 110059.49 105602.04 3.99 may'10 113358.07 103786.11 8.58 jun'10 103089.41 102989.80 0.09 jul'10 113854.01 108332.80 4.95 aug'10 119151.50 116962.61 1.96 sep'10 124537.59 129367.31 4.33 oct'10 139019.75 128191.38 9.70 nov'10 118898.35 110178.81 7.81 dec'10 93709.65 87794.38 5.30 Total 1339111.64 1306361.42 2.45% Electrical Comparison Figure 218: DB vs VKC predicted Electrical Consumption The electrical consumption predicted by Design Builder matches perfectly with that of metered value. All the monthly error values fall well within ASHRAE defined 15% error margin for a calibrated model and with only 2.5% annual percentile difference. The maximum monthly error is 9.7% in October 2010. Figure 219: DB vs VKC predicted Gas Consumption 173 VKC Building (kBtu) DB Model (kBtu) CV(RMSE) jan'10 459253.29 119880.82 131.16 feb'10 207718.03 74700.11 51.41 mar'10 383274.08 45800.31 130.43 apr'10 348558.03 42521.54 118.28 may'10 191202.99 34351.52 60.62 jun'10 127401.98 30387.54 37.50 jul'10 118808.11 27496.82 35.29 aug'10 186130.48 27907.19 61.15 sep'10 213447.34 21735.23 74.09 oct'10 255229.75 28225.28 87.73 nov'10 310264.78 78407.96 89.61 dec'10 303582.29 167463.56 52.61 Total 3104871.15 698877.88 77.49% Gas Comparison Figure 220: DB vs VKC predicted Electrical Consumption Gas consumption throughout the calibration process was extremely awry. The gas consumption never seemed to fall within reasonable limits of calibration. Figure 221: EUI Comparison 174 Electrical EUI for the VKC building was 46.75 kBtu/sft-yr and that predicted by Design Builder is 46.78 kBtu/sft-yr with a difference of only 0.03 kBtu/sft-yr. However, the gas EUI is completely off. The Gas EUI of VKC building is 31.77 kBtu/sft-yr whereas Design Builder predicts only 7.33 kBtu/sft-yr with a difference of 24.44 kBtu/sft-yr. Figure 222: Calibrated Model End Use The overall end use for this building looks very balanced and accurate for an institutional building at Los Angeles. As an end use cooling contributes 12%, heating 13%, ventilation 21%, water heating 2%, plug loads 21% and lighting as 31%. Heating end use which contributes to 13% of overall energy consumption looks fairly accurate but when compared to measure gas consumption, it is estimated at least three times less. 175 This graph clearly illustrates contribution of overall end uses for total electrical consumption. Cooling is the biggest variable brining the change in the profile of electrical consumption. Figure 224: Calibrated Model Gas End Use Figure 223: Calibrated Model Electrical End Use 176 However, gas side of the equation is not at all calibrated. The gas consumption even if forms 13% of total end use appears to be way off when compared to metered consumption. This matter is looked into in the section below. 9.3. Gas Issues Electrical consumption of Design Builder was perfectly calibrated to actual VKC electrical consumption. However, the gas consumption was still way off than actual consumption. Even after trying all the possible ways, the Design Builder predicted consumption was continuously a lot less than actual consumption. This part of chapter looks into different possibilities that could be inferred out of this situation and possible verification of results. 9.3.1. Full VKC Envelope Heating Load Calculations The first logical way to verify the gas consumption predicted by Design Builder was to verify the peak loads that it calculates during winter design day. In order to verify these values, heat loss calculations were done for the full VKC envelope. 9.3.1.1. Manual Heat Loss Calculation (Spreadsheet) Heat Loss through the VKC envelope was calculated at the steady state using typical Heat Loss equation. ASHRAE defined outside dry bulb temperature was used as ambient temperatures. Heat loss equation used is as follows: Heat Loss (Q) = U-Value (U) x Area (A) x Difference in Temperature ( ∆T) Q = U x A x ∆T (Grondzik et al. 2011) 177 This equation was used to calculate heat loss through walls, windows, roofs and basement floor. Additional load of Ventilation and Infiltration was calculated separately. The ventilation rate was defined as air changes per square foot instead of basing it on number of occupancy. Occupancy varied with different function of space and was difficult to replicate same in the excel sheet. Therefore, Ventilation rate was kept as 0.5 ACH/sft and infiltration of the building was kept ‘0’ for simplification purpose of comparison. Heat loss because of ventilation was calculated based on following equation: Heat Loss (Q) = 1.08 x CFM x Difference in Temperature ( ΔT) Q = 1.08 x CFM x ΔT (Grondzik et al. 2011) The internal thermostat setting was kept as 68F and ASHRAE based outside dry bulb (ODB) was kept as 43.9F which made the difference in temperature to be 24.1F. Ground Temperature was kept as 57.2F for the whole year. 178 Table 18: Manual Heat Loss Calculations Walls Area (sft) U‐Value Delta THeat Loss (A*U*Delta‐T) West Wing 12954 0.288 24.1 89911 East Wing 12954 0.288 24.1 89911 North Wing 9528 0.288 24.1 66132 Basement (adj Ground) 6477 0.242 10.8 16928 Basement (adj Non AC) 1828 0.288 10.8 5686 268568 Windows Area (sft) U‐Value Delta THeat Loss (A*U*Delta‐T) West Wing 2214 1.018 24.1 54318 East Wing 2214 1.018 24.1 54318 North Wing 2181 1.018 24.1 53508 Basement (Courtyard) 2902 1.018 24.1 71197 233341 Roof Area (sft) U‐Value Delta THeat Loss (A*U*Delta‐T) West Wing 7938 0.239 24.1 45722 East Wing 7938 0.239 24.1 45722 North Wing 4290 0.239 24.1 24710 116154 Ground Floor Area (sft) U‐Value Delta THeat Loss (A*U*Delta‐T) Basement (Except Non AC) 28973 0.349 10.8 109205 109205 Ventilation/Infiltration ASHRAE 62.2 CFM = (Occ * 7.5cfm/occ) + (0.01cfm/sft * CFA) Occupancy (class/off/corridor) 15200 1900 Heat Loss (Q) = 1.08 CFM ΔT 395625.6 Option‐2 Thermostat Setting (F 68 CFM = (Area * Vent/sft) Ashrae ODB (F) 43.9 CFM = 95276*0.5 Delta T 24.1 47638 Heat Loss (Q) = 1.08 CFM ΔT ground temperature 57.2 1239921.9 Total Heat Loss (Btu/hr) 1967190 Total Heat Loss (kBtu/hr) 1967 Heat Loss Predicted by DB 1812 %age difference to Manual Calcs ‐7.89% VKC ‐ Heat Loss Calculations Delta T (F) 179 9.3.1.2. Design Builder Predicted Heat Loss Calculation The Design Builder predicted loads are shown below. Figure 225: Design Builder Predicted Heat Loss Estimation (Graphical) Temperature and heat loss graph shows the amount of heat loss by individual components. Total heat loss predicted by Design Builder is 1812 kBtu-hr. Figure 226: Design Builder Predicted Heat Loss Estimation (Data) 180 Temperature and heat loss graph shows the amount of heat loss by individual components. Total heat loss predicted by Design Builder is 1812 kBtu-hr. 9.3.1.3. Comparison of Manually Calculated and Design Builder Heat Loss Design Builder predicted design day peak loads when compared to the manual calculations, there was only 7.89% difference. Table 19: Heat Loss (By Component) Comparison b/w Manual Calculations & DB The loads were then compared on individual component basis provided more clarity to the differences in question. Design Builder predicted heat loss were 15% less for walls, 37% less for windows, 41% less for ground floor but 17% more for roof. There was higher percentage of differences on individual components even if overall percentage difference is only 8%. These differences are primarily because Design Builder uses algorithms used to calculate dynamic heat flows and thermal lags from individual building components. On the other hand, manual steady state heat loss calculations are over simplified. However, this 8% difference doesn’t explain such a mammoth difference between Design Builder predicted gas consumption and metered value. In fact, Design Builder might be predicting the loads more accurately than manual calculations. 181 This clearly meant that Design Builder is accurately calculating the loads and there wasn’t any error in some inputs by the author. Even though individual heat loss components had greater discrepancy but overall heat losses were similar. Once the loads were verified, the doubts were casted on the accuracy of VKC actual gas consumption instead of Design Builder predicted gas consumption. 9.3.2. eQuest – Parallel Research Results In order to verify the Design Builder outputs, another comparison was done. This time the monthly gas consumption was compared instead of only loads. There could have been a discrepancy in calculating the final gas consumption even if the loads were similar. This was done through comparing Design Builder Gas Consumption to that of eQuest predicted gas consumption. This comparison was possible because of another parallel research that was been conducted for a Research Paper submittal at SimBuild 2012. This research paper was co-authored with Andrea Martinez, Karen Kensek and Marc Schiler. The title of the paper is “Comparison Of Two Different Simulation Programs While Calibrating Same Building.” 9.3.2.1. All Inputs Match Walls (sub-grade and exposed), slabs (sub-grade and internal), roof, and finishing materials were matched using the exact U-values and dimensions in both software programs. The glass properties like visible light transmittance, U-value and SHGC were also entered in both eQuest and Design Builder. HVAC systems were not auto sized but the exact description was input manually. The CFM at Air Handling Units as noted from the Air Balance Report was put in accurately in both simulation softwares with the same efficiency and Pressure Rise of fans. The Fan 182 Curve was matched within both softwares. Economizer control type was selected to be Differential Enthalpy with Outdoor Dry Bulb temperature low limit as 50 and high limit as 70. Part load curves obtained from Trane for that specific chiller model and same coefficients were inserted in both softwares. The controls of both chillers were kept sequential as in the VKC. The chilled water pump, condenser pump and boiler pump were exactly matched for flow rates, power consumption and head. All pumps were set to constant speed but intermittent control type. Same weather file and ASHRAE handbook design conditions were used in both software programs. All schedules for occupancy, lighting, and equipment were also matched. 9.3.2.2. Almost Same Gas Prediction Annual gas predicted by both Design Builder and eQuest was far less than the real annual consumption in the building. Table 20: Metered, Design Builder & eQuest predicted Gas Consumption eQuest predicted slightly higher gas consumption than Design Builder but was a very close match to Design Builder predicted consumption. Predictions from both softwares 183 highly match in profile and total annual prediction. There exist 15% of difference in annual prediction between Design Builder and eQuest. Comparing these two softwares, it became highly probable that the measured data from the building is erroneous. 9.4. Conclusions The loads predicted by Design Builder matched with manual calculations. Two different simulation softwares predicted almost same gas consumptions. Based on the discoveries made above several conclusions could be made. The author identified three such conclusions that are discussed below. 9.4.1. Wrong Model that is used by FMS As discussed earlier in thesis in section 2.6 that there was no proper way of measurement of gas consumption at VKC. There is a campus steam that is supplied to this building. However, instead of measuring the amount of steam at the building, supplied Gas was measured with a common shared meter by three buildings. The gas usage was then allocated to all four buildings based on a model created on assumptions by Facilities Management Services. Consequently, one of the reasons for such a discrepancy might be the model that was generated is erroneous. It is also quite probable that one of the four buildings in the grouped measurement had an anomalous function, system or efficiency. Not only was the scale of the measured consumption unlikely, but the profile did not match the student occupancy or weather profile. 184 9.4.2. Over excessive heating The second possible reasoning that could be sought was in the operations of the building. There could be a possibility of overheating the space or use of heating system during unoccupied hours. There could have been a lapse in co-ordination and the heating system could be switched on throughout unoccupied hours irrespective of definite schedule. 9.4.3. Building is losing a lot of heat – Commissioning Proposed The third possible reasoning could be that the building is losing a lot of heat either by infiltration or duct leakages. The current system in the building has seen so many changes and has a complex HVAC distribution system with both constant volume dual duct and VAV on the same AHU. There is a significant possibility that the heat is being lost in the distribution system. Building commissioning was proposed to the Facility Management Services for this building. 185 CHAPTER - 10: ENERGY EFFICIENCY MEASURES Energy Efficiency Measures (EEM) also termed as Energy Conservation Measures are the possible ways in which the energy consumption of the building can be reduced. These measures are first explored independently to understand their effectiveness followed by grouping them together to see the overall impact and head towards Net Zero Energy. This chapter explores independent effectiveness of all EEM’s 186 10.1. Pre-M&V Plan A Pre-M&V plan was created in which probable list of iterations that could be done for VKC were mentioned. Figure 227: Calibrated Model End Use It is understood by the end use of the calibrated model that lighting and plug loads are the prime end uses followed by heating, cooling, pumps and fans. Domestic hot water, cooling tower and exterior lighting are very small part of equation. The EEMs should target the biggest portion of end use first and then go in hierarchical order of maximum consumption. The EEMs were broadly divided in three main categories, namely lighting, envelope and HVAC. These three categories are discussed in detail below. However, there were some EEMs that were part of Pre M&V plan but were not modeled due to constraints in the 187 simulation tool. These EEMs were phase change materials, water/ground source heat pumps, direct/indirect evaporative coolers, 4 pipe chilled beams in offices, variable refrigerant flow with water box technology. 10.2. Lighting EEMs Lighting is the highest contributor in the energy consumption for VKC. Keeping this in mind aggressive measures were taken in reduction of lighting consumption. The EEMs performed are as follows: EEM 1: Lighting Controls – Continuous Dimming The design light levels for classroom, offices, computer labs were kept at 500 Lux where as for corridors and restrooms as 100 Lux. These values were taken from IES Lighting Handbook - 8th Edition. Lighting controls were adjusted to continuous dimming to save energy as the first lighting EEM. EEM 2: Lighting Controls – 3 Stepped Keeping the same design conditions as first lighting EEM, the lighting controls were modified to 3 stepped. EEM 3: Energy Efficient Lighting LEDs were proposed as energy efficient lighting system. Design conditions (in Lox) were noted from IES lighting handbook. These values when converted to lumens per square feet is 46.45 lm/sft (500 Lux) for classrooms, offices and computer labs whereas 9.29 lm/sft for corridors and restrooms. 188 The EEM is proposed using Philips L Prize LED light which has an efficacy of 94 lumens/watt and over 25,000 hour life. (http://www.sacbee.com/2012/03/09/ 4324483/the-award-winning-philips-l-prize.html). The loss due to fixture inefficiency in estimated and final fixture efficacy is taken as 0.70 lm/watt. This when transformed into Lighting Power Density (LPD) is 0.66 W/sft for classrooms and 0.13 W/sft for corridors. EEM 4: Exterior Lights override off in day time The exterior lights follow a fixed schedule in addition to override settings. The lights are automatically turned off if there is sunlight even if the schedule is to be on at that time. EEM 5: Skylights in corridor spaces The skylights were added to the third floor corridor spaces in addition to photo sensors. The skylights were kept as 3% of total corridor roof area. 189 10.2.1. EEM-1: Lighting Controls-Continuous Dimming First EEM was to set lighting controls in classrooms and offices as continuous dimming. Figure 228: Electrical Comparison Figure 229: Gas Comparison Annual reduction was 13.6% for electrical consumption and 0.65% for gas consumption. Figure 230: End Use Electrical Comparison Figure 231: End Use Gas Comparison Lighting end use reduced by 37%, cooling by 8%, heating by 2%, fans by 6%, pumps by 2% and cooling tower by 15%. The EUI reduced from 51.26 to 45.17 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐1 810798 215211 1014873 559795 606585 351657 604155 82047 59118 % change 37% 0% 0% 8% 2% 6% 1% 0% 15% Figure 232: EEM predicted end use Figure 233: EUI Comparison b/w EEM & Calibrated 190 10.2.2. EEM-2: Lighting Controls-3 Stepped Lighting controls in classrooms and offices were set as 3-Stepped dimming system. Figure 234: Electrical Comparison Figure 235: Gas Comparison Annual reduction was 12% for electrical consumption and 1.2% for gas consumption. Figure 236: End Use Electrical Comparison Figure 237: End Use Gas Comparison Lighting end use was reduced by 32%, cooling by 8%, heating by 3%, fans by 6%, pumps by 1% and cooling tower by 14%. The EUI reduced from 51.26 to 45.83 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐2 872454 215211 1014873 565103 600639 351703 605474 82047 59967 % change 32% 0% 0% 8% 3% 6% 1% 0% 14% Figure 238: EEM predicted end use Figure 239: EUI Comparison b/w EEM & Calibrated 191 10.2.3. EEM-3: Efficient Interior Lighting LED having fixture efficacy of 0.7 lumens/sft were used Figure 240: Electrical Comparison Figure 241: Gas Comparison Annual reduction was 20.5% for electrical but 6.3% increase for gas consumption. Figure 242: End Use Electrical Comparison Figure 243: End Use Gas Comparison Lighting end use reduced by 59%, cooling by 10%, heating by (-7)%, fans by 7%, pumps by (-1)% and cooling tower by 19%. The EUI reduced from 51.26 to 42.70 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐3 529911 215211 1014873 546939 660696 345409 617444 82047 56145 % change 59% 0% 0% 10% ‐7% 7% ‐1% 0% 19% Figure 244: EEM predicted end use Figure 245: EUI Comparison b/w EEM & Calibrated 192 10.2.4. EEM-4: Efficient Interior Lighting Exterior lighting set to ‘override off’ during day time irrespective of their schedule. Figure 246: Electrical Comparison Figure 247: Gas Comparison Annual reduction was 0.5% for electrical and no change in gas consumption. Figure 248: End Use Electrical Comparison Figure 249: End Use Gas Comparison External lighting end use reduced by 7% and there was no change in rest of end uses. The EUI reduced from 51.26 to 51.10 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐4 1289741 200912 1014873 611011 616760 373375 612402 82046 69345 % change 0% 7% 0% 0% 0% 0% 0% 0% 0% Figure 250: EEM predicted end use Figure 251: EUI Comparison b/w EEM & Calibrated 193 10.3. Envelope EEMs Envelope related EEMs were done to understand the effect of envelope on overall energy consumption and possibly reduce that consumption. EEM 6: High Performance Glazing The existing single glazing with properties as VLT 0.57, SHGC 0.62 and U-Value as 1.018 Btu / °F ft 2 hr were replaced with high performing glass with VLT 0.6, SHGC 0.45 and U- Value as 0.175 Btu / °F ft 2 hr. EEM 7: High Performance Glazing In this EEM, more high performing glass was used to see the impact. The SHGC value was further reduced to 0.25 keeping VLT and U-Value same as EEM-6. EEM 8: Insulation in Roof The 5” glass fiber insulation was added to roof increasing R-Value to 22.22 Btu /°F ft 2 hr. EEM 9: Insulation in Walls The 4” glass fiber insulation was added to walls increasing R-Value to 17.9 Btu /°F ft 2 hr. EEM 10: Insulation in Walls The 2” glass fiber insulation was added to walls increasing R-Value to 10.62 Btu/°Fft 2 hr. This was done to see the impact of different R-Values on overall energy consumption. EEM 11: Air Tightness of Building The eleventh EEM was to improve the building to be more air tight and with better construction details. The air tightness of building was considered as 0.4 ACH. 194 10.3.1. EEM-6: High Performance Glazing High performing glass with VLT 0.6, SHGC 0.45 and U-Value as 0.175 Btu / °F ft 2 hr. Figure 252: Electrical Comparison Figure 253: Gas Comparison Annual reduction was 1.5% for electrical 8.2% for gas consumption. Figure 254: End Use Electrical Comparison Figure 255: End Use Gas Comparison Cooling end use reduced by 5%, heating by 9%, fans by 6%, pumps by 1% and cooling tower by 8%. The EUI reduced from 51.26 to 49.99 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐6 1289741 215211 1014873 580765 559167 350895 607117 82045 63786 % change 0% 0% 0% 5% 9% 6% 1% 0% 8% Figure 256: EEM predicted end use Figure 257: EUI Comparison b/w EEM & Calibrated 195 10.3.2. EEM-7: High Performance Glazing High performing glass with VLT 0.6, SHGC 0.25 and U-Value as 0.175 Btu / °F ft 2 hr. Figure 258: Electrical Comparison Figure 259: Gas Comparison Annual reduction was 2.1% for electrical 5% for gas consumption. Figure 260: End Use Electrical Comparison Figure 261: End Use Gas Comparison Cooling end use was reduced by 8%, heating by 6%, fans by 7%, pumps by 1% and cooling tower by 14%. The EUI reduced from 51.26 to 49.99 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐7 1289741 215211 1014873 563606 582136 348859 607488 82046 59473 % change 0% 0% 0% 8% 6% 7% 1% 0% 14% Figure 262: EEM predicted end use Figure 263: EUI Comparison b/w EEM & Calibrated 196 10.3.3. EEM-8: Insulation in Roof The 5” glass fiber insulation was added to roof increasing R-Value to 22.22 Btu /°F ft 2 hr. Figure 264: Electrical Comparison Figure 265: Gas Comparison Annual reduction was 1.1% for electrical and 5.6% for gas consumption. Figure 266: End Use Electrical Comparison Figure 267: End Use Gas Comparison Cooling end use reduced by 5%, heating by 6%, pumps by 1% and cooling tower by 8%. The EUI reduced from 51.26 to 50.36 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐8 1289741 215211 1014873 577906 577479 373244 604606 82046 63799 % change 0% 0% 0% 5% 6% 0% 1% 0% 8% Figure 268: EEM predicted end use Figure 269: EUI Comparison b/w EEM & Calibrated 197 10.3.4. EEM-9: Insulation in Walls The 4” glass fiber insulation was added to walls increasing R-Value to 17.9 Btu /°F ft 2 hr. Figure 270: Electrical Comparison Figure 271: Gas Comparison Annual electrical consumption increased by 0.1 % & gas consumption decreased by 9.9% Figure 272: End Use Electrical Comparison Figure 273: End Use Gas Comparison Heating end use reduced by 11% and pumps by 1% whereas cooling increased by (1%) and cooling tower consumption by 2%. The EUI reduced from 51.26 to 50.56 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐9 1289741 215211 1014873 616345 547371 372233 609128 82046 70642 % change 0% 0% 0% ‐1% 11% 0% 1% 0% ‐2% Figure 274: EEM predicted end use Figure 275: EUI Comparison b/w EEM & Calibrated 198 10.3.5. EEM-10: Insulation in Walls The 2” glass fiber insulation was added to walls increasing R-Value to 10.6 Btu /°F ft 2 hr. Figure 276: Electrical Comparison Figure 277: Gas Comparison Annual electrical consumption remained same but gas consumption decreased by 8.2% Figure 278: End Use Electrical Comparison Figure 279: End Use Gas Comparison Heating end use reduced by 9% but cooling tower increased by 1%. The EUI reduced from 51.26 to 50.67 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐10 1289741 215211 1014873 614054 559360 372457 609721 82045 70351 % change 0% 0% 0% 0% 9% 0% 0% 0% ‐1% Figure 280: EEM predicted end use Figure 281: EUI Comparison b/w EEM & Calibrated 199 10.3.6. EEM-11: Air Tightness The air tightness of building was reduced to 0.4 ACH. Figure 282: Electrical Comparison Figure 283: Gas Comparison Annual electrical consumption remained almost same whereas gas decreased by 14.6% Figure 284: End Use Electrical Comparison Figure 285: End Use Gas Comparison Heating end use reduced by 17% and fans by 3% whereas cooling increased by 3% and cooling tower consumption by 4%. The EUI reduced from 51.26 to 50.29 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐11 1289741 215211 1014873 629336 514672 362562 611339 82045 72313 % change 0% 0% 0% ‐3% 17% 3% 0% 0% ‐4% Figure 286: EEM predicted end use Figure 287: EUI Comparison b/w EEM & Calibrated 200 10.4. HVAC EEMs Number of HVAC related EEMs were tested ranging from simple adjustments and sequence operations to changing full HVAC systems. EEM 12: Set Point Adjustments The cooling set points were adjusted from 71F to 76F where as heating set points were adjusted from 70F to 68F. These values are still within comfort range. EEM 13: Mixed Mode Mixed mode was the thirteenth EEM in which both mechanical ventilation and natural ventilation systems were used. The ‘Calculated’ setting for natural ventilation calculations were used in Design Builder. Natural ventilation set point was kept as 72F above which the windows would open automatically. A mmaximum of 40% of each window could be opened. This opening size is controlled using modulation control with lower value as 4 and upper value as 15 and modulation factor of 0.05 (5%). This meant that if there is a difference of 4F between inside and outside temperature the opening would automatically start closing proportionally. If the difference increases to 15%, the opening of would become 5 % of original opening size. The control mode was set as ‘Temperature’ with zone heating set point as 68 and zone cooling set point as 76. EEM 14: Variable Flow Pumps The plant loop flow for chilled water, hot water and condenser loop were modified to variable volume pumps instead of the currently installed constant volume pumps. 201 EEM 15: Variable Flow Pumps The hot water loop pump was modified back to a constant volume loop whereas the chilled water and condenser loop were left variable volume. EEM 16: Night Flushing Night flushing was used as an EEM with proper schedule to exclude very hot and cold months and run between 11pm to 6am. The thermostat tolerance was kept as 1.5F outside which the system would kick in. The setting used was “cycle zone fans only” with cycling run time as 3600 sec. EEM 17: Night Flushing The schedule, thermostat tolerance and cycling run time was kept the same as the previous run whereas the setting employed was ‘cycle on any’. EEM 18: Insulation + Radiant Ceiling Insulation was added to each ceiling with an internal source of chilled water tubes. The distance between each tube was kept as 4 inches. This generated enough cooling capacity for the system to be effective. EEM 19: Displacement Ventilation In order to simulate the effect of a Displacement Ventilation system, certain adjustments were made to the HVAC settings at coil level and chiller level. Design inlet water temperature of the AHU cooling coils was kept as 55F and outlet air temperature as 63F. CFM was kept the same as before for each AHU. At chiller level ‘leaving water 202 temperature’ was set as 53F and entering fluid temperature was maintained as 75F. The space (zone) cooling set point was set as 80F. EEM 20: Heat Pumps This EEM also changed the whole HVAC system by taking out any gas related items. All heating and cooling demand is served by heat pumps individually installed in each zone. EEM 21: Heat Recovery A heat recovery wheel is installed at the AHU level in order to make use of waste heat. EEM 22: Pre Heat & Pre Cool Pre heating and pre cooling coils were added to the current system to see their effect and reduce loads on actual coils. 203 10.4.1. EEM-12: Set Point Adjustments The cooling S.P adjusted from 71F to 76F whereas heating S.P. adjusted from 70F to 68F. Figure 288: Electrical Comparison Figure 289: Gas Comparison Annual electrical consumption reduced by 9.1% whereas gas consumption by 47.7%. Figure 290: End Use Electrical Comparison Figure 291: End Use Gas Comparison Cooling end use reduced by 29%, heating by 54%, fans by 28%, pumps by 11% and cooling tower by 49%. The EUI reduced from 51.26 to 43.76 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐12 1289741 215211 1014873 434608 283601 269542 544355 82050 35422 % change 0% 0% 0% 29% 54% 28% 11% 0% 49% Figure 292: EEM predicted end use Figure 293: EUI Comparison b/w EEM & Calibrated 204 10.4.2. EEM-13: Mixed Mode A mixed mode system was attempted in which each window can open up to 40% Figure 294: Electrical Comparison Figure 295: Gas Comparison Annual electrical consumption reduced by 8.9% and gas consumption by 61.7% Figure 296: End Use Electrical Comparison Figure 297: End Use Gas Comparison Cooling end use reduced by 28%, heating by 70%, fans by 28%, pumps by 10% and cooling tower by 50%. The EUI reduced from 51.26 to 42.82 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐13 1289741 215211 1014873 440331 185896 267483 549480 82047 34900 % change 0% 0% 0% 28% 70% 28% 10% 0% 50% Figure 298: EEM predicted end use Figure 299: EUI Comparison b/w EEM & Calibrated 205 10.4.3. EEM-14: Variable Flow Pumps The plant loop flow for chilled water, hot water and condenser loop were modified to variable volume pumps instead of currently installed constant volume pumps. Figure 300: Electrical Comparison Figure 301: Gas Comparison Annual electrical consumption reduced by 8.6% and gas consumption increased by 12% Figure 302: End Use Electrical Comparison Figure 303: End Use Gas Comparison Cooling end use reduced by 7%, fans by 0%, pumps by 51% and cooling tower by 4% whereas heating increased by 14%. The EUI reduced from 51.26 to 48.37 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐14 1289741 215211 1014873 565776 700414 373380 301757 82066 66272 % change 0% 0% 0% 7% ‐14% 0% 51% 0% 4% Figure 304: EEM predicted end use Figure 305: EUI Comparison b/w EEM & Calibrated 206 10.4.4. EEM-15: Variable Flow Pumps The hot water loop pump was modified back to constant volume loop whereas chilled water and condenser loop were left variable volume. Figure 306: Electrical Comparison Figure 307: Gas Comparison Annual electrical consumption was reduced by 6.3% and gas consumption by 0.3% Figure 308: End Use Electrical Comparison Figure 309: End Use Gas Comparison Cooling end use was reduced by 7%, pumps by 35% and cooling tower by 4%. The EUI reduced from 51.26 to 48.47 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐15 1289741 215211 1014873 565775 614807 373380 396618 82046 66272 % change 0% 0% 0% 7% 0% 0% 35% 0% 4% Figure 310: EEM predicted end use Figure 311: EUI Comparison b/w EEM & Calibrated 207 10.4.5. EEM-16: Night Cooling Night flushing with schedule to exclude very hot and cold months and run between 11pm to 6am. The setting used was “cycle zone fans only” with cycling run time as 3600 sec. Figure 312: Electrical Comparison Figure 313: Gas Comparison Annual electrical consumption was reduced by 0.7% and gas consumption by 0.2% Figure 314: End Use Electrical Comparison Figure 315: End Use Gas Comparison Cooling end use reduced by 1% and cooling tower consumption by 2%. The EUI reduced from 51.26 to 50.94 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐16 1289741 215211 1014873 603688 615356 373306 611460 82046 67923 % change 0% 0% 0% 1% 0% 0% 0% 0% 2% Figure 316: EEM predicted end use Figure 317: EUI Comparison b/w EEM & Calibrated 208 10.4.6. EEM-17: Night Cooling The schedule, thermostat tolerance and cycling run time was kept same as previous run where as setting was used as ‘cycle on any’. Figure 318: Electrical Comparison Figure 319: Gas Comparison Annual electrical consumption reduced by 0.6% and gas consumption by 0.2% Figure 320: End Use Electrical Comparison Figure 321: End Use Gas Comparison Cooling end use reduced by 1% and cooling tower consumption by 2%. The EUI reduced from 51.26 to 50.94 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐16 1289741 215211 1014873 603688 615356 373306 611460 82046 67923 % change 0% 0% 0% 1% 0% 0% 0% 0% 2% Figure 322: EEM predicted end use Figure 323: EUI Comparison b/w EEM & Calibrated 209 10.4.7. EEM-18: Insulation + Chilled Ceiling Insulation was added to each ceiling with an internal source of chilled water tubes. The distance between each tube was kept as 4 inches. Figure 324: Electrical Comparison Figure 325: Gas Comparison Annual electrical consumption reduced by 7.3% and gas consumption by 27.1% Figure 326: End Use Electrical Comparison Figure 327: End Use Gas Comparison Changing the full HVAC system led to reduction in heating consumption by 31%, fans by 39%, and pumps by 39% but increased cooling slightly by 10% and cooling tower by 26%. Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐18 1289741 215211 1014873 670982 427103 228319 375799 82054 87544 % change 0% 0% 0% ‐10% 31% 39% 39% 0% ‐26% Figure 328: EEM predicted end use Figure 329: EUI Comparison b/w EEM & Calibrated 210 10.4.8. EEM-19: Displacement Ventilation Displacement Ventilation Strategy was mimicked in Design Builder as described earlier. Figure 330: Electrical Comparison Figure 331: Gas Comparison Annual electrical consumption reduced by 12.9% and gas consumption by 44.2% Figure 332: End Use Electrical Comparison Figure 333: End Use Gas Comparison Cooling end use reduced by 42%, heating by 50%, fans by 43%, pumps by 12% and cooling tower by 67%. The EUI reduced from 51.26 to 42.35 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐19 1289741 215211 1014873 353845 307590 212707 537079 82050 22648 % change 0% 0% 0% 42% 50% 43% 12% 0% 67% Figure 334: EEM predicted end use Figure 335: EUI Comparison b/w EEM & Calibrated 211 10.4.9. EEM-20: Heat Pumps This EEM also changed the whole HVAC system by taking out any gas related items. All heating and cooling demand is served by heat pump individually installed in each zone. Figure 336: Electrical Comparison Figure 337: Gas Comparison Annual electrical consumption reduced by 6% and gas consumption by 75.7% Figure 338: End Use Electrical Comparison Figure 339: End Use Gas Comparison Heating end use reduced by 86%, fans by 28%, pumps by 100% & cooling tower by 100% whereas cooling increased by 88%. The EUI reduced from 51.26 to 43.09 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 EEM‐20 1289741 215211 1014873 1148386 88102 267483 0 82046 0 % change 0% 0% 0% ‐88% 86% 28% 100% 0% 100% Figure 340: EEM predicted end use Figure 341: EUI Comparison b/w EEM & Calibrated 212 10.5. Executive Summary All the above independent EEMs were then put together to compare them simultaneously. There were a lot of observations during the process which are discussed in the end of this chapter. Based on these observations, final EEMs were decided for proving zero net energy calculations. Table 21: End Use Consumption of all EEMs ECM Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Total %age Difference Calibrated 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 4884764 EEM‐1 810798 215211 1014873 559795 606585 351657 604155 82047 59118 4304237 11.88% EEM‐2 872454 215211 1014873 565103 600639 351703 605474 82047 59967 4367471 10.59% EEM‐3 529911 215211 1014873 546939 660696 345409 617444 82047 56145 4068675 16.71% EEM‐4 1289741 200912 1014873 611011 616760 373375 612402 82046 69345 4870466 0.29% EEM‐5 1289741 200912 1014873 611011 616760 373375 612402 82046 69345 4870466 0.29% EEM‐6 1289741 215211 1014873 580765 559167 350895 607117 82045 63786 4763600 2.48% EEM‐7 1289741 215211 1014873 563606 582136 348859 607488 82046 59473 4763434 2.48% EEM‐8 1289741 215211 1014873 577906 577479 373244 604606 82046 63799 4798905 1.76% EEM‐9 1289741 215211 1014873 616345 547371 372233 609128 82046 70642 4817590 1.38% EEM‐10 1289741 215211 1014873 614054 559360 372457 609721 82045 70351 4827813 1.17% EEM‐11 1289741 215211 1014873 629336 514672 362562 611339 82045 72313 4792092 1.90% EEM‐12 1289741 215211 1014873 434608 283601 269542 544355 82050 35422 4169402 14.64% EEM‐13 1289741 215211 1014873 440331 185896 267483 549480 82047 34900 4079961 16.48% EEM‐14 1289741 215211 1014873 565776 700414 373380 301757 82066 66272 4609489 5.64% EEM‐15 1289741 215211 1014873 565775 614807 373380 396618 82046 66272 4618722 5.45% EEM‐16 1289741 215211 995654 603688 615356 373306 611460 82046 67923 4854384 0.62% EEM‐17 1289741 215211 999330 603764 615159 373306 611428 82046 67942 4857926 0.55% EEM‐18 1289741 215211 1014873 670982 427103 228319 375799 82054 87544 4391625 10.10% EEM‐19 1289741 215211 1014873 353845 307590 212707 537079 82050 22648 4035743 17.38% EEM‐20 1289741 215211 1014873 1148386 88102 267483 0 82046 0 4105841 15.95% This graph shows all the end uses of independent EEM’s along with percentage difference of each EEM from the calibrated model. The impact of each EEM could easily be gauged from above table and graphs below. The first graph shown below is the representation of the above table from which impacts on various end uses and overall impacts could be gauged. The graph below that shows the percentage differences of each end use from the calibrated model. The energy consumption of end-uses that got increased instead of decreasing is highlighted in pink. This gives a graphical indication of the end-use that is making the EEM overall less effective. All EEMs discussed above save 213 energy overall but not because of simultaneous effect of all end-uses. This factor was carefully studied before finalizing the EEMs for ZNE purpose. Figure 342: End Use Comparisons of all EEMs ECM Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Total % Difference EEM‐1 37% 0% 0% 8% 2% 6% 1% 0% 15% 11.88% EEM‐2 32% 0% 0% 8% 3% 6% 1% 0% 14% 10.59% EEM‐3 59% 0% 0% 10% ‐7% 7% ‐1% 0% 19% 16.71% EEM‐4 0% 7% 0% 0% 0% 0% 0% 0% 0% 0.29% EEM‐5 0% 7% 0% 0% 0% 0% 0% 0% 0% 0.29% EEM‐6 0% 0% 0% 5% 9% 6% 1% 0% 8% 2.48% EEM‐7 0% 0% 0% 8% 6% 7% 1% 0% 14% 2.48% EEM‐8 0% 0% 0% 5% 6% 0% 1% 0% 8% 1.76% EEM‐9 0% 0% 0% ‐1% 11% 0% 1% 0% ‐2% 1.38% EEM‐10 0% 0% 0% 0% 9% 0% 0% 0% ‐1% 1.17% EEM‐11 0% 0% 0% ‐3% 17% 3% 0% 0% ‐4% 1.90% EEM‐12 0% 0% 0% 29% 54% 28% 11% 0% 49% 14.64% EEM‐13 0% 0% 0% 28% 70% 28% 10% 0% 50% 16.48% EEM‐14 0% 0% 0% 7% ‐14% 0% 51% 0% 4% 5.64% EEM‐15 0% 0% 0% 7% 0% 0% 35% 0% 4% 5.45% EEM‐16 0% 0% 2% 1% 0% 0% 0% 0% 2% 0.62% EEM‐17 0% 0% 2% 1% 0% 0% 0% 0% 2% 0.55% EEM‐18 0% 0% 0% ‐10% 31% 39% 39% 0% ‐26% 10.10% EEM‐19 0% 0% 0% 42% 50% 43% 12% 0% 67% 17.38% EEM‐20 0% 0% 0% ‐88% 86% 28% 100% 0% 100% 15.95% Figure 343: Percentile Difference of each end use of EEM with calibrated model 214 10.5.1. End Use Comparisons for all Alternatives Figure 344: Total Electrical Use for the Alternatives Figure 345: Total Gas Use for Alternatives 215 Figure 346: Lighting End Use for all alternatives Figure 347: Exterior Lighting End Use for all alternatives 216 Figure 348: Equipment End Use for all alternatives Figure 349: Cooling End Use for all alternatives 217 Figure 350: Heating End Use for all alternatives Figure 351: Fans End Use for all Alternatives 218 Figure 352: Pumps End Use for all Alternatives Figure 353: End use for Domestic Hot Water 219 Figure 354: Cooling Tower End Use for all Alternatives Figure 355: Annual Operation Cost Savings for all alternatives 220 10.6. Analysis of all EEMs There were some key findings which were determined by analyzing all the EEMs discussed above. These findings are described below:  There were very slight differences between continuous dimming and 3-stepped dimming. This meant that the overall illuminance level in the rooms is quite high. We don’t need continuous dimming as a ZNE EEM which is an expensive solution when compared to 3-stepped dimming.  High Performance Glazing had slight impact on overall energy consumption. This clearly meant that deep overhangs are playing a very important role in cutting down solar gains and the building is not impacted much by radiant gains.  Higher insulation in wall increased the cooling requirement. This was unexpected but could be understood in the Los Angeles climate. Heat loss from the building during the night is essential for this climate. Again, this EEM had very slight impact on overall energy consumption which meant that the building is more internally dominated.  Operable windows decreased energy consumption. This was very much expected. Natural Ventilation is an important strategy that must be installed in this building for passive cooling purposes. This has a huge impact in reducing energy load.  Variable Pumps proved to be a very successful strategy for the chilled water loop and condenser loop but not for the hot water loop. The heating consumption went up when a variable pump was used. It was understood that the continuous 221 flow of hot water is better for this building to minimize heat losses. By keeping constant volume pumps, overall heating is lower even though pump consumption is higher.  Displacement Ventilation was one of the best possible strategies out of HVAC EEMs. This decreased the energy consumption drastically in all end-uses. This was not a directly modeled option, but was approximated by the measures indicated.  Heat Pumps were another good strategy. It reduced energy consumption overall but increased cooling consumption.  Using Energy Efficient lighting was a very effective strategy. Considering that lighting end use is the biggest end use of VKC, it reduced the energy consumption drastically. 222 CHAPTER - 11: ZNE PROPOSAL This chapter describes the possible sequence of selected effective EEMs and concludes the thesis by proving the hypothesis correct. This is done through verifying ZNE calculations. 223 11.1. Selection & Sequence of EEMs As discussed in the previous chapter, there were a lot of observations made on numerous EEMs. Based on these observations and EEMs that were of most impactful in reducing energy consumption were selected for the ZNE process. These measures were run over each other (cumulatively) unlike last chapter where EEMs were run independently over the calibrated model. One must note that these energy efficiency measures were not selected based on the cost parameter of installing them. Secondly, there can be numerous such combinations possible to achieve ZNE. The one that author took is described below. RUN-1: Energy Efficient Lighting LED fixtures of 0.7 lm/watt efficacy were used to replace all lighting fixtures in VKC. Lighting Power Density (LPD) was based on design level conditions of individual spaces. RUN-2: Lighting Controls – 3 Stepped Lighting controls were then adjusted to 3-stepped dimming to save energy. RUN-3: Variable Flow Pumps The plant loop flow for chilled water and condenser loop were modified to variable volume pumps instead of currently installed constant volume pumps. RUN-4: Displacement Ventilation Displacement Ventilation HVAC strategy was used which proved to be an effective as discussed in the previous chapter. 224 RUN-5: Insulated Roof Glass Fiber Insulation (5”) was added to roof to increase R-Value to 22.22. RUN -6: Mixed Mode Natural Ventilation was used in addition to Mechanical systems to reduce pressure on the latter to perform all the time. The ‘Calculated’ setting for natural ventilation calculations was used in Design Builder. The Natural ventilation set point was kept as 72F above which the windows would open automatically. A maximum of 40% of each window could be opened. This opening size is controlled using a modulation control with a lower value as 4 and upper value of 15 and modulation factor of 0.05 (5%). This meant that if there is a difference of 4F between inside and outside temperature the opening would automatically start closing proportionally. If the difference increases to 15%, the opening of would become 5 % of original opening size. The control mode was set as ‘Temperature’ with zone heating set point as 68 and zone cooling set point as 76. RUN -7: Energy Efficient Exterior Lighting + Override in Day Time An 80 W LED flood light replacement for the currently installed 300 W halogen lamps was used for this EEM. This product was found from the following website: http://www.alibaba.com/product-gs/523378393/Led_flood_light_replacement_metal_ halide.html. The controls were set to automatically override schedule in day time. RUN -8: Occupancy Sensors The effect of occupancy sensors couldn’t be modeled in Design Builder. The energy was estimated to be reduced based on ASHRAE 90.1 - Table G 3.2 Power Adjustment 225 Percentages for Automatic Lighting Controls. The light consumption was reduced by 10% following that chart. However, occupancy sensors would impact the corridor lights and Library stack area much more than 10%. The VKC Library stacks are used sporadically whereas no one uses corridor late in the night but lights are switched on for 24 hours a day, 7 days a week. It was assumed that the energy reduction for corridors would be 30% and stacks to be 50%. RUN -9: Corridor Skylights The skylights were added to the third floor corridor spaces in addition to photo sensors. The skylights were kept as 3% of total corridor roof area. RUN -10: Plug Loads Plug Loads that were untouched till now were adjusted based on the ASHRAE recommended baseline. These values should be bare minimum as per ASHRAE in today’s world. However, VKC is currently using slightly higher than the minimum. No particular EEM was suggested to reduce plug loads as this end use highly depends on user. 226 11.1.1. RUN-1: Energy Efficient Lighting An LED fixture of 0.7 lm/watt efficacy was used to replace all lighting fixtures in VKC. Lighting Power Density (LPD) was based on design level conditions of individual spaces. Figure 356: Electrical Comparison of Final EEM Figure 357: Electrical Comparison of Final EEM Annual electrical consumption reduced by 20.5% whereas gas increased by 6.3%. Figure 358: End Use Electrical Comparison Figure 359: End Use Gas Comparison Lighting end use reduced by 59%, cooling by 10%, fans by 7%, cooling tower by 19% whereas heating increased by 7% . The EUI reduced from 51.26 to 42.70 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐1 529911 215211 1014873 546939 660696 345409 617444 82047 56145 % change 59% 0% 0% 10% ‐7% 7% ‐1% 0% 19% Figure 360: EEM predicted end use Figure 361: EUI Comparison b/w EEM & Calibrated 227 11.1.2. RUN -2: Lighting Controls – 3 Stepped Lighting controls were then adjusted to 3-stepped dimming to save more lighting energy. Figure 362: Electrical Comparison of Final EEMs Figure 363: Gas Comparison of Final EEMs Annual electrical consumption reduced further to 26.8% from calibrated model whereas gas remained same as last run. Figure 364: End Use Electrical Comparison Figure 365: End Use Gas Comparison Lighting end use reduced further to 76%, cooling to 14%, fans to 10%, cooling tower to 26% whereas heating remained same. The EUI reduced from 42.70 to 39.92 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐2 309618 215211 1014873 524589 658619 336163 611255 82047 51270 % change 76% 0% 0% 14% ‐7% 10% 0% 0% 26% Figure 366: EEM predicted end use Figure 367: EUI Comparison b/w EEM & Calibrated 228 11.1.3. RUN-3: Variable Flow Pumps Chilled water and condenser loop were modified to variable volume pumps. Figure 368: Electrical Comparison of Final EEMs Figure 369: Gas Comparison of Final EEMs Annual electrical consumption reduced further to 33% from calibrated model whereas gas consumption remained same as previous run. Figure 370: End Use Electrical Comparison Figure 371: End Use Gas Comparison Cooling end use reduced further to 20%, cooling tower to 28%, pumps to 35%. Rest end uses remained same. The EUI reduced further from 39.92 to 37.23 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐3 309618 215211 1014873 485809 658619 336163 395302 82047 49670 % change 76% 0% 0% 20% ‐7% 10% 35% 0% 28% Figure 372: EEM predicted end use Figure 373: EUI Comparison b/w EEM & Calibrated 229 11.1.4. RUN-4: Displacement Ventilation Displacement Ventilation was used as HVAC system to see the effect over previous runs. Figure 374: Electrical Comparison of Final EEMs Figure 375: Gas Comparison of Final EEMs Annual electrical consumption reduced further to 44.1% from calibrated model and gas consumption for first time reduced by 49.1% from calibrated values. Figure 376: End Use Electrical Comparison Figure 377: End Use Gas Comparison Cooling end use reduced further to 57%, fans to 50%, pumps to 45%, cooling tower to 80%, heating to 56%. The EUI reduced further from 37.23 to 28.29 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐4 309618 215211 1014873 264792 273660 187784 334058 82051 13693 % change 76% 0% 0% 57% 56% 50% 45% 0% 80% Figure 378: EEM predicted end use Figure 379: EUI Comparison b/w EEM & Calibrated 230 11.1.5. RUN-5: Insulation in Roof Glass Fiber Insulation (5”) was added to roof to increase R-Value to 22.22. Figure 380: Electrical Comparison of Final EEMs Figure 381: Gas Comparison of Final EEMs Annual electrical consumption reduced further to 45.3% and gas consumption to 52.9% from calibrated model. Figure 382: End Use Electrical Comparison Figure 383: End Use Gas Comparison Cooling end use reduced further to 61%, fans to 53%, pumps to 47%, cooling tower to 82%, heating to 60%. The EUI reduced further from 28.29 to 27.50 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐5 309618 215211 1014873 236441 247259 176018 326343 82051 12183 % change 76% 0% 0% 61% 60% 53% 47% 0% 82% Figure 384: EEM predicted end use Figure 385: EUI Comparison b/w EEM & Calibrated 231 11.1.6. RUN-6: Mixed Mode Mixed mode system was chosen as next EEM in which each window can open up to 40%. Figure 386: Electrical Comparison of Final EEMs Figure 387: Gas Comparison of Final EEMs Annual electrical consumption reduced slightly to 45.4% and gas consumption to 66.8% from calibrated model. Figure 388: End Use Electrical Comparison Figure 389: End Use Gas Comparison Heating end use reduced further to 76% but rest end uses remained pretty much the same. The EUI reduced slightly from 27.50 to 26.44 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐6 310376 215211 1014873 235516 150225 174437 324827 82050 11690 % change 76% 0% 0% 61% 76% 53% 47% 0% 83% Figure 390: EEM predicted end use Figure 391: EUI Comparison b/w EEM & Calibrated 232 11.1.7. RUN -7: Energy Efficient Exterior Lighting + Override An 80 W LED flood light replacement for currently installed 300 W halogen lamps. Figure 392: Electrical Comparison of Final EEMs Figure 393: Gas Comparison of Final EEMs Annual electrical consumption reduced further to 49.2% whereas gas consumption remained at 66.8% reduction from calibrated model. Figure 394: End Use Electrical Comparison Figure 395: End Use Gas Comparison Exterior lighting end use reduced by 75% and rest end uses remained the same. The EUI reduced further from 26.44 to 24.74 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐7 310376 53577 1014873 235516 150225 174437 324827 82050 11690 % change 76% 75% 0% 61% 76% 53% 47% 0% 83% Figure 396: EEM predicted end use Figure 397: EUI Comparison b/w EEM & Calibrated 233 11.1.8. RUN -8: Occupancy Sensors Energy reduction based on ASHRAE 90.1 - Table G 3.2 using occupancy sensors Figure 398: Electrical Comparison of Final EEMs Figure 399: Gas Comparison of Final EEMs Annual electrical consumption reduced further to 51.6% whereas gas consumption remained at 66.8% reduction from calibrated model. Figure 400: End Use Electrical Comparison Figure 401: End Use Gas Comparison Lighting end use reduced to 84% and rest end uses remained the same. The EUI reduced further from 24.74 to 23.69 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐8 210540 53577 1014873 235516 150225 174437 324827 82050 11690 % change 84% 75% 0% 61% 76% 53% 47% 0% 83% Figure 402: EEM predicted end use Figure 403: EUI Comparison b/w EEM & Calibrated 234 11.1.9. RUN -9: Skylights in Corridors Skylights of 3% corridor roof area were added to the third floor corridor spaces. Figure 404: Electrical Comparison of Final EEMs Figure 405: Gas Comparison of Final EEMs Annual electrical consumption reduced slightly to 51.7% whereas gas consumption remained at 66.8% reduction from calibrated model. Figure 406: End Use Electrical Comparison Figure 407: End Use Gas Comparison The lighting end use even though decreased had minimal effect on overall percentile difference. The EUI reduced very slightly from 24.74 to 23.67 kBtu/sft-yr. Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 RUN‐9 207803 53577 1014873 235516 150225 174437 324827 82050 11690 % change 84% 75% 0% 61% 76% 53% 47% 0% 83% Figure 408: EEM predicted end use Figure 409: EUI Comparison b/w EEM & Calibrated 235 11.1.10. Final Run: Plug Loads Plug Loads were adjusted based on ASHRAE recommended baseline. Figure 410: Electrical Comparison of Final EEMs Figure 411: Gas Comparison of Final EEMs Annual electrical consumption reduced to 57% whereas gas consumption remained at 66.8% reduction from calibrated model. Figure 412: End Use Electrical Comparison Figure 413: End Use Gas Comparison The plug load end use reduced by 22% which made the site EUI (21.33 ) to go below the maximum site generation potential through renewable sources. (22.65 kBtu/sft-yr) Lighting Exterior Lighting Plug Loads Cooling (c Heating Fans Pumps DHW Cooling Tower Calibrated Model 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 Final EEM (10th) 207803 53577 792511 235516 150225 174437 324827 82050 11690 % change 84% 75% 22% 61% 76% 53% 47% 0% 83% Figure 414: EEM predicted end use Figure 415: EUI Comparison b/w EEM & Calibrated 236 11.2. Executive Summary It was found that there were diminishing returns of the EEMs in the latter half of proposed EEMs. Consolidated energy consumption profiles for all proposed EEMs are shown below for both electricity and gas. Figure 416: Comparison of Electrical Consumption of all proposed EEMs Figure 417: Comparison of Gas Consumption of all proposed EEMs 237 End use and total variations due to different EEMs were recorded. The percentage differences were also calculated from the calibrated model and are shown below. Table 22: End Use of all EEMs ECM Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Total %age Difference Calibrated 1289741 215211 1014873 611011 616760 373375 612402 82046 69345 4884764 RUN‐1 529911 215211 1014873 546939 660696 345409 617444 82047 56145 4068675 16.71% RUN‐2 309618 215211 1014873 524589 658619 336163 611255 82047 51270 3803645 22.13% RUN‐3 309618 215211 1014873 485809 658619 336163 395302 82047 49670 3547313 27.38% RUN‐4 309618 215211 1014873 264792 273660 187784 334058 82051 13693 2695739 44.81% RUN‐5 309618 215211 1014873 236441 247259 176018 326343 82051 12183 2619996 46.36% RUN‐6 310376 215211 1014873 235516 150225 174437 324827 82050 11690 2519205 48.43% RUN‐7 310376 53577 1014873 235516 150225 174437 324827 82050 11690 2357571 51.74% RUN‐8 210540 53577 1014873 235516 150225 174437 324827 82050 11690 2257735 53.78% RUN‐9 207803 53577 1014873 235516 150225 174437 324827 82050 11690 2254998 53.84% Final Run 207803 53577 792511 235516 150225 174437 324827 82050 11690 2032636 58.39% Table 23: Percentage Differences of all End Uses from Calibrated Model ECM Lighting Exterior Lighting Plug Loads Cooling (chiller) Heating Fans Pumps DHW Cooling Tower Total % Difference RUN‐1 59% 0% 0% 10% ‐7% 7% ‐1% 0% 19% 16.71% RUN‐2 76% 0% 0% 14% ‐7% 10% 0% 0% 26% 22.13% RUN‐3 76% 0% 0% 20% ‐7% 10% 35% 0% 28% 27.38% RUN‐4 76% 0% 0% 57% 56% 50% 45% 0% 80% 44.81% RUN‐5 76% 0% 0% 61% 60% 53% 47% 0% 82% 46.36% RUN‐6 76% 0% 0% 61% 76% 53% 47% 0% 83% 48.43% RUN‐7 76% 75% 0% 61% 76% 53% 47% 0% 83% 51.74% RUN‐8 84% 75% 0% 61% 76% 53% 47% 0% 83% 53.78% RUN‐9 84% 75% 0% 61% 76% 53% 47% 0% 83% 53.84% RUN‐10 84% 75% 22% 61% 76% 53% 47% 0% 83% 58.39% Figure 418: Energy Consumption by all EEMs 238 All end uses for each EEM are shown separately in individual graphs. This is done to understand the effect of all EEMs on individual End Use Figure 419: Total Electrical Consumption for Alternatives Figure 420: Total Gas Use for Alternatives 239 Figure 421: Lighting End Use for Alternatives Figure 422: External Lighting End Use for Alternatives 240 Figure 423: Equipment End Use for Alternatives Figure 424: Cooling End Use for Alternatives 241 Figure 425: Heating End Use for Alternatives Figure 426: Fan End Use for Alternatives 242 Figure 427: Pumps End Use for Alternatives Figure 428: Domestic Hot Water End Use for Alternatives 243 Figure 429: Cooling Tower End Use for Alternatives Figure 430: Operational Cost Savings for Alternatives 244 11.3. ZNE Calculations The maximum on-site potential of the VKC site as discussed in Chapter 3 (section 3.4) is 632,565 kWh. This value when converted to Energy Use Intensity (EUI) comes out to be 22.65 kBtu/sft-yr. The intent of ZNE building is to first minimize the energy consumption of the building and then support it with on-site renewable energies. The total energy consumption of VKC has been radically reduced by 58.39% for the calibrated model to have an EUI of 21.33 kBtu/sft-yr. Figure 431: EUI Comparison of Final EEM to Calibrated Model This EUI of 21.33 kBtu/sft-yr is lower than the maximum Site Potential EUI of 22.65 kBtu/sft-yr (that is the potential energy generated on site). This proves that VKC can be a net zero energy building if all the ten EEMs discussed were implemented in the building. 245 Figure 432: ZNE Calculations Figure 433: End Use Comparison between Calibrated Model and ZNE version of VKC The end uses of the ZNE version of VKC building are shown above in comparison to the calibrated model. This clearly shows the dominance of plug loads and the drastic reduction in the lighting end use in the final ZNE version. The dominance of plug loads is primarily because that end use was left alone while implementing various energy efficiency measures over calibrated model. 246 11.4. Operational Cost Savings Operational cost savings were calculated if the VKC building runs as a ZNE building after implementing all proposed EEMs. Figure 434: Cost Analysis The ZNE building estimated electrical and gas consumptions were subtracted from original VKC electrical and gas consumptions respectively for 2010. The utility rate for calculating the cost was used as static and not on peak, super peak, part peak or off peak basis. The electricity utility rate was used as 12 cents per kWh and gas rate as USD 1.25 per Therm. The total savings when added together came out to be $ 133,282. In addition, there is renewable energy generated which would further offset the need of utility power. The PV panels over the VKC roof can generate 632,565 kWh annually which would further save $75,908 if compounded as savings on an electrical utility bill at 12 cents/kWh. If the on-site generation is more at a particular time, this excess electricity can be sent back to electrical grid and the meter would be spin in reverse direction. Excess generation would even save more money. The utility cannot store the excess for 247 free, but in energy terms there is an excess and even with a discounted rate, there would be a profit available. 11.5. Summary & Conclusions It has been proven that it is possible to achieve the net zero energy goal for an existing institutional building by calibrating an energy model to the utility data of the building, providing various energy efficiency measures and generating on-site electricity. The hypothesis has thus been verified. There have been numerous roadblocks, real life delays, software limitations that had to be overcome to achieve this result. It began with choosing a case study building, accumulating associated building information from different sources, getting an accurate weather file, acquiring utility information, renting tools from SCE to gather plug load information, benchmarking of building with various industry standards to understand current building performance, doing climate analysis, performing site context analysis along with solar shade analysis to understand the effect of neighboring buildings, choosing the right energy simulation software and learning it, overcoming interoperability issues of different softwares, understanding the calibration process and associated protocols of modeling it, choosing a ZNE definition, estimating on-site renewable energy potential, setting a ZNE target, making accurate fractional and temperature schedules after obtaining information from various sources, calculating heating and cooling loads by manual calculation for verification purposes, unraveling a history which was associated with and complicated HVAC systems installed in the building, investigating ways to accurately model such a complicated HVAC system, incorporating exact chiller curves, dealing with the possibility of inaccurate gas data, 248 evaluating numerous energy efficiency measures and ways to model them and finally putting some selected EEMs in sequence to reach the zero net energy goal. The operational cost savings were then estimated at each energy efficiency measure step and overall zero net energy proved building. According to author, this whole process has been a successful exercise with a steep learning curve. One of the outcomes of this thesis is that it led Facilities Management Services department of USC to sub-meter the VKC in order to gauge its actual gas consumption and potentially move towards a commissioning process to avoid further loss. It can be taken as a successful aspect of this thesis that this study led to actual decisions being made in the real world. This thesis has not only successfully proved VKC to be a potential zero net energy building but also proved that full on-site energy potential is not required to meet ZNE requirements. The Solar PV’s can be designed for only 94% of total site potential. A large amount of on-site generation was possible in this special case as the full roof was available for installing solar PV’s. All the mechanical system was in the basement and cooling tower in the neighboring building. This site potential could even be increased by putting wind turbines over the roof of VKC but is not needed to be a ZNE if the proposed EEMs are followed for reducing energy consumption. It must be noted that all these energy efficiency measures are based on a calibrated model which behaves like the actual VKC building. However, this calibration was done to the utility bills and energy consumption of a particular year which in this case was 2010. That particular year might not be the best indication of average temperature values of that location. This was verified by running a small test in which the actual 2010 weather 249 file was replaced with TMY3 file obtained from Los Angeles airport. The cooling end use was reduced further by 27%, fans by 3%, cooling tower by 67%. However, heating end use increased by 32% and pumps by 2%. Overall EUI remained nearly similar with a slight decrease by 0.19 kBtu/sft-yr. This meant that 2010 was slightly warmer than average temperatures in Los Angeles which required more cooling and less heating than a typical year. The energy simulation software selection to carry out this mammoth task was a really good choice: which in this case was Design Builder based on the Energy Plus engine. It offered a good flexibility while modeling, has a really good user-friendly interface, can export different type of results to a .csv format which can then easily be opened in excel, has a capability of modeling complex HVAC systems, can do day-lighting and computational fluid dynamic studies, calculates heating and cooling loads based on ASHRAE design conditions and produces accurate results. However, there were some downfalls that were noticed for Design Builder as well. Firstly, it takes a really long time to simulate results. It took an average 4-5 hours per run while calculating energy consumption in the latter part of energy efficiency measures. Secondly, it can’t model mixed mode in the detailed mode of HVAC system. Thirdly, it doesn’t have any utility information and cost outputs. Last and foremost, it doesn’t have capabilities to store results of one simulation and then compare it to the next one with a small change in the same file. All the files have to be saved separately and results are compared later in excel. Even though there was some of these downfalls, overall this is very useful software. This thesis has explored one of the ways in which ZNE could be achieved for VKC based on one of the ZNE definitions. It must be noted that the process shown through this thesis is just one combination of EEMs to achieve ZNE. A lot more combinations can be 250 possible to achieve the same result and it shouldn’t be considered the sequence of EEMs proposed is the only most probable way of making VKC a zero net energy building. A lot more possibilities can be experimented with for finding the same. A lot of real life scenarios like budgets and time frame have an impact on choosing and implementation of EEMs which have not been seen in this thesis. 11.6. Future Work This thesis, even though it sounds convincingly complete can be taken up for future works. There is the possibility of taking ZNE model as a base model and devising more strategies to make it more energy efficient or doing related research. Some of the possibilities with further modeling and related researches are discussed below.  Sequence of EEMs More combinations of sequences of EEMs can be experimented to reach ZNE goal and finally choose which requires the least number of iterations.  Cost Base EEM Analysis The Net Present Value (NPV) and Life Cycle Costing for implementing each EEM can be found which can be a deciding factor in choosing and sequencing EEMs to reach ZNE goal. This aspect has been intentionally overlooked in this thesis but would prove crucial while making actual retrofitting decisions.  Different ZNE Definitions Calculations can be done to check if these EEMs satisfy other definitions of ZNE as described earlier in this thesis. This can lead to co-relations among ZNE definitions and possibly lead to one industry specific definition. 251  Incentives There are numerous incentives given by Utility companies that can be explored which would aid in making actual retrofit decisions. Zero Net Energy building are beat code by a huge margin and must be taken advantage of by the means of incentives.  Sub-Metering of VKC It would be useful to follow up with the metered readings of Gas Usage for VKC once the sub-meters are installed in the building. USC’s Facilities Management Services has already started taking an action in this regard.  Commissioning of VKC The simulation model created in Design Builder can be updated if there are some important findings once the commissioning of VKC is done and help in accurately predicting more energy savings.  Comparison with ASHRAE 90.1 Baseline ASHRAE 90.1 baseline model can be created for this building typology and then compared to ZNE model of VKC. This will give a comparison of how much better is this building performing with respect to the baseline case.  Calibration using different simulation softwares A full scale study can be done by simulating the same building in another software either based on the same or different simulation engines and then comparing the results. The same Architectural and HVAC inputs, weather file, schedules, LPD, EPD, Occupancy, equipment curves and other related inputs can be input in the second software. The 252 comparison can then be based on loads calculated, energy consumption predicted while calibrating the same building in different softwares and while performing same energy efficiency measures. Some of the work on these lines has already been done by the author for a research paper submitted in SimBuild 2012 with the title “Comparing two simulation softwares while calibrating the same building”.  Post Occupancy Surveys Post occupancy surveys can be done for finding out the problems/ areas of discomfort in the current operation of buildings. The adjustments can be tailored to those findings which would eventually aid in the path of zero net energy. 253 BIBLIOGRAPHY ASHRAE Handbook, 2005. ASHRAE Fundamentals. California Energy Commission 2008, California Commercial End-Use Survey (CEUS), The California Energy Commission, accessed August 2011, <http://www.energy.ca.gov/ceus/> Delaware Valley Green Building Council 2009, The Commercial Buildings Energy Consumption Survey (CBECS), DVGBC, accessed October 2011, <http://www.dvgbc.org/green_resources/library/commercial-buildings-energy- consumption-survey-cbecs> Grondzik, W, Kwok, A, Stein, B & Reynolds, J, 2011, Mechanical and Electrical Equipment for Buildings 11th Edition, John Wiley & Sons Publishing, California Haberl, J & Bou-Saada, T 1998, ‘Procedures for calibrating hourly simulation models to measured building energy and environment data’, ASME Journal of Solar Energy Engineering 120 p. 193-234. Hirsch, J 1998, DOE-2, accessed September 2011, http://doe2.com/ Hirsch, J 1998, DOE-2 Documentation, V.2.2, September 2001.Volume 3, Topics. Simualtion Research Group, LBNL Hunn, B 1996, Fundamentals of building energy dynamics. MIT Press. International Performance Measurement & Verification Protocol 2002, Concepts and Options for Determining Energy and Waste Savings, IPMVP, accessed August 2011, http://www.nrel.gov/docs/fy02osti/31505.pdf Jas Air Service 1999, Test and Balance Analysis Report, California Khuen, C 2011, Weather Analytics, accessed August 2011, <www.weatheranalytics.com> Marszal, A, Heiselberg, P, Bourrelle, J, Musall, E, Voss, K, Sartori, I & Napolitano, A 2011, “Zero Energy Building – A review of definations and calculations methodologies,” Energy and Buildings 43, p. 971-979, viewed 15 October 2011, http://www.sciencedirect.com.libproxy.usc.edu/science/article/pii/S037877881 0004639 254 Mazria, E 2009, Testimony of Mr. Edward Mazria, viewed 23 August 2011, http://architecture2030.org/files/Mazria_testimony.pdf Noesis Energy 2012, Coefficient of Variation of the Root Mean Squared Error, Noesis Energy, accessed 16 February 2012, http://www.noesisenergy.com/glossary/cv -rmse Pan, Y, Huang, Z & Wu, G 2007, “Calibrated building energy simulation and its application in a high rise commercial building in Shanghai,” Energy and Buildings 39, p.651-657 viewed 17 July 2011, http://www.sciencedirect.com.libproxy.usc.edu/science/article/pii/S037877880 6002404 Pan, Y, Zuo, M & Wu, G 2009, ‘Whole building energy simulation and energy saving potential analysis of a large public building’, paper presented at the Eleventh International IBPSA Conference, 27-30 July 2009, viewed 17 July 2011, http://www.ibpsa.org/proceedings/BS2009/BS09_0129_136.pdf Raftery, P, Keane, M & Donnell, J 2011, ‘Calibrating whole building energy models: An evidence-based methodology,’ Energy and Buildings 43, p. 3666-3679 viewed 19 October 2011, http://www.sciencedirect.com.libproxy.usc.edu/science/article/pii/S0378778811 002349 The Engineering Tool Box 2011, Converting kW/ton to COP or EER, viewed 8 October 2011, http://www.engineeringtoolbox.com/cop-eer-d_409.html The 2030 Challenge, Architecture 2030, accessed September 2011, <http://www.architecture2030.org/2030_challenge/the_2030_challenge> Torcellini, P, Pless, S & Deru, M 2006, Zero Energy Buildings: A Critical Look at the Definition, viewed 10 September 2011, http://www.nrel.gov/docs/fy06osti/39833.pdf Turner, C & Frankel, M 2008, Energy Performance of LEED for New Construction Buildings, viewed 28 September 2011, http://www.usgbc.org/ShowFile.aspx?DocumentID=3930 U.S. Department of Energy 2012, M&V Guidelines: Measurement and Verification for Federal Energy Projects, Federal Energy Management Program, accessed March 2012, http://www1.eere.energy.gov/femp/pdfs/mv_guidelines.pdf 255 U.S. Environmental Protection Agency 2011, Energy Use Intensity, Energy Star, accessed 04 November 2011, http://www.energystar.gov/index.cfm?fuseaction=buildingcontest.eui Waddell, C & Kaserekar, S 2010, ‘Solar gain and cooling load comparison using energy modeling software’, paper presented at Fourth National Conference of IBPSA- USA, 11-13 August 2010, viewed 11 January 2012, http://www.ibpsa.us/pub/simbuild2010/papers/SB10-DOC-TS04A-01- Kasarekar.pdf 256 APPENDIX A: UTILITY INFORMATION This utility information shown below was obtained from Facilities Management Services, USC. Table 24: VKC Gas Consumption Based on Consumption Month Natural Gas VonKleinsmid Center (blg #4) (based on consumption month) Bldg Code JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL VKC 4,593 2,077 3,833 3,486 1,912 1,274 1,188 1,861 2,134 2,552 3,103 3,036 31,049 Bldg Code JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL VKC $2,928 $549 $5,324 $2,086 $1,784 $1,024 $678 $1,522 $1,392 $1,581 $1,764 $1,665 22,298 $ CALENDAR YEAR: 2010 | NATURAL GAS CONSUMPTION (IN THERMS) CALENDAR YEAR: 2010 | NATURAL GAS COST Table 25: VKC Gas Consumption Based on Billing Month Natural Gas VonKleinsmid Center (blg #4) (based on billing month) Bldg Code JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL VKC 3,198 4,593 2,077 3,833 3,486 1,912 1,274 1,188 1,861 2,134 2,552 3,103 31,211 Bldg Code JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL VKC $1,979 $2,928 $549 $5,324 $2,086 $1,784 $1,024 $678 $1,522 $1,392 $1,581 $1,764 22,612 $ CALENDAR YEAR: 2010 | NATURAL GAS CONSUMPTION (IN THERMS) CALENDAR YEAR: 2010 | NATURAL GAS COST 257 Table 26: Electrical Consumption of VKC from 2001 to 2011 Average of kwh/day FY month 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 1 4,391 3,579 4,353 5,265 5,152 4,967 5,997 4,178 4,396 4,581 3,673 2 5,352 3,847 4,733 5,870 5,209 5,181 6,606 4,945 4,996 4,767 3,844 3 5,478 3,944 4,973 5,820 6,034 4,860 6,839 4,876 5,620 5,468 4,151 4 5,298 4,110 4,818 5,411 5,991 5,401 6,177 4,454 4,985 4,961 4,485 5 4,120 4,032 5,058 4,798 4,466 4,619 5,405 4,041 4,593 3,770 3,963 6 3,691 2,816 3,801 3,441 3,834 3,973 4,137 3,304 3,503 2,702 3,023 7 3,306 3,633 4,111 3,554 4,260 3,711 3,337 3,271 3,781 3,323 3,133 8 3,498 3,898 4,283 3,791 4,348 4,348 4,766 3,787 4,623 3,286 2,857 9 4,007 3,613 4,948 4,388 4,571 3,638 5,139 4,024 4,370 3,497 2,622 10 4,219 4,586 4,463 4,689 5,229 4,222 5,168 4,824 4,976 3,669 3,580 11 3,733 4,353 4,195 5,269 5,026 4,251 4,515 4,454 4,629 3,657 3,422 12 3,766 4,412 4,800 4,692 4,469 5,049 3,092 4,310 3,399 3,436 3,513 Grand Total 4,238 3,902 4,545 4,749 4,882 4,518 5,098 4,206 4,489 3,926 3,522 kwh/sqft 15.8 14.6 17.0 17.7 18.2 16.9 19.0 15.7 16.7 14.6 % change (prev. yr) -8% 16% 4% 3% -7% 13% -18% 7% -13% Figure 435: Electrical Consumption Profiles of VKC from 2001 to 2011 258 Table 27: Fifteen Minute Interval Electrical Consumption (KW) as obtained from FMS Building No. Time Logged Total KW 41/1/2010 0:00 14.93 41/1/2010 0:15 15.74 41/1/2010 0:30 17.61 41/1/2010 0:45 17.37 41/1/2010 1:00 17.57 41/1/2010 1:15 17.7 41/1/2010 1:30 17.69 41/1/2010 1:45 17.68 41/1/2010 2:00 17.49 41/1/2010 2:15 17.44 41/1/2010 2:30 17.66 41/1/2010 2:45 17.59 41/1/2010 3:00 17.66 41/1/2010 3:15 17.37 41/1/2010 3:30 17.58 41/1/2010 3:45 17.62 41/1/2010 4:00 17.61 41/1/2010 4:15 17.53 41/1/2010 4:30 17.37 41/1/2010 4:45 17.35 41/1/2010 5:00 17.52 41/1/2010 5:15 17.64 41/1/2010 5:30 17.56 41/1/2010 5:45 17.51 41/1/2010 6:00 17.2 41/1/2010 6:15 17.03 41/1/2010 6:30 17.28 41/1/2010 6:45 17.25 41/1/2010 7:00 17.89 41/1/2010 7:15 20.12 41/1/2010 7:30 20.26 41/1/2010 7:45 20.01 41/1/2010 8:00 19.95 41/1/2010 8:15 19.99 41/1/2010 8:30 19.98 41/1/2010 8:45 19.87 41/1/2010 9:00 19.94 41/1/2010 9:15 20.07 41/1/2010 9:30 19.75 41/1/2010 9:45 19.79 4 1/1/2010 10:00 19.81 259 APPENDIX B: SCHEDULES This section describes the schedule that was made by author after referring to different sources to be used in Design Builder for calibration purposes. Table 28: Schedule Used for Design Builder Simulation Model (Fractional) Classroom Intermittant Load NV Schedule Corridor Light Schedule:Compact, Schedule:Compact, Schedule:Compact, VKC_Intermittant_Equip, VKC_NV Sch, VKC_Off_Light, Fraction, Fraction, Fraction, Through: 10 Jan, Through: 28 Feb, Through: 10 Jan, For: AllDays, For: AllDays, For: AllDays, Until: 24:00, 0, Until: 24:00, 0, Until: 05:00, 0, Through: 1 May, Through: 12 May, Until: 24:00, 1, For: Weekends Holidays, For: Weekdays Weekends SummerDThrough: 12 May, Until: 24:00, 0, Until: 07:00, 0, For: AllDays, For: AllOtherDays, Until: 18:00, 1, Until: 24:00, 1, Until: 08:00, 0, Until: 24:00, 0, Through: 22 Aug, Until: 18:00, 0.33, For: AllOtherDays, For: AllDays, Until: 24:00, 0, Until: 24:00, 0, Until: 05:00, 0, Through: 19 May, Through: 22 Aug, Until: 24:00, 1, For: AllDays, For: Weekends Holidays, Through: 15 Dec, Until: 24:00, 0, Until: 24:00, 0, For: AllDays, Through: 22 Aug, For: AllOtherDays, Until: 24:00, 1, For: Weekends Holidays, Until: 09:00, 0, Through: 31 Dec, Until: 24:00, 0, Until: 17:00, 1, For: AllDays, For: AllOtherDays, Until: 24:00, 0, Until: 05:00, 0, Until: 08:00, 0, Through: 30 Nov, Until: 24:00, 1; Until: 18:00, 0.16, For: Weekdays Weekends SummerDesignDay, Until: 24:00, 0, Until: 07:00, 0, Through: 15 Dec, Until: 18:00, 1, For: Weekends Holidays, Until: 24:00, 0, Until: 24:00, 0, For: AllOtherDays, For: AllOtherDays, Until: 24:00, 0, Until: 08:00, 0, Through: 31 Dec, Until: 18:00, 0.33, For: AllDays, Until: 24:00, 0, Until: 24:00, 0; Through: 31 Dec, For: AllDays, Until: 24:00, 0; 260 Table 29: Schedule Used for Design Builder Simulation Model (Fractional) Office Light New Classroom Light Office Equipment Sch Schedule:Compact, Schedule:Compact, Schedule:Compact, VKC_Off_Light, VKC_NewClass_Light, VKC_Off_Equip, Fraction, Fraction, Fraction, Through: 10 Jan, Through: 10 Jan, Through: 10 Jan, For: Weekends Holidays, For: Weekends Holidays, For: Weekends Holidays, Until: 24:00, 0, Until: 24:00, 0, Until: 24:00, 0.0545, For: AllOtherDays, For: AllOtherDays, For: AllOtherDays, Until: 09:00, 0, Until: 09:00, 0, Until: 09:00, 0.0545, Until: 17:00, 1, Until: 17:00, 1, Until: 17:00, 1, Until: 24:00, 0, Until: 24:00, 0, Until: 24:00, 0.0545, Through: 12 May, Through: 12 May, Through: 12 May, For: Weekdays SummerDesignDay, For: Weekdays SummerDesignDay, For: Weekdays SummerDesignDay, Until: 07:00, 0, Until: 08:00, 0, Until: 07:00, 0.0545, Until: 08:00, 0.5, Until: 17:00, 1, Until: 08:00, 0.5, Until: 17:00, 1, Until: 18:00, 0.5, Until: 17:00, 1, Until: 18:00, 0.5, Until: 24:00, 0, Until: 18:00, 0.5, Until: 24:00, 0, For: Weekends AllOtherDays, Until: 24:00, 0.0545, For: Weekends AllOtherDays, Until: 24:00, 0, For: Weekends AllOtherDays, Until: 24:00, 0, Through: 22 Aug, Until: 24:00, 0.0545, Through: 22 Aug, For: Weekends Holidays, Through: 22 Aug, For: Weekdays SummerDesignDay, Until: 24:00, 0, For: Weekdays SummerDesignDay, Until: 09:00, 0, For: AllOtherDays, Until: 09:00, 0.0545, Until: 17:00, 1, Until: 09:00, 0, Until: 17:00, 1, Until: 24:00, 0, Until: 17:00, 1, Until: 24:00, 0.0545, For: Weekends AllOtherDays, Until: 24:00, 0, For: Weekends AllOtherDays, Until: 24:00, 0, Through: 15 Dec, Until: 24:00, 0.0545, Through: 15 Dec, For: Weekdays SummerDesignDay, Through: 15 Dec, For: Weekdays SummerDesignDay, Until: 08:00, 0, For: Weekdays SummerDesignDay, Until: 07:00, 0, Until: 17:00, 1, Until: 07:00, 0.0545, Until: 08:00, 0.5, Until: 18:00, 0.5, Until: 08:00, 0.5, Until: 17:00, 1, Until: 24:00, 0, Until: 17:00, 1, Until: 18:00, 0.5, For: Weekends AllOtherDays, Until: 18:00, 0.5, Until: 24:00, 0, Until: 24:00, 0, Until: 24:00, 0.0545, For: Weekends AllOtherDays, Through: 31 Dec, For: Weekends AllOtherDays, Until: 24:00, 0, For: Weekends Holidays, Until: 24:00, 0.0545, Through: 31 Dec, Until: 24:00, 0, Through: 31 Dec, For: Weekdays SummerDesignDay, For: AllOtherDays, For: Weekdays SummerDesignDay, Until: 09:00, 0, Until: 09:00, 0, Until: 09:00, 0.0545, Until: 17:00, 1, Until: 17:00, 1, Until: 17:00, 1, Until: 24:00, 0, Until: 24:00, 0; Until: 24:00, 0.0545, For: Weekends AllOtherDays, For: Weekends AllOtherDays, Until: 24:00, 0; Until: 24:00, 0.0545; 261 Table 30: Schedule Used for Design Builder Simulation Model (Fractional) Old Classroom Light Library Light Library Equip Sch Schedule:Compact, Schedule:Compact, Schedule:Compact, VKC_OldClass_Light, VKC_Library_Light, VKC_Lib_Equip, Fraction, Fraction, Fraction, Through: 5 Jan, Through: 10 Jan, Through: 10 Jan, For: AllDays, For: Weekdays SummerDesignDay, For: Weekdays SummerDesignDay, Until: 24:00, 0, Until: 09:00, 0, Until: 09:00, 0.0545, Through: 10 Jan, Until: 17:00, 1, Until: 17:00, 1, For: AllDays, Until: 24:00, 0, Until: 24:00, 0.0545, Until: 09:00, 0, For: Weekends AllOtherDays, For: Weekends AllOtherDays, Until: 17:00, 1, Until: 24:00, 0, Until: 24:00, 0.0545, Until: 24:00, 0, Through: 12 May, Through: 12 May, Through: 15 Mar, Until: 09:00, 0, For: Monday Tuesday Wednesday Thursday, For: Weekdays SummerDesignDay WinterDesignDayUntil: 22:00, 1, Until: 09:00, 0.0545, Until: 08:00, 0, Until: 24:00, 0, Until: 22:00, 1, Until: 24:00, 1, For: Friday Saturday, Until: 24:00, 0.0545, For: Weekends AllOtherDays, Until: 09:00, 0, For: Friday Saturday, Until: 10:00, 0, Until: 17:00, 1, Until: 09:00, 0.0545, Until: 18:00, 1, Until: 24:00, 0, Until: 17:00, 1, Until: 22:00, 0.75, For: Sunday, Until: 24:00, 0.0545, Until: 24:00, 0.5, Until: 12:00, 0, For: Sunday, Through: 21 Mar, Until: 20:00, 1, Until: 12:00, 0.0545, For: AllDays, Until: 24:00, 0, Until: 20:00, 1, Until: 09:00, 0, For: SummerDesignDay, Until: 24:00, 0.0545, Until: 21:00, 1, Until: 09:00, 0, For: SummerDesignDay, Until: 24:00, 0, Until: 22:00, 1, Until: 09:00, 0.0545, Through: 1 May, Until: 24:00, 0, Until: 22:00, 1, For: Weekdays SummerDesignDay WinterDesignDayFor: AllOtherDays, Until: 24:00, 0.0545, Until: 08:00, 0, Until: 24:00, 0, For: AllOtherDays, Until: 24:00, 1, Through: 22 Aug, Until: 24:00, 0.0545, For: Weekends AllOtherDays, For: Weekdays SummerDesignDay, Through: 22 Aug, Until: 10:00, 0, Until: 09:00, 0, For: Weekdays SummerDesignDay, Until: 18:00, 1, Until: 17:00, 1, Until: 09:00, 0.0545, Until: 22:00, 0.75, Until: 24:00, 0, Until: 17:00, 1, Until: 24:00, 0.5, For: Weekends AllOtherDays, Until: 24:00, 0.0545, Through: 12 May, Until: 24:00, 0, For: Weekends AllOtherDays, For: AllDays, Through: 15 Dec, Until: 24:00, 0.0545, Until: 03:00, 1, For: Monday Tuesday Wednesday Thursday, Through: 15 Dec, Until: 07:00, 0, Until: 09:00, 0, For: Monday Tuesday Wednesday Thursday, Until: 08:00, 0.5, Until: 22:00, 1, Until: 09:00, 0.0545, Until: 24:00, 1, Until: 24:00, 0, Until: 22:00, 1, Through: 22 Aug, For: Friday Saturday, Until: 24:00, 0.0545, For: AllDays, Until: 09:00, 0, For: Friday Saturday, Until: 09:00, 0, Until: 17:00, 1, Until: 09:00, 0.0545, Until: 20:00, 1, Until: 24:00, 0, Until: 17:00, 1, Until: 24:00, 0, For: Sunday, Until: 24:00, 0.0545, Through: 15 Dec, Until: 12:00, 0, For: Sunday, For: Weekdays SummerDesignDay WinterDesignDayUntil: 20:00, 1, Until: 12:00, 0.0545, Until: 08:00, 0, Until: 24:00, 0, Until: 20:00, 1, Until: 24:00, 1, For: SummerDesignDay, Until: 24:00, 0.0545, For: Weekends AllOtherDays, Until: 09:00, 0, For: SummerDesignDay, Until: 10:00, 0, Until: 22:00, 1, Until: 09:00, 0.0545, Until: 18:00, 1, Until: 24:00, 0, Until: 22:00, 1, Until: 22:00, 0.75, For: AllOtherDays, Until: 24:00, 0.0545, Until: 24:00, 0.5, Until: 24:00, 0, For: AllOtherDays, Through: 31 Dec, Through: 31 Dec, Until: 24:00, 0.0545, For: Weekends Holidays, For: Weekdays SummerDesignDay, Through: 31 Dec, Until: 24:00, 0, Until: 09:00, 0, For: Weekdays SummerDesignDay, For: AllOtherDays, Until: 17:00, 1, Until: 09:00, 0.0545, Until: 09:00, 0, Until: 24:00, 0, Until: 17:00, 1, 262 Table 31: Schedule Used for Design Builder Simulation Model (Fractional) New Classroom Occupancy Office Occupancy New Classroom Computers Load Schedule:Compact, Schedule:Compact, Schedule:Compact, VKC_NewClassroom_Occ, VKC_Office_Occ, VKC_NewClassComp_Equip, Fraction, Fraction, Fraction, Through: 5 Jan, Through: 10 Jan, Through: 5 Jan, For: AllDays, For: Weekends Holidays, For: AllDays, Until: 24:00, 0, Until: 24:00, 0, Until: 24:00, 0, Through: 10 Jan, For: AllOtherDays, Through: 10 Jan, For: Weekends Holidays, Until: 09:00, 0, For: Weekends Holidays, Until: 24:00, 0, Until: 17:00, 0.75, Until: 24:00, 0, For: AllOtherDays, Until: 24:00, 0, For: AllOtherDays, Until: 09:00, 0, Through: 12 May, Until: 09:00, 0, Until: 17:00, 0.025, For: Weekdays SummerDesignDay, Until: 17:00, 0.5, Until: 24:00, 0, Until: 07:00, 0, Until: 24:00, 0, Through: 12 May, Until: 08:00, 0.25, Through: 12 May, For: Weekdays SummerDesignDay WintUntil: 09:00, 0.5, For: Weekdays SummerDesignDay WinterDesig Until: 08:00, 0, Until: 12:00, 1, Until: 08:00, 0, Until: 16:00, 1, Until: 14:00, 0.75, Until: 18:00, 1, Until: 17:00, 0.8, Until: 17:00, 1, Until: 24:00, 0, Until: 18:00, 0.5, Until: 18:00, 0.25, For: Weekends AllOtherDays, Until: 24:00, 0, Until: 24:00, 0, Until: 24:00, 0, For: Weekends Holidays AllOtherDays, For: Weekends AllOtherDays, Through: 22 Aug, Until: 24:00, 0, Until: 24:00, 0, For: Weekends Holidays, Through: 22 Aug, Through: 22 Aug, Until: 24:00, 0, For: Weekdays SummerDesignDay WintFor: Weekdays SummerDesignDay, For: AllOtherDays, Until: 08:00, 0, Until: 09:00, 0, Until: 09:00, 0, Until: 16:00, 1, Until: 12:00, 0.75, Until: 17:00, 0.65, Until: 17:00, 0.8, Until: 14:00, 0.5, Until: 24:00, 0, Until: 24:00, 0, Until: 17:00, 0.75, Through: 15 Dec, For: Weekends Holidays AllOtherDays, Until: 24:00, 0, For: Weekdays SummerDesignDay WinterDesig Until: 24:00, 0, For: Weekends AllOtherDays, Until: 08:00, 0, Through: 15 Dec, Until: 24:00, 0, Until: 18:00, 1, For: Weekdays SummerDesignDay WintThrough: 15 Dec, Until: 24:00, 0, Until: 08:00, 0, For: Weekdays SummerDesignDay, For: Weekends AllOtherDays, Until: 16:00, 1, Until: 07:00, 0, Until: 24:00, 0, Until: 17:00, 0.8, Until: 08:00, 0.25, Through: 31 Dec, Until: 18:00, 0.5, Until: 09:00, 0.5, For: Weekends Holidays, Until: 24:00, 0, Until: 12:00, 1, Until: 24:00, 0, For: Weekends Holidays AllOtherDays, Until: 14:00, 0.75, For: AllOtherDays, Until: 24:00, 0, Until: 17:00, 1, Until: 09:00, 0, Through: 31 Dec, Until: 18:00, 0.25, Until: 17:00, 0.5, For: Weekends Holidays, Until: 24:00, 0, Until: 24:00, 0; Until: 24:00, 0, For: Weekends AllOtherDays, For: AllOtherDays, Until: 24:00, 0, Until: 09:00, 0, Through: 31 Dec, Until: 17:00, 0.025, For: Weekdays SummerDesignDay, Until: 24:00, 0; Until: 09:00, 0, Until: 12:00, 0.7, Until: 14:00, 0.4, Until: 17:00, 0.7, Until: 24:00, 0, For: Weekends AllOtherDays, Until: 24:00, 0; 263 Table 32: Schedule Used for Design Builder Simulation Model (Temperature) Temperature Schedules: 0 ‐ off, 1 ‐ on, 0.5 ‐ Setback Cool_AHU ‐ 1,3,4 Cool_AHU ‐ 2Heat_AHU‐1,3,4 Heat_AHU‐2 Schedule:Compact, Schedule:Compact, Schedule:Compact, Schedule:Compact, Uni_ClassRm_Cool, VKC_Cool_AHU2, Uni_ClassRm_Heat, VKC_Heat_AHU 2, Temperature, Temperature, Temperature, Temperature, Through: 10 Jan, Through: 10 Jan, Through: 10 Jan, Through: 10 Jan, For: Weekdays SummerDesignDay, For: Weekdays SummerDesignDay, For: Weekdays SummerDesignDay WinterDesignDayFor: Weekdays SummerDesignDay WinterDesignDay, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 22:00, 1, Until: 22:00, 1, Until: 22:00, 1, Until: 22:00, 1, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 24:00, 0.5, For: Saturday, For: Weekends, For: Saturday, For: Weekends, Until: 07:00, 0.5, Until: 24:00, 0, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 18:00, 1, For: Holidays, Until: 18:00, 1, For: Holidays, Until: 24:00, 0.5, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 07:00, 0.5, For: Sunday, Until: 17:00, 1, For: Sunday, Until: 17:00, 1, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 17:00, 1, For: WinterDesignDay AllOtherDays, Until: 17:00, 1, For: AllOtherDays, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 24:00, 0.5, For: Holidays, Through: 15 May, For: Holidays, Through: 15 May, Until: 07:00, 0.5, For: Weekdays SummerDesignDay, Until: 07:00, 0.5, For: Weekdays SummerDesignDay WinterDesignDay, Until: 17:00, 1, Until: 07:00, 0.5, Until: 17:00, 1, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 23:00, 1, Until: 24:00, 0.5, Until: 23:00, 1, For: WinterDesignDay AllOtherDays, Until: 24:00, 0.5, For: AllOtherDays, Until: 24:00, 0.5, Until: 24:00, 0.5, For: Weekends, Until: 24:00, 0.5, For: Saturday, Through: 15 May, Until: 24:00, 0, Through: 15 May, Until: 07:00, 0.5, For: Weekdays SummerDesignDay, For: Holidays, For: Weekdays SummerDesignDay WinterDesignDayUntil: 18:00, 1, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 23:00, 1, Until: 17:00, 1, Until: 23:00, 1, For: Sunday, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 07:00, 0.5, For: Saturday, For: WinterDesignDay AllOtherDays, For: Saturday, Until: 17:00, 1, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 18:00, 1, Through: 22 Aug, Until: 18:00, 1, For: Holidays, Until: 24:00, 0.5, For: Weekdays SummerDesignDay, Until: 24:00, 0.5, Until: 07:00, 0.5, For: Sunday, Until: 07:00, 0.5, For: Sunday, Until: 17:00, 1, Until: 07:00, 0.5, Until: 22:00, 1, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 17:00, 1, Until: 24:00, 0.5, Until: 17:00, 1, For: AllOtherDays, Until: 24:00, 0.5, For: Weekends, Until: 24:00, 0.5, Until: 24:00, 0.5, For: Holidays, Until: 24:00, 0, For: Holidays, Through: 22 Aug, Until: 07:00, 0.5, For: Holidays, Until: 07:00, 0.5, For: Weekdays SummerDesignDay WinterDesignDay, Until: 17:00, 1, Until: 07:00, 0.5, Until: 17:00, 1, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 17:00, 1, Until: 24:00, 0.5, Until: 22:00, 1, For: WinterDesignDay AllOtherDays, Until: 24:00, 0.5, For: AllOtherDays, Until: 24:00, 0.5, Until: 24:00, 0.5, For: WinterDesignDay AllOtherDays, Until: 24:00, 0.5, For: Weekends, Through: 22 Aug, Until: 24:00, 0.5, Through: 22 Aug, Until: 24:00, 0.5, For: Weekdays SummerDesignDay, Through: 15 Dec, For: Weekdays SummerDesignDay WinterDesignDayFor: Holidays, Until: 07:00, 0.5, For: Weekdays SummerDesignDay, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 22:00, 1, Until: 07:00, 0.5, Until: 22:00, 1, Until: 17:00, 1, Until: 24:00, 0.5, Until: 23:00, 1, Until: 24:00, 0.5, Until: 24:00, 0.5, For: Saturday, Until: 24:00, 0.5, For: Saturday, For: AllOtherDays, Until: 07:00, 0.5, For: Weekends, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 18:00, 1, Until: 24:00, 0, Until: 18:00, 1, Through: 15 Dec, Until: 24:00, 0.5, For: Holidays, Until: 24:00, 0.5, For: Weekdays SummerDesignDay WinterDesignDay, For: Sunday, Until: 07:00, 0.5, For: Sunday, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 17:00, 1, Until: 07:00, 0.5, Until: 23:00, 1, Until: 17:00, 1, Until: 24:00, 0.5, Until: 17:00, 1, Until: 24:00, 0.5, Until: 24:00, 0.5, For: WinterDesignDay AllOtherDays, Until: 24:00, 0.5, For: Saturday, For: Holidays, Until: 24:00, 0.5, For: Holidays, Until: 07:00, 0.5, Until: 07:00, 0.5, Through: 31 Dec, Until: 07:00, 0.5, Until: 18:00, 1, Until: 17:00, 1, For: AllDays, Until: 17:00, 1, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 07:00, 0.5, Until: 24:00, 0.5, For: Sunday, For: WinterDesignDay AllOtherDays, Until: 17:00, 1, For: AllOtherDays, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 24:00, 0.5; Until: 24:00, 0.5, Until: 17:00, 1, Through: 15 Dec, Through: 15 Dec, Until: 24:00, 0.5, For: Weekdays SummerDesignDay, For: Weekdays SummerDesignDay WinterDesignDayFor: Holidays, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 23:00, 1, Until: 23:00, 1, Until: 17:00, 1, Until: 24:00, 0.5, Until: 24:00, 0.5, Until: 24:00, 0.5, For: Saturday, For: Saturday, For: AllOtherDays, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 24:00, 0.5, Until: 18:00, 1, Until: 18:00, 1, Through: 31 Dec, Until: 24:00, 0.5, Until: 24:00, 0.5, For: AllDays, For: Sunday, For: Sunday, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 17:00, 1, Until: 17:00, 1, Until: 17:00, 1, Until: 24:00, 0.5; Until: 24:00, 0.5, Until: 24:00, 0.5, For: Holidays, For: Holidays, Until: 07:00, 0.5, Until: 07:00, 0.5, Until: 17:00, 1, Until: 17:00, 1, Until: 24:00, 0.5, Until: 24:00, 0.5, For: WinterDesignDay AllOtherDays, For: AllOtherDays, Until: 24:00, 0.5, Until: 24:00, 0.5, 264 APPENDIX C: INFORMATION OBTAINED FROM FMS Table 33: Areas of VKC Rooms on First Floor, Courtesy FMS (USC) , 2011 Room Number Space Type Area (sft) '' 'CORRIDOR' 1085 '' 'CORRIDOR' 1090 '' 'CORRIDOR' 640 '' 'CORRIDOR' 384 '' 'ENTRANCE' 378 '' 'ENTRANCE' 378 '100' 'CLASSROOM' 765 '101' 'CLASSROOM' 492 '102' 'CLASSROOM' 679 '103' 'SEMINAR RM' 227 '104' 'SEMINAR RM' 303 '105' 'CLASSROOM' 386 '106' 'CLASSROOM' 386 '107' 'CLASSROOM' 386 '108' 'CLASSROOM' 386 '109' 'CLASSSROOM' 385 '110' 'CLASSROOM' 366 '111' 'CLASSROOM' 419 '112' 'OFFICE' 446 '113' 'OM JC' 4 '114' 'OM JC' 10 '130' 'STUDY' 1529 '132' 'OFFICE' 204 '150' 'CLASSROOM' 764 '151' 'CLASSROOM' 492 '152' 'SEMINAR' 677 '153' 'SEMINAR RM' 227 '154' 'SEMINAR RM' 457 '155' 'CLASSROOM' 463 '156' 'CLASSROOM' 937 '157' 'CLASSROOM' 465 '158' 'CLASSROOM' 464 '160' 'CLASSROOM' 384 '161' 'CLASSROOM' 386 '162' OM VEST' 18 '163' 'OM JC' 17 '164' 'WOMENS' 173 '165' 'VEST' 28 '166' 'MENS RM' 188 FIRST FLOOR 265 Table 34: Areas of VKC Rooms on Second Floor, Courtesy FMS (USC) , 2011 Room Number Space Type Area (sft) '' 'CORR' 1093 '' 'BRIDGE' 167 '' 'BRIDGE' 167 '' 'CORR' 1062 '' 'CORRIDOR' 1147 '' 'LOBBY' 291 '' 'LOBBY' 291 '200' 'CLASSROOM' 450 '201' 'CLASSROOM' 471 '202' 'CLASSROOM' 307 '203' 'CLASSROOM' 464 '204' 'SEMINAR RM' 307 '205' 'CLASSROOM' 464 '206' 'CLASSROOM' 383 '207' 'CLASSROOM' 466 '208' 'CLASSROOM' 307 '209' 'CLASSROOM' 386 '210' 'CLASSROOM' 464 '211' 'CLASSROOM' 465 '213' 'COMP LAB' 432 '214' 'OFF' 134 '214A' 'OFFICE' 91 '214B' 'OFF' 96 '215' 'OM JC' 10 '216' 'OM JC' 28 '255' 'CLASSROOM' 307 '256' 'CLASSROOM' 462 '257' 'CLASSROOM' 386 '258' 'CLASSROOM' 464 '259' 'CLASSROOM' 307 '260' 'CLASSROOM' 465 '261' 'CLASSROOM' 463 '263' 'OFFICE' 328 '263A' 'OFFICE' 89 '263B' 'OFFICE' 94 '263C' 'OFFICE' 77 '263D' 'OFFICE' 188 '264' 'OM VEST' 19 '265' 'OM JC' 18 '266' 'WOMENS RM' 173 '267' 'VEST' 114 '268' 'MENS RM' 122 '280' 'OM TELE' 21 SECOND FLOOR 266 Table 35: Areas of VKC Rooms on Third Floor, Courtesy FMS (USC) , 2011 Room Number Space Type Area (sft) '' 'RECEPTION' 167 '' 'CORRIDOR' 1298 '' 'CORRIDOR' 1288 '' 'CORRIDOR' 1032 '300' 'TRAIN' 428 '300B' 'OFFICE' 171 '301' 'OFFICE' 226 '301A' 'OFFICE' 112 '301B' 'OFFICE' 118 '302' 'OFFICE' 105 '303' 'OFFICE' 113 '304' 'OFFICE' 109 '305' 'OFFICE' 117 '307' 'OFFICE' 105 '308' 'OFFICE' 113 '309' 'OFFICE' 109 '310' 'OFFICE' 117 '312' 'OFFICE' 115 '313' 'OFFICE' 107 '368' 'OFFICE' 95 '368A' 'OFFICE' 151 '368B' 'OFFICE' 104 '369' 'OFFICE' 107 '370' 'OFFICE' 110 '371' 'OFFICE' 113 '371A' 'STORE' 20 '372' 'OFFICE' 113 '373A' 'OFFICE' 116 '373B' 'OFFICE' 113 '373C' 'OFFICE' 113 '373D' 'STUDENTS' 253 '374' 'AV RM' 110 '375' 'LOUNGE' 146 '376' 'OFFICE' 113 '376A' 'STORE' 20 '377' 'OFFICE' 152 '378' 'OFFICE' 206 '379' 'CONF' 226 '379B' 'OFFICE' 105 '379C' 'OFFICE' 118 '380' 'OFFICE' 248 '381A' 'OFFICE' 113 '381B' 'OFFICE' 113 '382' 'OFFICE' 435 '382A' 'WORK RM' 166 '383' 'OFFICE' 107 '384' 'OFFICE' 152 '385' 'OFFICE' 109 '386' 'OFFICE' 160 '387' 'STORE' 21 THIRD FLOOR 267 Table 36: VKC Lighting Inventory (08/122/00) obtained from FMS, 2011 Proposed Ballast Proposed Lamp Quan Type Quan. Type 1 ROOF 0 1.00 NO WORK 1 *250W HPS 300.0 2 ROOF 1 0.00 1 TW15ECON 17.0 3 ROOF 1 0.00 1 TW15ECON 17.0 4 STAIR 2 3 1.00 EL2/32IS 2 FBO32/741 25.5 5 STAIR 2 1 1.00 EL2/32IS 2 FO17/741 15.5 6 368 6 1.00 EL3/32IS 3 FO32/741 25.3 7 368A 2 1.00 EL3/32IS 3 FO32/741 25.3 8 381 4 1.00 EL4/32IS 4 FO32/741 25.5 9 381B 2 1.00 EL4/32IS 4 FO32/741 25.5 10 391A 2 1.00 EL4/32IS 4 FO32/741 25.5 11 373 4 2.00 EL2/32IS 4 FO32/741 25.5 12 373E 4 2.00 EL2/32IS 4 FO32/741 25.5 13 373D 2 2.00 EL2/32IS 4 FO32/741 25.5 14 373C 2 2.00 EL2/32IS 4 FO32/741 25.5 15 373B 2 2.00 EL2/32IS 4 FO32/741 25.5 16 373A 2 2.00 EL2/32IS 4 FO32/741 25.5 17 373A 1 2.00 EL2/32IS 4 FO32/741 25.5 18 379 2 1.00 EL4/32IS 4 FO32/741 25.5 19 379A 2 1.00 EL4/32IS 4 FO32/741 25.5 20 379B 2 1.00 EL3/32IS 3 FO32/741 25.3 21 379C 2 1.00 EL3/32IS 3 FO32/741 25.3 22 382 2 1.00 EL4/32IS 4 FO32/741 25.5 23 382 10 0.50 EL4/32IS 2 FO32/741 25.5 24 382A 2 1.00 EL4/32IS 4 FO32/741 25.5 25 382A 3 1.00 EL4/32IS 4 FO32/741 25.5 26 382 2 1.00 EL4/32IS 4 FO32/741 25.5 27 386 2 1.00 EL4/32IS 4 FO32/741 25.5 28 387 1 1.00 EL2/32IS 2 FBO32/741 25.5 29 385 2 1.00 EL4/32IS 4 FO32/741 25.5 30 383 2 1.00 EL4/32IS 4 FO32/741 25.5 31 380 4 1.00 EL4/32IS 4 FO32/741 25.5 32 378 4 1.00 EL3/32IS 3 FO32/741 25.3 33 375 2 1.00 EL4/32IS 4 FO32/741 25.5 34 377 2 1.00 EL4/32IS 4 FO32/741 25.5 35 376A 1 1.00 EL2/32IS 2 FBO32/741 25.5 36 376 2 1.00 EL4/32IS 4 FO32/741 25.5 37 374 2 1.00 EL4/32IS 4 FO32/741 25.5 38 370 2 1.00 EL4/32IS 4 FO32/741 25.5 39 372 2 1.00 EL4/32IS 4 FO32/741 25.5 40 371A 1 1.00 EL2/32IS 2 FBO32/741 25.5 41 371 2 1.00 EL4/32IS 4 FO32/741 25.5 42 369 2 1.00 EL4/32IS 4 FO32/741 25.5 43 365 2 1.00 EL4/32IS 4 FO32/741 25.5 44 367 2 1.00 EL4/32IS 4 FO32/741 25.5 Fix. Quan Location Line Prop. Watts VKC BUILDING LIGHTING INVENTORY (08/12/00) 268 Table 37: Air Balance Report of Air Handling Unit (AHU) - 1 & 3, Courtesy FMS (USC) , 2011 269 Table 38: Air Balance Report of Air Handling Unit (AHU) - 2, Courtesy FMS (USC) , 2011 270 Table 39: Air Balance Report of Air Handling Unit (AHU) - 4, Courtesy FMS (USC) , 2011 271 Figure 436: Submittal of VKC Pumps, Courtesy FMS (USC) , 2011 272 Figure 437: Submittal of VKC Pumps, Courtesy FMS (USC) , 2011 273 Figure 438: Submittal of VKC Pumps, Courtesy FMS (USC) , 2011 274 Figure 439: Condensate Return Unit Submittal, Courtesy FMS (USC) , 2011 275 Figure 440: Condensate Return Unit Submittal, Courtesy FMS (USC) , 2011 276 Figure 441: Water Coils Submittal, Courtesy FMS (USC) , 2011 277 Figure 442: Air Filter used in VKC, Courtesy FMS (USC) , 2011 278 Figure 443: Variable Speed Drive installed at VKC, Courtesy FMS (USC) , 2011 279 Figure 444: Variable Frequency Drive Specifications, Courtesy FMS (USC) , 2011 280 Table 40: Centralized Hot Water Details, Courtesy FMS (USC) , 2011 281 Table 41: Exhaust Fan Details, Courtesy FMS (USC), 2011 282 Table 42: Supply Air Fan Details, Courtesy FMS (USC), 2011 283 Table 43: Sump Pumps Details, Courtesy FMS (USC), 2011 284 Table 44: Fire/House Pumps Details, Courtesy FMS (USC), 2011

Abstract (if available)

Abstract With the current rapid depletion of non-renewable resources to generate power, energy conservation and on site generation have become the most critical aspects of the equation. Buildings should be so designed or retrofitted in order to generate its own electricity and cater to its own demand. ❧ This thesis looks as the ways in which we can do a post occupancy analysis of an existing institutional building of about 95,000 square feet that was built in 1960’s in order to reduce usage and approach a Zero Net Energy goal. This case study building is Von Kleinsmid Centre (VKC) which is located at the heart of USC (University of Southern California). It is challenging to retrofit an existing institutional building because of its complexity and make it achieve a ‘Zero Net Energy’ goal. ❧ All the roadblocks, real life delays, software limitations that had to be overcome to achieve this result are explained in this thesis. The Zero Net Energy goal was achieved by calibrating energy model to the utility data of the building, providing various energy efficiency measures and generating on-site electricity.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Net zero energy building: the integration of design strategies and PVs for zero-energy consumption

PDF

"Watts per person" paradigm to design net zero energy buildings: examining technology interventions and integrating occupant feedback to reduce plug loads in a commercial building

PDF

Net-zero cultural urbanism: the implementation of traditional and cultural net-zero urban housing design in Lagos

PDF

Energy simulation in existing buildings: calibrating the model for retrofit studies

PDF

Facade retrofit: enhancing energy performance in existing buildings

PDF

Zero peak homes: designing for zero electric peak demand in new single family residential buildings sited in California climate zone 10

PDF

Post occupancy energy evaluation of Ronald Tutor Hall using eQUEST; computer based simulation of existing building and comparison of data

PDF

Digital tree simulation for residential building energy savings: shading and evapotranspiration

PDF

Life cycle assessment: existing building retrofit versus replacement

PDF

Building retrofitting evaluation: Energy savings and cost effectiveness of building retrofits on Graduate Art Studios at the University of California, Los Angeles

PDF

Energy use intensity estimation method based on building façade features by using regression models

PDF

ctrl+z: exploring the effects of undoing retrofits to pre-war buildings in Los Angeles

PDF

District energy systems: Studying building types at an urban scale to understand building energy consumption and waste energy generation

PDF

Night flushing and thermal mass: maximizing natural ventilation for energy conservation through architectural features

PDF

Tilted glazing: angle-dependence of direct solar heat gain and form-refining of complex facades

PDF

External bracing of existing buildings to reduce drift under lateral load

PDF

An analysis of building component energy usage: a data driven approach to formulate a guideline

PDF

Façade retrofit performance evaluation: Predicting energy conservation potential from renovations to the building envelope

PDF

Mitigating thermal bridging in ventilated rainscreen envelope construction: Methods to reduce thermal transfer in net-zero envelope optimization

PDF

Studies in preliminary design of fenestration: balancing daylight harvesting and energy consumption

Asset Metadata

Creator Singh, Sukreet (author)

Core Title Zero net energy institutional building

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Publication Date 05/05/2012

Defense Date 05/11/2012

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag calibration,design builder,Energy,energy conservation measures,net zero energy,OAI-PMH Harvest,ZNE

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Schiler, Marc (committee chair), Carlson, Anders (committee member), Simmonds, Peter (committee member)

Creator Email sukreets@usc.edu,sukreetsingh@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-32977

Unique identifier UC11289043

Identifier usctheses-c3-32977 (legacy record id)

Legacy Identifier etd-SinghSukre-779.pdf

Dmrecord 32977

Document Type Thesis

Rights Singh, Sukreet

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA