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Watt Hall energy management system implementation initiative

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Watt Hall energy management system implementation initiative

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Content WATT HALL ENERGY MANAGEMENT SYSTEM IMPLEMENTATION INITIATIVE by Shih-Hsin Lin A Thesis Presented to the FACULTY OF THE SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF BUILDING SCIENCE August 2008 Copyright 2008 Shih-Hsin Lin ii Acknowledgments Thanks to Prof. Thomas Spiegelhater for his direct and giving me the opportunity to join the EMS team to enrich my research. Thanks to Prof. Marc Schiler for his direct and kindly helping me to solve problems and elucidating unclear point, which made me learn a lot during the research process. Thanks to Prof. Christoph Kapeller for his valuable information and direct. Thanks to Ms. Karen Mozes for her valuable suggestions and direct. Special thanks to Laura Haymond for her helping with my grammar during the whole research period. I really appreciated. Special thanks to J.B. Cleveland for his help in the EMS project. Finally, thanks to every members in MBS 2008. You are my best teachers and friends. iii Table of Contents Acknowledgments............................................................................................................... ii List of Tables ....................................................................................................................... v List of Figures ................................................................................................................... vii Abstract ............................................................................................................................. xv Chapter 1 Introduction ................................................................................................... 1 Chapter 2 Research Background ................................................................................... 7 2.1 Architecture 2030 ............................................................................................... 7 2.2 Environmental Management System (ISO 14001/14004) ................................11 2.3 EMS Implementation of USC Architecture School ......................................... 13 Chapter 3 Research Scope, Objectives, Procedure and Method .................................. 18 3.1 Research Scope ................................................................................................ 18 3.2 Research Objectives ......................................................................................... 21 3.3 Research Procedure and Method ...................................................................... 25 Chapter 4 Building Information and Building Information Model of Watt Hall ........ 34 4.1 Pre-building factor ........................................................................................... 35 4.2 Building History ............................................................................................... 44 4.3 Occupancy Zoning & Occupancy Schedule Profile of Watt Hall .................... 48 4.4 Envelope Profile of Watt Hall .......................................................................... 50 4.5 Non-User Related Internal Heat Gain Profile of Watt Hall ............................. 58 4.6 HV AC System of Watt Hall .............................................................................. 60 4.7 Watt Hall Energy Consumption Profile............................................................ 63 4.8 Summary of Current Watt Hall Energy Consumption Problems and Improvement Directions ........................................................................................ 76 Chapter 5 Indoor Thermal Comfort Research of Watt Hall ......................................... 80 5.1 Introduction of the Indoor Thermal Comfort Research ................................... 80 5.2 Data Acquisition System (DAS) Installation of Watt Hall ............................... 82 5.3 Data Logger Results Analysis ........................................................................ 107 5.4 Summary ........................................................................................................ 135 iv Chapter 6 Building Energy Consumption Simulation Models .................................. 137 6.1 eQUEST Simulation Model of Watt Hall ....................................................... 139 6.2 Ecotect Model ................................................................................................ 148 6.3 Summary ........................................................................................................ 155 Chapter 7 Conclusion & Future Work ....................................................................... 156 Bibliography ................................................................................................................... 161 Appendix A The Room Schedule of Watt Hall .............................................................. 166 Appendix B Space Operation Schedules of Watt Hall ................................................... 172 Appendix C Envelope Material Details and Revit Input of Watt Hall .......................... 180 Appendix D The Construction Materials Input and Calculated U-Values in eQUEST and ECOTECT Model of Watt Hall ........................................... 202 Appendix E Lighting Schedule of Watt Hall ................................................................. 222 Appendix F Devices Survey of Watt Hall ..................................................................... 233 Appendix G Cal-ARCH Benchmarking Results ............................................................ 240 Appendix H Data Acquisition System (DAS) Plans and Details of Watt Hall .............. 246 Appendix I The Normalization Details of the Data Acquisition System ..................... 256 v List of Tables Table 2-1 EMS Costs and Benefits (Stapleton, Glover, & Davis) .................................... 12 Table 4-1 Floor area of Watt Hall ..................................................................................... 47 Table 4-2 Operating hours per day of the main activity area in Watt Hall ....................... 49 Table 4-3 Envelope profile of Watt Hall (ASHRAE Standard 90.1-2004, 2004) ............. 57 Table 4-4 Interior Lighting Power Densities of Watt Hall compare with the space-by space method of ASHRAE 90.1-2004 (ASHRAE Standard 90.1-2004, 2004) ................................................................................................................ 60 Table 4-5 Summary of Energy Star and Cal-Arch Attributes (Matson & Piette, 2005) ... 69 Table 4-6 Watt Hall’s Cal-ARCH Benchmarking results comparison .............................. 71 Table 4-7 The total CO 2 emission of Watt Hall and MCB (Cleveland J. , 2008) ............. 74 Table 5-1 Phase I DAS recording note ............................................................................. 95 Table 5-2 Phase II DAS recording notes ........................................................................... 97 Table 5-3 Temperature normalization constant of each data loggers .............................. 104 Table 5-4 Relative Humidity normalization constant of each data loggers .................... 106 Table 5-5 Data logger location and time of recorded peak data ..................................... 109 Table 5-6 Definitions of thermal comfort factors and related terms (ASHRAE 55-2004, 2004) .............................................................................................................. 126 Table 6-1 Tested Strategies in eQUEST.......................................................................... 144 Table B- 1 The Schedule list of Watt Hall ...................................................................... 172 Table B- 2 The list of the operation schedules of each room in Watt Hall ..................... 172 Table C- 1 Main construction materials of Watt Hall ..................................................... 180 vi Table C- 2 The details, Revit model input and thermal properties of Watt Hall’s envelope materials (AC Martin Partners, Inc, 2005; Killingsworth, Brady & Associates, Architects Inc., 1971; Lin, Revit Model of Watt Hall, 2008; Lin, The eQUEST Model of Watt Hall, 2008) ...................................................... 182 Table D- 1 The materials input and calculated U-values in eQUEST and ECOTECT model of Watt Hall (Lin, The ECOTECT Model of Watt Hall, 2008; Lin, The eQUEST Model of Watt Hall, 2008) ...................................................... 202 Table E- 1 Lighting Fixtures of Watt Hall ...................................................................... 230 vii List of Figures Figure 1-1 US Building energy & electricity consumption (Architecture 2030, 2006-2007); (Energy Information Administration, 2008) ................................. 2 Figure 2-1 USC School of Architecture EMS Baseline Research frame work................. 14 Figure 3-1 Research scope of this study in the EMS Baseline Research project ............. 18 Figure 3-2 Research scope in EMS Implementation Process Guideline (EPA, 2000) ..... 20 Figure 3-3 1995 Typical Commercial Buildings Delivered Energy End-Use (D & R International, 2007) ......................................................................................... 23 Figure 3-4 Research process and frame work ................................................................... 25 Figure 4-1 The Project Information input in the Revit model of Watt Hall (Lin, Revit Model of Watt Hall, 2008) ............................................................................... 36 Figure 4-2 Watt Hall site context from Google Earth and USC campus map (Google Earth, 2007; University of Southern California, 2008) ................................... 37 Figure 4-3 The Google Earth SketchUp model of Watt Hall in Google Earth (Google Earth, 2007; Lin, SketchUp Model of Watt Hall, 2008) ................................. 37 Figure 4-4 Watt Hall’s climate zone from Google Earth (California Energy Commission, 2006 ; Google Earth, 2007) ....................................................... 39 Figure 4-5 Weather average for Los Angeles, California. The data is based on 43years historical data from Weatherbase.com (Canty and Associates LLC, 2008) .... 40 Figure 4-6 Average precipitation for Los Angeles, California. The data is based on 43years historical data from Weatherbase.com (Canty and Associates LLC, 2008) ................................................................................................................ 40 Figure 4-7 Heating & cooling degree days of California Climate Zone 9. The data is from U.S Energy Efficiency and Renewable Energy, Department of Energy . 41 Figure 4-8 Relative humidity for California Climate Zone 9 (Pacific Gas and Electric Company, 2008) .............................................................................................. 42 viii Figure 4-9 Extra-terrestrial radiation for California Climate Zone 9 (Pacific Gas and Electric Company, 2008) ................................................................................. 42 Figure 4-10 Prevailing wind speed & direction for California Climate Zone 9 (Pacific Gas and Electric Company, 2008) ................................................................... 43 Figure 4-11 Northwest view of Watt Hall construction phases illustration (Lin, Revit Model of Watt Hall, 2008) ............................................................................... 45 Figure 4-12 Construction phases input in the Revit model of Watt Hall (Lin, Revit Model of Watt Hall, 2008) ............................................................................... 46 Figure 4-13 Watt Hall floor plan & area (Lin, Revit Model of Watt Hall, 2008) ............. 47 Figure 4-14 Occupancy plan of Watt Hall (Lin, Revit Model of Watt Hall, 2008) .......... 48 Figure 4-15 The exterior of Watt Hall ............................................................................... 50 Figure 4-16 Location of Watt Hall glass façade type 1: 1 st & 2 nd floor studio façade ...... 52 Figure 4-17 Details of Watt Hall glass façade type 1: 1 st & 2 nd floor studio façade (Killingsworth, Brady & Associates, Architects Inc., 1971; Lin, Revit Model of Watt Hall, 2008) ............................................................................... 52 Figure 4-18 Watt Hall glass façade type 2: 1 st & 2 nd floor Office S façade ...................... 53 Figure 4-19 Details of Watt Hall glass façade type 2: 1 st & 2 nd floor studio façade (Killingsworth, Brady & Associates, Architects Inc., 1971; Lin, Revit Model of Watt Hall, 2008) ............................................................................... 53 Figure 4-20 Watt Hall glass façade type 3: 3rd Floor office façade ................................. 54 Figure 4-21 Details of Watt Hall glass façade type 3: 3rd floor office façade (AC Martin Partners, Inc, 2005; AC Martin Partners, Inc, 2005; Lin, Revit Model of Watt Hall, 2008) ............................................................................... 54 Figure 4-22 The roof detail of Watt Hall causes thermal bridge (AC Martin Partners, Inc, 2005; Lin, Revit Model of Watt Hall, 2008) ............................................ 57 Figure 4-23 Electricity consumption data recorded by FMS, USC from June 1997- December 2007 ................................................................................................ 64 Figure 4-24 Over all electricity consumption pattern recorded by USC FMS ................. 65 Figure 4-25 MBC & SOFAW electricity consumption estimated by Ian McCully (McCully, 2008) .............................................................................................. 67 ix Figure 4-26 Gas consumption data recorded by USC FMS from March 2005-January 2008 ................................................................................................................. 68 Figure 4-27 Energy Start benchmarking results of Watt Hall (ENERGY STAR, 2007) .. 70 Figure 4-28 The results of Cal-Arch benchmarking Watt Hall with all building types in California (CALARCH, 2003) ........................................................................ 72 Figure 4-29 Watt Hall and nearby building energy performance benchmarking by EU Building Performance Certificate from April 2006- March 2007 (Cleveland J. , 2008; Directorate-General for Energy and Transport: The Directive, 2007) ................................................................................................................ 74 Figure 4-30 Watt building energy performance benchmarking by EU Building Performance Certificate from January 2007- December 2007 (Directorate-General for Energy and Transport: The Directive, 2007) ........... 75 Figure 4-31 Design Strategies of Climate Zone 9 (Liggett, Alshaali, Lang, & Milne, 2007) ................................................................................................................ 77 Figure 5-1 DAS Equipment (Lin, DAS Equipment, 2008) .............................................. 82 Figure 5-2 DAS Installation Flow Chart ........................................................................... 85 Figure 5-3 BoxCar3.7 exporting interface (BoxCar, 2002) .............................................. 87 Figure 5-4 Microsoft Excel 2007 Text Import Interface (Microsoft, 2007) ..................... 87 Figure 5-5 Phase I HOBO installation location ................................................................ 94 Figure 5-6 Phase II HOBO installation location ............................................................... 96 Figure 5-7 Phase I data loggers temperature normalization ............................................. 98 Figure 5-8 Phase I data loggers RH normalization ........................................................... 99 Figure 5-9 Phase II data loggers temperature normalization ............................................ 99 Figure 5-10 Phase II data loggers RH normalization ...................................................... 100 Figure 5-11 Phase I normalization: WATB-3 and average comparison .......................... 102 Figure 5-12 Phase I normalization: WAT3-3 and average comparison .......................... 103 Figure 5-13 Phase I all data performance ....................................................................... 107 x Figure 5-14 Phase II all data performance ...................................................................... 108 Figure 5-15 Phase I all data temperature performance from 10/26/07 to 10/31/07 .........110 Figure 5-16 Phase II first floor temperature performance from 01/09/08-01/1 1/08 ........ 111 Figure 5-17 Phase I basement temperature data in November, 2007 ..............................113 Figure 5-18 Phase I basement temperature data from 11/12/07 to 11/15/07 ...................114 Figure 5-19 Phase II basement temperature data in January, 2008 ..................................115 Figure 5-20 Phase I first floor temperature data from 10/26/07-10/31/07 .......................1 17 Figure 5-21 Phase II first floor temperature data from 01/19/08-01/22/08 .....................118 Figure 5-22 Phase II second floor temperature data from 12/01/07-12/10/07 ................ 120 Figure 5-23 Phase II second floor temperature data from 12/10/07-12/31/07 ................ 120 Figure 5-24 WAT3-O location and placement ................................................................ 123 Figure 5-25 Phase I third floor temperature data in November, 2007 ............................ 123 Figure 5-26 Phase I third floor temperature data from 12/01/07 to 12/10/07 ................. 124 Figure 5-27 Phase II third floor temperature data from 12/10/07 to 12/31/07 ............... 124 Figure 5-28 Overall Watt Hall comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) ................... 127 Figure 5-29 Basement spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) ................... 128 Figure 5-30 Basement individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) ............................................................... 129 Figure 5-31 First floor spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) ................... 129 Figure 5-32 First Floor individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) ............................................................... 130 Figure 5-33 Second floor spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) ................... 131 xi Figure 5-34 Second floor individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) ....................................... 132 Figure 5-35 Third floor spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) ................... 133 Figure 5-36 Third floor individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) ............................................................... 134 Figure 6-1 eQUEST Model of Watt Hall ........................................................................ 143 Figure 6-2 Watt Hall preliminary baseline simulation results in eQUEST ..................... 146 Figure 6-3 Total energy consumption of each alternative ............................................... 147 Figure 6-4 Sun path illustration of Watt Hall ECOTECT model (Lin, The ECOTECT Model of Watt Hall, 2008) ............................................................................. 149 Figure 6-5 3 rd floor southeast corner shadow range study (Lin, The ECOTECT Model of Watt Hall, 2008) ........................................................................................ 151 Figure 6-6 Daylighting levels and testing alternatives on the Watt Hall 3 rd floor from ECOTECT model (Lin, The ECOTECT Model of Watt Hall, 2008) ............ 152 Figure 6-7 Shading alternative comparison in ECOTECT (Lin, The ECOTECT Model of Watt Hall, 2008) ........................................................................................ 152 Figure 6-8 Daylighting levels of the model with louver and overhang from ECOTECT model calculation (Lin, The ECOTECT Model of Watt Hall, 2008) ............ 153 Figure 6-9 The simulation impact of 3 rd floor shading ................................................... 154 Figure B- 1 The operation schedules of Watt Hall .......................................................... 177 Figure C- 1 The illustration of the location of the main construction materials in Watt Hall ................................................................................................................ 181 Figure E- 1 Lighting Schedule of Watt Hall (Lin, Revit Model of Watt Hall, 2008) ..... 222 Figure F- 1 Devices Survey of Watt Hall (Lin, Revit Model of Watt Hall, 2008) .......... 233 Figure G- 1 The results of Cal-Arch benchmarking Watt Hall with all building types in California (CALARCH, 2003) ...................................................................... 240 Figure G- 2 The results of Cal-Arch benchmarking Watt Hall with office building types in California (CALARCH, 2003) .................................................................. 241 xii Figure G- 3 The results of Cal-Arch benchmarking Watt Hall with education building type in California (CALARCH, 2003) .......................................................... 242 Figure G- 4 The results of Cal-Arch benchmarking Watt Hall with all building types in California south coast climate (CALARCH, 2003) ...................................... 243 Figure G- 5 The results of Cal-Arch benchmarking Watt Hall with office building types in California south coast climate (CALARCH, 2003) .................................. 244 Figure G- 6 The results of Cal-Arch benchmarking Watt Hall with education building types in California south coast climate (CALARCH, 2003) ......................... 245 Figure H- 1 Data Acquisition System (DAS) plans and schedules of Watt Hall (Lin, Revit Model of Watt Hall, 2008) ................................................................... 246 Figure I- 1 Phase I all data loggers’ temperature normalization data with average ........ 256 Figure I- 2 Phase I WATB-1 temperature normalization data with average ................... 257 Figure I- 3 Phase I WATB-2 temperature normalization data with average ................... 257 Figure I- 4 Phase I WATB-3 temperature normalization data with average ................... 257 Figure I- 5 Phase I WAT1-1 temperature normalization data with average .................... 257 Figure I- 6 Phase I WAT1-2 temperature normalization data with average .................... 257 Figure I- 7 Phase I WAT2-1 temperature normalization data with average .................... 257 Figure I- 8 Phase I WAT2-2 temperature normalization data with average .................... 258 Figure I- 9 Phase I WAT2-3 temperature normalization data with average .................... 258 Figure I- 10 Phase I WAT3-2 temperature normalization data with average .................. 258 Figure I- 11 Phase II all data loggers’ temperature normalization data with average ..... 259 Figure I- 12 Phase II WATB-1 temperature normalization data with average ................ 260 Figure I- 13 Phase II WATB-2 temperature normalization data with average ................ 260 Figure I- 14 Phase II WATB-3 temperature normalization data with average ................ 260 Figure I- 15 Phase II WATB-4 temperature normalization data with average ................ 260 Figure I- 16 Phase II WATB-5 temperature normalization data with average ................ 260 xiii Figure I- 17 Phase II WATB-6 temperature normalization data with average ................ 260 Figure I- 18 Phase II WAT1-1 temperature normalization data with average ................ 261 Figure I- 19 Phase II WAT1-2 temperature normalization data with average ................ 261 Figure I- 20 Phase II WAT1-3 temperature normalization data with average ................ 261 Figure I- 21 Phase II WAT1-4 temperature normalization data with average ................ 261 Figure I- 22 Phase II WAT1-5 temperature normalization data with average ................ 261 Figure I- 23 Phase II WAT1-6 temperature normalization data with average ................ 261 Figure I- 24 Phase II WAT1-7 temperature normalization data with average ................ 262 Figure I- 25 Phase II WAT2-1 temperature normalization data with average ................ 262 Figure I- 26 Phase II WAT2-2 temperature normalization data with average ................ 262 Figure I- 27 Phase II WAT2-3 temperature normalization data with average ................ 262 Figure I- 28 Phase II WAT2-4 temperature normalization data with average ................ 262 Figure I- 29 Phase II WAT2-5 temperature normalization data with average ................ 262 Figure I- 30 Phase II WAT2-6 temperature normalization data with average ................ 263 Figure I- 31 Phase II WAT3-1 temperature normalization data with average ................ 263 Figure I- 32 Phase II WAT3-2 temperature normalization data with average ................ 263 Figure I- 33 Phase II WAT3-3 temperature normalization data with average ................ 263 Figure I- 34 Phase II WAT3-4 temperature normalization data with average ................ 263 Figure I- 35 Phase II WAT3-5 temperature normalization data with average ................ 263 Figure I- 36 Phase II WAT3-6 temperature normalization data with average ................ 264 Figure I- 37 Phase I all data loggers’ RH normalization data with average ................... 264 Figure I- 38 Phase I WAT2-1 RH normalization data with average ............................... 265 Figure I- 39 Phase I WAT2-2 RH normalization data with average ............................... 265 Figure I- 40 Phase I WAT3-2 RH normalization data with average ............................... 265 xiv Figure I- 41 Phase I WAT3-3 RH normalization data with average ............................... 265 Figure I- 42 Phase II all data loggers’ temperature normalization data with average .... 266 Figure I- 43 Phase II WATB-1 RH normalization data with average ............................. 267 Figure I- 44 Phase II WATB-2 RH normalization data with average ............................. 267 Figure I- 45 Phase II WATB-3 RH normalization data with average ............................. 267 Figure I- 46 Phase II WATB-4 RH normalization data with average ............................. 267 Figure I- 47 Phase II WAT1-2 RH normalization data with average .............................. 267 Figure I- 48 Phase II WAT1-3 RH normalization data with average .............................. 267 Figure I- 49 Phase II WAT1-4 RH normalization data with average .............................. 268 Figure I- 50 Phase II WAT1-5 RH normalization data with average .............................. 268 Figure I- 51 Phase II WAT1-6 RH normalization data with average .............................. 268 Figure I- 52 Phase II WAT1-7 RH normalization data with average .............................. 268 Figure I- 53 Phase II WAT2-1 RH normalization data with average .............................. 268 Figure I- 54 Phase II WAT2-2 RH normalization data with average .............................. 268 Figure I- 55 Phase II WAT2-3 RH normalization data with average .............................. 269 Figure I- 56 Phase II WAT2-4 RH normalization data with average .............................. 269 Figure I- 57 Phase II WAT2-5 RH normalization data with average .............................. 269 Figure I- 58 Phase II WAT2-6 RH normalization data with average .............................. 269 Figure I- 59 Phase II WAT3-1 RH normalization data with average .............................. 269 Figure I- 60 Phase II WAT3-2 RH normalization data with average .............................. 269 Figure I- 61 Phase II WAT3-3 RH normalization data with average .............................. 270 Figure I- 62 Phase II WAT3-4 RH normalization data with average .............................. 270 Figure I- 63 Phase II WAT3-5 RH normalization data with average .............................. 270 Figure I- 64 Phase II WAT3-6 RH normalization data with average .............................. 270 xv Abstract As a place to cultivate future architects, the School of Architecture stands in the leading position to demonstrate how to renovate Watt Hall into a carbon-neutral and low-energy-consumption building through the implementation of the ISO14000 Environmental Management System. As a part of the EMS baseline research project led by Thomas Spiegelhalter, this initial study focuses on the Energy Management System. The main work of this study contains as-built data collection, generating a building information model, establishing energy consumption models, measuring and monitoring the indoor environmental comfort performance, and research on energy consumption profiles, and post-occupancy profiles. This study will not only reveal Watt Hall’s current energy performance but also set the baseline and propose feasible energy consumption improvement strategies. The effectiveness of thesis strategies will then be demonstrated through computer modeling, the most effective approaches then used to generate a long-term energy monitoring system and energy management plan. 1 Chapter 1 Introduction Through the rapid development of science and technology humanity continues to progress in a variety of industries ranging from medicine to space exploration. However, in the process of technological advancement great damage to the natural environment has also occurred. Global warming and climate changes have made people aware of the continuing degradation of the environment at the hands of humans. Being suddenly conscious of the limited natural resources available, people have begun to seek out solutions in an attempt to redeem the current situation. As a result of this sudden awareness, sustainability has been thrust forward into the international spotlight. One of the first responses to this emerging global crisis was the Earth Summit, a United Nations Conference on Environment and Development (UNCED) held in Rio de Janeiro in June of 1992. In the United States alone buildings account for 65% of electricity consumed, 36% of energy used, 30% of greenhouse gases (GHG) emitted, 30% of raw materials used, 30% of waste output (136 million tons annually), and 12% of potable water consumption (U.S. Green Building Council, 2007). Data from the US Energy Information Administration illustrates that buildings are responsible for almost half (48%) of all energy consumption and GHG emissions annually; globally the percentage is even greater. Seventy-six percent (76%) of all power plant-generated electricity is used just to operate buildings, as illustrated in Figure 1-1 (Architecture 2030, 2006-2007). 2 Figure 1-1 US Building energy & electricity consumption (Architecture 2030, 2006-2007); (Energy Information Administration, 2008) In response to the realization of the significant impact of buildings on the natural environment, individuals around the world came together to form what became known as Architecture 2030. Architecture 2030 developed with the intention of attempting to improve not only the current building environment but to also aid in the reduction of green house gas emissions. By challenging developing professionals through the 2010 Imperative, members of Architecture 2030 called on all related professions and institutions around the world to combine their efforts to improve the industry. The 2010 Imperative is a list of guidelines that challenge educators to complete ecological literacy and transit a carbon-neutral design within their curriculum. The other side of the 2010 Imperative, and an overall objective on Architecture 2030, is to eventually have carbon neutral campuses which teach carbon neutral design. As an echo to this call for reform in the very way architects are taught to design, the School of Architecture of the University of Southern California committed to adopt the 2010 Imperative in the spring 2007. 3 In response to the 2010 Imperative call for more energy efficient design the School of Architecture of the University of Southern California has taken steps to improve not only its curriculum but the very building budding architects are taught in, Watt Hall. Using the ISO14000 Environmental Management Standard as a means of implementing an Environmental Management System (EMS), USC School of Architecture formed the EMS baseline research team (USC AR-EMS). The USC AR-EMS, started in spring 2007, is under the leadership of Thomas Spiegelhalter with an awarded grant by the USC Future Fuels and Energy Initiative. One of the objectives of this team is to retrofit Watt Hall so as to lower current greenhouse gas emissions and energy consumption. Operating as a vanguard of the university, this project will set a precedent and demonstrate how retrofitting existing buildings can create a more sustainable environment. The EMS baseline research is divided into seven categories with which to proceed. 1. Outdoor Environment Management (OEM); 2. Purchasing and Procurement Service (PPS); 3. Energy Management (EM); 4. Indoor Environmental Quality (IEQ); 5. Water Management (WM); 6. Waste Management and Recycling (WMR); 7. Green Practices Committee Communication Efforts (GPCCE). 4 Among these categories, the EM system produces the most immediate results by directly revealing the building’s current energy performance. This thesis primarily concentrates on the Energy Management and Indoor Environment Quality initiatives, which includes collecting as-built building information, generating a building information model (BIM) from the as-built, collecting indoor comfort data, and researching energy consumption profiles, post-occupancy schedules, as-built HV AC system performance, and evaluating alternatives by performing energy consumption simulation models of Watt Hall through the previously generated BIM. Since Watt Hall is an existing building whose current status is the result of multiple architects’ input and three construction phases over a span of more than thirty years, collecting baseline as-built information has proven to be a complicated procedure. For information regarding the building envelope, there is lack of consistent building documentation of each of the three construction phases. As a result, the newest BIM modeling software, Revit, was adopted in this study to organized and document current as-built construction information as identified by USC AR-EMS team. A prime example of the complications arising from the Watt Hall’s three construction phases can be observed in the existing HV AC system. Currently, Watt Hall’s chilled water supply is connected to the university’s centrally distributed chilled water loop. Watt Hall’s heat supply is also gleaned from a central system provided by the university which links the entire campus. As a direct result of varying construction phases, varying parts of Watt Hall have varying control mechanisms. Improper documentation 5 compounds this issue by providing no clear method of discerning the existing HV AC system. The lack of separated meters by which to divide the existing Watt Hall from its neighboring but dependent structures, such as the Wood Shop, further complicates matters regarding the calculation of Watt Hall’s current energy consumption profile. Once an accurate energy consumption profile has been acquired, an imperative ingredient to setting goals for future improvement, this study moves on to not only compare current energy consumption levels with the ASHREA 90.1-2004 standard, but also employs the European standard, Building Energy Performance Certificate, to reveal Watt Hall’s performance on the world scale. This demonstrates the resolution of USC AR-EMS to not merely lower energy consumption of Watt Hall but to go on to achieving a carbon-neutral environment for upcoming designers of carbon neutral building. With regards to monitoring and research into indoor environmental comfort, this phase of the study begins by collecting data from multiple data loggers stationed to monitor main activity areas. This data is then employed to generate a clear understanding of the indoor temperature range during the course occupancy. By comparing the recorded data of each selected zones in Watt Hall and with USC weather station data, the indoor environment temperature and humidity profile can be compiled. This profile can later be used to develop a better understanding of the demands on Watt Hall’s interior environment and individual HV AC control strategies. Once the demands have been isolated, instead of using less-grounded brainstorming or completely cost-oriented comparisons, this study employs computer-aided tools to 6 generate solutions to meet these demands in a more energy efficient manner. To evaluate these more sustainable alternatives this study relies on two popular energy simulation tools, eQUEST and ECOTECT. Because the results of the computer simulations provide life cycle costs of individual strategies along with the embodied energy costs, these results can be used to isolate the more reliable options. The intention of employing computer models as the dominant means of determining appropriate solutions for Watt Hall is to set a precedent for how effective energy efficient strategies with the highest gain with the lowest embodied energy can be isolated without incurring the actual cost of construction. This research not only sets the energy demand baseline of Watt Hall but goes on to set the future goals and action required for a carbon neutral building. This study also proposes feasible energy consumption improvement strategies while establishes a long-term energy monitoring system and energy management plan. Once the proposed strategies are in place the monitoring system used previously can be employed to verify the effectiveness of each implemented strategy as they are implemented. Continued observation of building performance is also an important part of the Environmental Management Systems. 7 Chapter 2 Research Background 2.1 Architecture 2030 Greenhouse gas (GHG) emissions, a well-known major contributor to global warming, have become the benchmark of dealing with rapid climate change. Buildings account for a significant portion of GHG released into the atmosphere every year. According to the data from the U.S. Energy Information Administration, buildings are responsible for almost half (48%) of all global-warming-causing greenhouse gas (GHG) emissions annually. Furthermore, 76% of all electricity generated by US power plants goes to supply the Building Sector. Therefore, it appears evident that immediate action in the Building Sector is essential if a significant reduction in GHG is desired. In response to this growing crisis in the year 2002 a non-profit non-partisan independent organization entitled Architecture 2030 was established by architect Edward Mazria. Architecture 2030’s declared goal was to rapidly reduce the GHG emissions of the US and global Building Sector by changing the way buildings are planned, designed, and constructed. With these changes in place, the non-profit organization also expects the new Building Sector to become a key part in the solution to the global climate changes. (2030, 2006-2007) 8 2.1.1 2010 Imperative In order to achieve the long term goals of easing the persisting pressure of global warming and depletion of the world’s resources, Architecture 2030 declared that it is imperative to start immediately. One of the first areas of focus is schools in an attempt to bridge the interdependent relationship of ecology and design, which has yet to be integrated into the majority of curricula. The resulting ecological literacy can therefore become a central spirit of design education and meets the immediate and future Architecture 2030 challenges. The 2010 Imperative calls upon the whole design community to adopt the following: “Beginning in 2007, add to all design studio problems that: the design engage the environment in a way that dramatically reduces or eliminates the need for fossil fuel. By 2010, achieve complete ecological literacy in design education, including: design / studio; history / theory; materials / technology; structures / construction; professional practice / ethics. By 2010, achieve a carbon-neutral design school campus by: Implementing sustainable design strategies (optional - LEED Platinum / 2010 rating); generating on-site renewable power; purchasing green renewable energy and/or certified renewable energy credits (REC's, Green Tags), 20% maximum.” (Architecture 2030, 2006-2007) 9 2.1.2 2030 Challenge Scientists suggest that to avoid catastrophic climate change, the reduction of global greenhouse gas (GHG) in the next 10 years is crucial. The Architecture 2030 initiative thus focuses on the change of planning, design, and construction of buildings. Research claims that if within the next ten years human beings can successfully slow and reverse the GHG, global warming can be kept under one degree Celsius (°C) above today's level. To accomplish this task immediate action must be taken and global efforts from all the communities required. “To accomplish this, Architecture 2030 has issued The 2030 Challenge, asking the global architecture and building community to adopt the following targets: All new buildings, developments and major renovations shall be designed to meet a fossil fuel, GHG-emitting, energy consumption performance standard of 50% of the regional (or country) average for that building type. At a minimum, an equal amount of existing building area shall be renovated annually to meet a fossil fuel, GHG-emitting, energy consumption performance standard of 50% of the regional (or country) average for that building type. The fossil fuel reduction standard for all new buildings shall be increased to: 60% in 2010; 70% in 2015; 80% in 2020; 90% in 2025; Carbon-neutral in 2030 (using no fossil fuel GHG emitting energy to operate). These targets may be accomplished by implementing innovative sustainable design strategies, generating on-site renewable power and/or purchasing (20% maximum) renewable energy and/or certified renewable energy credits.” (Architecture 2030, 2006-2007) 10 2.1.3 The 2010 Imperative adoption of School of Architecture, University of Southern California As a place to cultivate future architects, the School of Architecture at the University of Southern California committed to adopt the 2010 Imperative in the spring of 2007. To meet the challenge of the 2010 Imperative the USC School of Architecture set out to set a precedent in how to retrofit an existing environment, transforming it into a sustainable environment and standing as a benchmark institute for the whole nation. With the lofty ambition of lowering GHG emissions and achieving carbon-neutrality, the school began the process of retrofitting Watt Hall by turning to the Environmental Management System regulated by ISO 14001/14004. 11 2.2 Environmental Management System (ISO 14001/14004) As an International Organization for Standard (ISO), ISO has formed a series of regulated standards to protect current environments for all kinds of industry to follow and apply. “The ISO 14000 family addresses Environmental Management. This means what the organization does to: minimize harmful effects on the environment caused by its activities, and to achieve continual improvement of its environmental performance.” (ISO, 2008) “ISO 14000 is a series of standards, and guideline reference documents, which cover the following: Environmental Management Systems, Environmental Auditing, Eco Labeling, Life Cycle Assessment, Environmental Aspects in Product Standards, Environmental Performance Evaluation. The ISO 14000 standards reflect different aspects of environmental management. The following list outlines the broad coverage of each: Environmental Management Systems: 14001, 14002, 14004 Environmental Auditing: 19011 Environmental Labeling: 14020, 14021, 14022, 14023, 14024, 14025 Life Cycle Assessment: 14040, 14041,14042, 14043 Evaluation of Environmental Performance: 14031 ” (ISO14001, 2003) “ISO 14001 is an internationally accepted specification for an environmental management system (EMS). It specifies requirements for establishing an environmental policy, determining environmental aspects and impacts of products/activities/services, planning environmental objectives and measurable targets, implementation and operation of programs to meet objectives and targets, checking and corrective action, and management review.” (ISO14001, 2003) Because ISO 14000 is an internationally accepted standard of regulations yielding a reduced impact on the environment, the application of ISO 14000 on Watt 12 Hall was decided to help improve the building’s environment and provide the following benefits: “An EMS can help you to comply with regulations more consistently and effectively. It also can help you identify and capitalize on environmental opportunities that go beyond compliance. …..A commitment to preventing pollution is a cornerstone of an effective EMS and should be reflected in an organization’s policy, objectives and other EMS elements. Examples throughout this Guide show how organizations have used an EMS to prevent pollution.” (Stapleton, Glover, & Davis) Table 2-1 EMS Costs and Benefits (Stapleton, Glover, & Davis) POTENTIAL COSTS POTENTIAL BENEFITS Internal > Staff (manager) time > Other employee time (Note: Internal Labor costs represent the bulk of the EMS resources expended by most organizations) External > Potential consulting assistance > Outside training of personnel > Improved environmental performance > Enhanced compliance > Prevention of pollution/ resource conservation > New customers/ markets > Increased efficiency/ reduced costs > Enhanced image with public, regulators, lenders, investors >Employee awareness of environmental issues and responsibilities 13 2.3 EMS Implementation of USC Architecture School “The University of Southern California is a large consumer of resources. Annually, USC consumes an average of 155 million kWh of electricity, 4 million therms of natural gas, and 270 million gallons of water. As a major research institution, it is the responsibility of USC to develop efficient ways in which these resources can be efficiently conserved and the university’s environmental impact reduced. In general, no research institutions in modern society are better able to catalyze the necessary transition to a measure able sustainable world than universities. They have access to both the leaders of tomorrow and the leaders of today.” (Spiegelhalter, USC FFEII Future Fuels and Energy Initiative Applied Research, 2006) In response to the adoption of the 2010 Imperative, the USC School of Architecture has embarked to improve its educational environment where future generations of architects are taught. After a preliminary evaluation, the school decided to improve its environment by adhering to the ISO 14000 provided standard for the implementation of the Environmental Management System (EMS). Thus, the Environmental Management System Research Project of USC School of Architecture (USC AR-EMS) lead by Thomas Spiegelhalter was established. “The Environmental Management Systems (EMS) Method will be the primary tool in this applied research project to help the School of Architecture to identify strategies in order to: (a) minimize how their operations (processes, etc.) negatively affect the environment (i.e. cause adverse changes to air, water, or land); (b) comply with applicable laws, regulations, and other environmentally oriented requirements, and (c) continually improve in the above categories.” (Spiegelhalter, Baseline Environmental Assessment and Feasibility Study for the Implementation of an Environmental Management System (EMS) at the School of Architecture, 2006) 14 USC AR-EMS divided the entire EM S project into seven subcategories. These included Outdoor Environment Management, Purchasing & Procurement Service, Energy Management, Indoor Environmental Quality, Water Management, Waste Management & Recycling, and Facilities & Green Practice Committee Communication Efforts, as illustrated in Figure 2-1. (Spiegelhalter, USC FFEII Future Fuels and Energy Initiative Applied Research, 2006) Figure 2-1 USC School of Architecture EMS Baseline Research frame work “To achieve the objectives set, the environmental aspects (development of a baseline environmental inventory and control sensor monitoring implementation strategy) will be initially quantified in their time changes. In addition there will be a quantitative feasibility study report how environmental sensors and meters installed throughout the different occupancy zones of the buildings and exterior landscape will provide climate related data on a daily basis. Web pages based on building performance and resource consumption data will be used as a unique learning opportunity to visualize, in real-time, the input and output flows of energy, water, and cycling of matter that are necessary to control better and 15 support the built environment, and reduce the environmental impact. An assessment of the environmental performance of the School of Architecture in the day-to-day campus operations will be first conducted. Specific assessment indicators of environmental performance need to be developed in seven areas of the School of Architecture operations: 1. OUTDOOR ENVIRONMENT MANAGEMENT: Sensor data use for potential natural resource facility operation strategies: climate conditions, temperature, sun, wind, humidity, etc.; Landscape Planning and Management, USC Community Landscaping, Land Use, Grounds Maintenance Additives and Techniques, Plants and Habitats, New Plantings. 2. PURCHASING AND PROCUREMENT SERVICE: Procurement Services Environmental Goals. Environmental Purchasing Guide Green Preferred Suppliers, Green Contracting, Packaging Reduction Requirements, Representative Items Purchased, Facilities Management Services Purchasing. 3. ENERGY MANAGEMENT: Energy Consumption Monitoring for Electricity, Heating and Cooling: Types of Energy Consumed, Annual Total Energy Consumption, Energy Conservation strategies, Reduce end-use campus energy consumption, Implementation and operation costs of Meters and adjustable occupancy sensors, Renew-able Energy Purchases and Energy Generating Systems Implementation Strategies, Payback and Currencies of Renewable Energy, Energy Generation Emission (Greenhouse Gas Reduction, etc.) 4. INDOOR ENVRIRONMENTAL QUALITY: CO2 Monitoring, Natural Ventilation Efficiency, Daylight and Views Efficiency, Low-Emitting Materials, Indoor Chemical and Pollutant Source Control, Controllability of HV AC, Lighting Systems, and Thermal Comfort. 5. W ATER MANAGEMENT: Annual Water Use, Water Meters, Annual Water Used by Buildings with Metering Data, Cost of Water Used Wastewater Generation and Disposal Annual total wastewater generated, Cost of Wastewater, Amount of wastewater reused, Number of wastewater discharges monitored for flow, Storm water Indicators: Runoff Generated at the School Storm water Management and Reuse, Number of storm water discharges monitored for quality. 16 6. W ASTE MANAGEMENT AND RECYCLING: Non-hazardous Solid Waste: Standard Solid Waste, Construction and Demolition Waste, Hazardous Waste, Chemical Waste, Computers, Biological Waste, Non-Landfill Disposal: Recycled Materials Composted Materials, Reused Materials 7. FACILITIES AND GREEN PRACTICES COMMITTEE COMMUNICATION EFFORTS: Number of Environmental Outreach Initiatives and Events, Green Practices Publications, Campus Communications, Outreach, Green Practices Committee. The seven selected indicators will provide different perspectives on environmental performance in each of the areas noted. Additional criteria (such as transportation data) will be used in the development of indicators were that quantitative indicators be preferred , and that data for the indicator should be readily obtainable in order to ensure the feasibility of updating the indicators from year to year. The research goals of the project were to develop a set of specific environmental performance indicators for The School of Architecture (and later in phase 2 for the wider USC campus), and to obtain the baseline data for these indicators. As more data are gathered, the Facilities and Green Practices Committee will perform analysis in order to set further specific goals for improvement of environmental performance based on the indicator data. This process will take place with attention to different indicator areas at different times depending on adequacy of data and in accordance with the priorities of the Green Practices Committee. The main body of the Baseline Environmental Assessment and Resource Control System Implementation report includes chapters for each area of campus operations investigated. Each chapter begins with a table listing of the indicators for the particular area of focus, and the baseline values of the indicators in the 2007fiscal year a description of each indicator will then be provided, along with the reasons for inclusion of the indicator. In order to facilitate updating of the indicators from year-to-year, a detailed assessment update guide that provides instructions for how to obtain the data will be provided. The indicators will be updated each summer and at the end of the fiscal year by student interns working under the supervision of the School’s Environmental Management Coordinator in collaboration with input from the USC Facilities Management Services (FMS). The baseline assessment report will not include subjective measures such as lifestyle, human health, social issues, or cultural effects. This can be a further research subject. 17 Expected Results and Impact The School of Architecture EMS Baseline Assessment and Resource Monitoring Implementation Feasibility Study will identify quantitative measures and applied research strategies that provide direct or indirect indicators of environmental performance improvements related to the following seven areas: 1. Outdoor Environment Management; 2. Purchasing and Procurement Service; 3. Energy Management; 4. Indoor Environmental Quality; 5. Water Management; 6. Waste Management and Recycling; 7. Green Practices Committee Communication Efforts The capability of monitoring and understanding the use of energy and material flows at the school of Architecture will not only be beneficial to the users of the building, but it will also serve as a stimulating starting point for the University to implement these EMS-systems in other buildings. By monitoring the energy and resource flows that go in and out at various parts of the School, the University can find the most efficient ways of conditioning the buildings. In the long run, the ability to monitor the use of resources over an extended period of time will allow for the University to provide Energy Passports for all of the buildings on the campus. Now, Building Energy Passports are widely used throughout Europe to provide additional real estate information and equivalence to the Kyoto Protocol Ratification. Energy Passports will identify which buildings within the University have the most sustainable energy and resource flows, and will help to motivate building user to implement and maintain sustainable practices. Furthermore, once control and monitoring sensors are successfully installed the building users will be able to see all the comfort zone temperatures throughout the building, respond to alarms, trend space temperatures, create user WebPages for remote access allowing set point adjustments, and interface the active HV AC and lighting systems to adjust to varying conditions and energy savings throughout the building.” (Spiegelhalter, Baseline Environmental Assessment and Feasibility Study for the Implementation of an Environmental Management System (EMS) at the School of Architecture, 2006) 18 Chapter 3 Research Scope, Objectives, Procedure and Method 3.1 Research Scope This study is part of the USC School of Architecture EMS Baseline Research project (USC-AR EMS). Of the seven subcategories previously described, this study focuses on the baseline research regarding Energy Management (EM) and Indoor Environment Quality (IEQ), as shown in Figure 3-1. Figure 3-1 Research scope of this study in the EMS Baseline Research project 19 According to the USC AR-EMS project description: “3. ENERGY MANAGEMENT: Energy Consumption Monitoring for Electricity, Heating and Cooling: Types of Energy Consumed, Annual Total Energy Consumption, Energy Conservation strategies, Reduce end-use campus energy consumption, Implementation and operation costs of Meters and adjustable occupancy sensors, Renew-able Energy Purchases and Energy Generating Systems Implementation Strategies, Payback and Currencies of Renewable Energy, Energy Generation Emission (Greenhouse Gas Reduction, etc.) 4. INDOOR ENVRIRONMENTAL QUALITY: CO2 Monitoring, Natural Ventilation Efficiency, Daylight and Views Efficiency, Low-Emitting Materials, Indoor Chemical and Pollutant Source Control, Controllability of HV AC, Lighting Systems, and Thermal Comfort.” (Spiegelhalter, Baseline Environmental Assessment and Feasibility Study for the Implementation of an Environmental Management System (EMS) at the School of Architecture, 2006) In the EM section of this study, the first research focus concentrated on generating profiles for the building envelope, users, and internal heat gains. The next step in understanding existing conditions involved collecting actual electricity and gas consumption bills to reveal current energy demand. After these profiles were generated, all data was then input into a Building Information Model (BIM) using Autodesk’s Revit. Following the model’s completion this study’s focus was to set up a clear building profile for future EMS development. This was accomplished through utilizing two energy consumption simulation models as a means of providing economical and efficient tools to assist future decision making regarding environmental improvement strategies. 20 In the IEQ section of this study thermal comfort research served as the focus. For the data required for this research, data loggers were installed in every major activity zone to monitor temperatures and relative humidity over time. The results of this study provided the current short-term indoor thermal comfort performance of Watt Hall. Despite the short-term constraints of this particular study, a real time monitoring system is an integral component in meeting the requirement s of EMS. The requirements of this study in the EMS baseline research are generated in reference to the procedure of EPA’s Integrated Environmental Management Systems Implementation Guide (EPA, 2000). The main work of study focused on the pink background area in Figure 3-2. Figure 3-2 Research scope in EMS Implementation Process Guideline (EP A, 2000) 21 3.2 Research Objectives The objectives of this study included: 1. Building Data collection and the generation of a Building Information Model of Watt Hall Every building’s unique energy consumption is due to a variety of factors ranging from materials used for construction to the users who inhabit the space. In order to obtain a thorough understanding of Watt Hall all data regarding possible influencing factors was gathered. This included information regarding the envelope materials, space usage, HV AC system, operation schedules, etc. Data yielded from this study was then distilled and organized for future reference. The resulting data from this study was also used to generate a BIM of existing conditions with the use of Revit for future reference and studies. 2. Post Occupancy User Profile Research The dominating factor of energy consumed by a building stems from the demand of the building’s inhabitants. The value of this critical component is subjected to occupant activities, schedule, and operational habits. To acquire these values as they relate to Watt Hall this study turned to the seasonal operation schedule of the school, current and historical enrollment situations for both the School of Architecture and the School of Fine Arts, and operation schedule according to each 22 major activity zone as previously defined. These values were then organized and analyzed to provide a clear understanding of the energy performance of Watt Hall. 3. Building Envelope Thermal Profile Previous researchers have indicated a strong relationship between the properties of a building’s envelope and the energy required to maintain indoor air temperatures within the perceived comfort zone for occupants. Insulation (R-value) of the building envelope in particular has been of great interest as it relates to infiltration and the time lag effect properties of many components of the space. Thus, in order to determine the properties and better understand the thermal performance of the existing building envelope of Watt Hall, the U- and R- values were considered by this study. 4. Internal Heat Gain Profile of Watt Hall Besides envelope properties and occupancy schedule, lighting fixtures and other necessary devices also account for a significant portion of any building’s energy consumption. Therefore, this study generates a table of all the energy-consuming devices in Watt Hall to supply this part of the energy consumption profile. 5. Watt Hall’s Indoor Comfort Data Profile To collect the data needed for this portion of the study, real-time indoor temperature and relative humidity monitoring devices were set up in the main activity areas of Watt Hall. For comparison and analysis purposes the exterior 23 temperatures and humidity as recorded by the USC weather station were also gathered. The resulting analysis of the indoor environment profile was then compared to the ASHRAE standard 55-2004 to help define the deficiencies of Watt Hall’s current mechanical systems. 6. HVAC System and Control Mechanism of Watt Hall The 2007 Building Energy Data Book indicated that energy used for space heating and cooling purposes was responsible for more than 50% of the energy consumed by a building, as illustrated in Figure 3-3. With regards to Watt Hall, as a building designed without natural ventilation for the first two phases, this fact held relative potential. Without natural ventilation, the HV AC system became the dominant medium by which to maintain indoor comfort levels. In response, this study’s scope of research was extended to include the HV AC system profile research of Watt Hall. Figure 3-3 1995 Typical Commercial Buildings Delivered Energy End-Use (D & R International, 2007) 24 7. Building Energy Consumption Profile Research By utilizing information from collected electricity and gas bills as provided by the University of Southern California for Watt Hall, this study generated a profile for current energy consumption levels. Once this profile was acquired this study moved on to compare it to standards provided by both the US and Europe. By comparing it with US and European standard this study not only provided Watt Hall’s current energy consumption profile but began to set up the baseline of for current building energy consumption levels. 8. Watt Hall’s Energy consumption Simulation Models In order to assist decisions regarding future energy consumption improvement strategizing, two energy consumption simulation tools, eQUEST and ECOTECT, were employed. These two tools were used to simulate the current energy performance of Watt Hall and then extrapolate the expected results from possible energy saving strategies. 9. Improvement Suggestions Through analysis of the previous baseline research and energy consumption simulations of Watt Hall, the most effective direction for improvement was isolated. This direction provided the ground work for generating possible suggestions and laid out the foundation for EMS to build on. 25 3.3 Research Procedure and Method In order to achieve the above objectives, this study separated the entire research work into four chief areas with which to proceed, as provided in Figure 3-4. Figure 3-4 Research process and frame work 26 3.3.1 Energy Management Groundwork Research The Groundwork Research is in regards to the collecting of necessary data with which to proceed in the research. This includes the collection of building information, generating profiles for Watt Hall’s post-occupancy, building envelope, and internal heat gains, collection of HV AC relevant data, and establishing the Building Information Model (BIM). Due to Watt Hall’s three phase construction over multiple decades, there was a distinct lack of consistent documentation regarding critical building information such as building materials and mechanical systems. Thus, the initial step for this project was to compile all relevant building information from the architects and engineers involved in Watt Hall’s construction. In response to discrepancies found between provided drawings and the actual building, an as-built study was performed to verify building materials and the configuration of spaces within Watt Hall. The second step was to then taken this information and input it into the BIM tool, Revit, in order generate an organized model of up-to-date building information for future EMS development. One of the critical aspects of this is study was to understand the thermal performance of Watt Hall’s existing building envelope. To accomplish this a compilation of the building envelope types through reference of collected documentation, architectural drawing and as-built building environmental survey was necessary. Through analysis of this data the study was able to select and define 27 typical wall and roof types by which to represent the entire building’s envelope performance for computer simulation purposes. By inputting the characteristics of these selected materials into eQUEST and ECOTECT the thermal properties of the envelope were defined. These properties included R-values, infiltration, and time lag effect. This data was then used to generate the building envelope profile table for Watt Hall. Following the generation of the building envelope profile was the organization of occupancy activities and schedule. For these purposes the study collected the seasonal operation schedule from both the office of the School of Architecture and the office of Fine Arts as these two departments share spaces within Watt Hall. Following current and historical enrollment records, this study went on to analyze the number of occupants and activities of each space. In response to the results of this analysis Watt Hall was divided into various zones defined by location and major activities by users. These ensuing zones were then employed for analyzing research regarding indoor comfort data and internal heat gains. In order to isolate the percentage of energy consumption by Watt Hall’s HV AC system all energy consuming devices in the building had to be catalogued and accounted for. Those devices included lighting fixtures, permanently fixed electronics, computer labs, and other devices which might account for Watt Hall’s energy consumption level. For information with respect to the mechanical systems this study turned to the University of Southern California, engineers, and contractors 28 to obtain the energy consumption profile in the HV AC sector. For information that was unattainable during this research period a clear table was compiled and necessary assumptions made based on observed trends within the building. This data was then employed in defining aspects of the resulting BIM. 3.3.2 Energy Consumption Baseline Research In order to acquire a baseline by which to compare research result the first step was to collect the electricity and gas bills for Watt Hall from the University of Southern California. The next step was to compare the actual energy consumption of Watt Hall to recorded US and European buildings performances to obtain a better understanding of current expectations regarding building energy performance. For the US building energy consumption comparison, this study relied on the data base provided by the Energy Information Administration. By comparing the energy consumed by Watt Hall to that of other like buildings in the US this study revealed Watt Hall’s perceived energy performance. In addition to comparing total energy consumption levels, this study also compared the building envelop, HV AC, and the lighting of Watt Hall to the ASHREA standard 90.1-2004.Since the purpose of ASHREA standard 90.1-2004 is to provide requirements for energy-efficient design, this analysis was done to obtain a better understanding Watt Hall’s energy performance in the context of energy efficiency (ASHRAE Standard 90.1-2004, 2004). 29 For the European building energy consumption comparison this study applied the Building Performance Certificate template to evaluate Watt Hall’s current energy consumption. This approach was chosen because the Building Performance Certificate is a requirement of the EU Directive 2002/91/EC on the energy performance of buildings. “The Directive 2002/91/EC (EPBD, 2003) of the European Parliament and Council on energy efficiency of buildings ("Energy Performance of Buildings Directive", EPBD) was adopted, after a lively discussion at all levels and with overwhelming support from Member States and the European Parliament, on 16th December 2002 and came into force on 4th January 2003. This Energy Performance of Buildings Directive (EPBD) is considered a very important legislative component of energy efficiency activities of the European Union designed to meet the Kyoto commitment and respond to issues raised in the Green Paper on energy supply security.” (Directorate-General for Energy and Transport: The Directive, 2007) The above comparison not only provided Watt Hall’s perceived energy performance on the International scale, but also provided a means of calibrating a second baseline for the following energy consumption simulation. 3.3.3 Indoor Comfort Data Research In order to understand the current performance of Watt Hall with regards to indoor comfort a Data Acquisition System (DAS) to monitor indoor temperatures and relative humidity was set up in accordance to Procedure for Measuring and Reporting Commercial Building Energy Performance provided by National Renewable Energy Laboratory (NREL) (Barley, M., Pless, & Torcellini, 2005). The 30 DAS was composed of several programmable data loggers and transducers. For the purpose of this study the Onset HOBO and StowAway was selected as the data logger. Through the placement of data loggers in each primary activity zone this study recorded both the temperature and humidity levels of each zone. Through a comparison of the recorded data to exterior temperatures as recorded by the USC weather station and to the ASHREA standard 55-2004, the indoor comfort and mechanical system performances were obtained. 3.3.4 Energy Consumption Simulation Model “Over the past 50 years, literally hundreds of building energy programs have been developed, enhanced, and are in use throughout the building energy community. The core tools in the building energy field are the whole-building energy simulation programs that provide users with key building performance indicators such as energy use demand, temperature, humidity, and costs.” (Crawley, Hand, Kummert, & Griffith, 2005) The U.S. Department has listed 345 building software tools in the Building Software Directory that are available to assist in generating energy efficient building design. “This directory provides information on 345 building software tools for evaluating energy efficiency, renewable energy, and sustainability in buildings. The energy tools listed in this directory include databases, spreadsheets, component and systems analyses, and whole-building energy performance simulation programs. A short description is provided for each tool along with other information including expertise required, users, audience, input, output, computer platforms, programming language, strengths, weaknesses, technical contact, and availability.” (DOE, 2006) 31 Under the energy simulation subcategory in the Building Software Directory, there were 100 software tools listed to assist in entire building energy analysis when this study accessed the web page. For the purposes of this study eQUEST and ECOTECT were selected to simulate the energy consumption performance of Watt Hall. The reason behind the selection of eQUEST as a primary simulation tool was due to its use of DOE-2 as its foundation for calculations. DOE-2 is the most widely recognized building energy simulation program currently available after two decades of continued development and enhancement. (Energy Design Resources, 2006) “DOE-2 is an up-to-date, unbiased computer program that predicts the hourly energy use and energy cost of a building given hourly weather information and a description of the building and its HV AC equipment and utility rate structure. Using DOE-2, designers can determine the choice of building parameters that improve energy efficiency while maintaining thermal comfort and cost-effectiveness. The purpose of DOE-2 is to aid in the analysis of energy usage in buildings; it is not intended to be the sole source of information relied upon for the design of buildings: The judgment and experience of the architect/engineer still remain the most important elements of building design. …………… DOE-2 has been validated by comparing its results with thermal and energy use measurements on actual buildings and with calculations. Detailed information on some of the DOE-2 program validation efforts may be found in the following reports (available from the National Technical Information Service, 5285 Port Royal Road, Springfield, V A 22161) …………… Because it is scientifically rigorous and open to inspection, DOE-2 has been chosen to develop state, national, federal, and international building energy efficiency standards, including: The ASHRAE-90.1 standard for commercial buildings, which is based on thousands of DOE-2 analyses for different building types and climates. The standard is mandatory for new federal buildings, and has been adopted by many states for non-federal buildings. 32 The ASHRAE-90.2 standard for residential buildings, which is based on 10,000 DOE-2 analyses. The State of California standard for commercial buildings (Title 24). Standards for other countries, such as Hong Kong, Saudi Arabia, Kuwait, Singapore, Malaysia, Philippines, Indonesia, Thailand, Switzerland, Brazil, Canada, Mexico and Australia.” (LBNL, 2008) However, DOE-2 in its "raw" standard form is a command line, or "batch"-oriented program. Users then create input files utilizing a text editor with the user’s building description written in DOE-2's building description language (BDL). The learning curve on raw DOE-2 is approximately six to twelve months and reported as still difficult to master unless users take at least one training course and have plenty of time to "practice". (Hirsch, DOE2.com, 2006) Therefore, eQUEST was adopted in this research because it extends DOE-2’s capability by providing a perceived more user-friendly interface. (Hirsch, Software: eQUEST, 2006) The use of ECOTECT as the second energy simulation software was done primarily to extend the research to the international scale. For this purpose ECOTECT was selected because: “As part of ongoing research into automated compliance testing against building regulations, the first set to have been fully implemented in ECOTECT is Part-L of the UK Building Regulations, which deals with the conservation of fuel and power. …………. In terms of Part-L (Part-J in Scotland), ECOTECT is the only building modeling and analysis tool to directly address all aspects of compliance, including the Elemental Method. Obviously the Whole Building Methods for Schools and Hospitals are dictated by Education and NHS guidelines, however the Carbon Performance Rating (CPR) for Office S buildings is supported. As ECOTECT uses the CIBSE Admittance method for its thermal analysis, you can also use these to demonstrate solar control even if you do not comply the prescriptive provisions and for the Carbon Emissions Method. As ECOTECT can export to 33 any other thermal analysis and simulation tools, it is significantly easier to apply the Carbon Emissions Method as this is by far the most flexible option.” (squ1, 2008) “CIBSE is the standard setter and authority on building services engineering. It publishes Guidance and Codes which are internationally recognised as authoritative, and sets the criteria for best practice in the profession. The Institution speaks for the profession and so is consulted by government on matters relating to construction, engineering and sustainability. It is represented on major bodies and organisations which govern construction and engineering occupations in the UK, Europe and worldwide.” (CIBSE, 2008) The input information for both the eQuest and ECOTEC simulation models was acquired through the previously defined ground work research. This study utilized these two energy simulation models to assist in breaking down the energy consumption for Watt Hall. These models were also used to evaluate the effectiveness of future improvement strategies. Through this research a comparison of the effectiveness of these two tools and building energy simulators was also compiled. This comparison proved pertinent with regards to utilizing these tools for future research. 34 Chapter 4 Building Information and Building Information Model of Watt Hall Ray & Nadine Watt Hall was built over three separate construction phases by different architects and engineers supervised under varying directors. Thus, the building has a lack of consist documentation in the form of as-built construction drawings and related information. As part of the EMS baseline research and in order to generate an accurate Building Information Model (BIM) for simulation purposes, all relevant building information had to be acquired and organized. This included but was not limited to all information regarding the current site terrain, location, building geometry, building materials, space usage, space devices, HV AC system, etc. What aspects of the building which proved to be lacking in documentation had to be recorded through on-site observation. Even more, the development of BIM is toward higher interoperability with other further analysis tools. The BIM of Watt Hall was determined as an essential tool for the ground work research and future development of Watt Hall’s Environmental Management System. 35 4.1 Pre-building factor 4.1.1 Location Ray & Nadine Watt Hall is the main building of the University of Southern California School of Architecture and the School of Fine Arts. The building is located on at Latitude 34.019°, Longitude -118.288°, and Altitude 182ft above Sea Level. The context of Watt Hall is the southwest corner of the USC University Park Campus, which is located southwest of downtown Los Angeles, California, USA. Watt Hall’s current address is defined as 850 West 37th Street, Los Angeles, CA 90089. Regarding above information was documented under “Project Information” and “Manage Place and Locations” section in the Revit Model, as shown in Figure 4-1. 36 Figure 4-1 The Project Information input in the Revit model of Watt Hall (Lin, Revit Model of Watt Hall, 2008) 4.1.2 Orientation & Circulation The main entrance of Watt Hall is on the southeast side, where it shares a court yard with Harris Hall. Private University Park Campus streets Bloom Walk and Watt Way frame the Northern borders of Watt Hall providing pedestrian and vehicular service access. Along the south west border lies an open green space used by faculty and students for the occasional school event. Busy urban artery Exposition Boulevard lies just beyond the campus park. See Figure 4-2. This study used Google SketchUp6 as a medium to obtain the terrain information from the Google Earth and then import the terrain into Watt Hall’s Revit model. At the end of this study, the 3D model of Watt Hall was shared to Google Earth, as shown in Figure 4-3. 37 Figure 4-2 Watt Hall site context from Google Earth and USC campus map (Google Earth, 2007; University of Southern California, 2008) Figure 4-3 The Google Earth SketchUp model of Watt Hall in Google Earth (Google Earth, 2007; Lin, SketchUp Model of Watt Hall, 2008) 38 4.1.3 Weather & Climate Watt Hall is considered to be located in a Mediterranean climate area. Mediterranean climate is considered to typically have mild wet winters and warm to hot summers. However, unlike other cities located in Mediterranean climates, Los Angeles benefits from the cooler air courtesy of the Pacific Ocean. Subsequently Los Angeles enjoys cooler summers and warmer winters than would otherwise be expected of a Mediterranean climate (Wikipedia, 2008). According to the Californian climate zone map provided by the California Energy Commission, Watt Hall is located in Climate Zone 9, as shown in Figure 4-4. Zone 9 is defined as the inland valley climate zone and influenced by both coastal and interior weather. The inland winds bring hot dry air, while the marine element provides cool moist air. In comparison to the more coastal climates, Zone 9 experiences warmer summers and cooler winters. (Pacific Gas and Electric Company, 2008) 39 Figure 4-4 Watt Hall’s climate zone from Google Earth (California Energy Commission, 2006 ; Google Earth, 2007) On average there is a recorded difference of 20°F between daily highs and nighttime lows. The average expected temperatures for summer range from 63 °F to 82 °, while winters are expected to stay between 48 °F and 65 °F. The historical average temperature conditions for Los Angeles are illustrated in Figure 4-5 (Wikipedia, 2008). Precipitation for Los Angeles is expected during both winter and spring. On average rainfall is about 15 inches (38 cm) per year. (Wikipedia, 2008) Between November and April this amounts to approximately 2 inches of rain per month. (Pacific Gas and Electric Company, 2008) The historical average precipitation 40 records are shown in Figure 4-6. Annually more than 50% of the time skies are recorded as clear or partly cloudy. Figure 4-5 Weather average for Los Angeles, California. The data is based on 43years historical data from Weatherbase.com (Canty and Associates LLC, 2008) Figure 4-6 Average precipitation for Los Angeles, California. The data is based on 43years historical data from Weatherbase.com (Canty and Associates LLC, 2008) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Record high 90 92 93 96 99 104 103 102 110 104 96 92 Average high 65 66 68 70 73 76 84 82 81 77 73 68 Average low 48 49 50 53 56 58 63 63 61 58 53 50 Record low 28 34 38 41 43 50 54 51 50 46 40 30 20 30 40 50 60 70 80 90 100 110 120 Temperature (*F) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Precipitation (in) 2.7 3.1 2.2 1.3 0.3 0.1 0 0 0.2 0.4 1.1 2.5 0 0.5 1 1.5 2 2.5 3 3.5 Precipitation (in) 41 The following climate characteristics of Watt Hall were according to the data provided by U.S Energy Efficiency and Renewable Energy, Department of Energy. Figure 4-7 below illustrates the heating degree days and cooling degree days of Watt Hall’s location. According to the data provided there is a clear indication that the heating demand on Watt Hall is greater than the cooling demand. Figure 4-8 to Figure 4-10 illustrate the subsequent levels of relative humidity, extra-terrestrial radiation and prevailing wind speeds for California Climate Zone 9. Figure 4-7 Heating & cooling degree days of California Climate Zone 9. The data is from U.S Energy Efficiency and Renewable Energy, Department of Energy 42 Figure 4-8 Relative humidity for California Climate Zone 9 (Pacific Gas and Electric Company, 2008) Figure 4-9 Extra-terrestrial radiation for California Climate Zone 9 (Pacific Gas and Electric Company, 2008) 43 Figure 4-10 Prevailing wind speed & direction for California Climate Zone 9 (Pacific Gas and Electric Company, 2008) 44 4.2 Building History Watt Hall, the common name for Ray & Nadine Watt Hall, was built in 1973 and conceived and designed by Killingsworth, Brady & Associates in cooperation with Sam. T. Hurst, the standing Dean of the USC School of Architecture at the time of initial construction. The typographic plan of open courtyards was derived from local contextual influences. “The new building with open courtyards that reflect the historic heritage of the region has served as a social nucleus and is still the heart of the School today.” (USC School of Architecture, 2007). At the end of the first phase of construction Watt Hall was composed of two stories above ground and a basement level. In 1990, the basement library was expanded below grade to include an atrium reading room with an exterior patio by Ellerbe Becket and Associate Professor Graeme Morland. In 2006, Watt Hall’s capacity was further extended with the addition of a third floor built through the cooperation of A.C. Martin & Partners, Christoph Kapeller and Robert Timme, the standing Dean of the School of Architecture at the time. During the decades between these major modifications to Watt Hall various retrofits and repairs were made as deemed necessary. During the initial gathering of building related information it was discovered that inconsistencies existed in the historical documentary concerning Watt Hall’s three major construction phases. Even information stemming from the same source was discovered to have conflicting versions that didn’t necessarily match up with 45 observed building conditions. Thus, this study referenced the architecture drawings provided by the USC Facilities Management Services and A.C. Martin Partner where appropriate, relying on on-site observation to verify any drawings provided. Once the information was verified to the best of ability through observation, all pertinent building information was then organized and entered into the BIM tool. The result was the generated definition of Watt Hall’s three major construction phases in Revit as illustrated in Figure 4-11 and Figure 4-12. Figure 4-11 Northwest view of Watt Hall construction phases illustration (Lin, Revit Model of Watt Hall, 2008) 46 Figure 4-12 Construction phases input in the Revit model of Watt Hall (Lin, Revit Model of Watt Hall, 2008) Due to inconsistencies in basic information provided regarding floor plans and areas, this study was forced to rely on the Revit model to re-calculate the current floor plan and area square footage. According to the calculation of the Revit Model generated by this study, the floor area of Watt Hall was provided as illustrated in Table 4-1& Figure 4-13. 47 Table 4-1 Floor area of Watt Hall Area Schedule (Gross Area) Name Area Perimeter 1ST FLOOR 17491 SF 660' - 11 27/32" 2ND FLOOR 17811 SF 582' - 0 1/2" 3RD FLOOR 21770 SF 916' – 3 11/16" BASEMENT 23911 SF 662' - 0" MEZZANINE 5984 SF 964' - 9 7/16" TOTAL 86967 SF 3786' - 1 15/32" Figure 4-13 Watt Hall floor plan & area (Lin, Revit Model of Watt Hall, 2008) 48 4.3 Occupancy Zoning & Occupancy Schedule Profile of Watt Hall In order to analyze the energy consumption of Watt Hall an understanding of the spectrum of spaces and their uses within the building was needed. To provide this information a detailed room schedule was generated by Revit as listed in Appendix A and combined with on-site documentation. Through this method it was discovered that the primary space usage of Watt Hall could be divided into the following categories; classroom, corridor, gallery, library, kitchen, office, restroom, storage & mechanical room, and studio, as shown in Figure 4-14. In Watt Hall, studio space clearly occupies the dominant portion of the building. Figure 4-14 Occupancy plan of Watt Hall (Lin, Revit Model of Watt Hall, 2008) 49 According to information provided by both the main office of the School of Architecture and the School of Fine Art, it was determined that Watt Hall’s operating schedule could be categorized into three seasons, Fall & Spring semesters, Summer semester, and winter/spring break as shown in Table 4-2. This operation schedule included the load for lighting, appliances, etc. with regards to each season. However, The HV AC system was not included in the schedule as it was revealed that the entire building of Watt Hall was being conditioned twenty-four hours a day, seven days a week, throughout the entire year. Because of the heavy design studio work load, the operation schedule of studio areas was set to twenty-four hours per day and seven days per week during the Fall and Spring Semesters. During the Summer Semesters, however, studio areas had reduced hours of operation as only half of the studios were occupied. The schedule regarding office spaces remained from 8:00 to 17:00 during the normal week day throughout the entire year. The detailed individual operation schedules were listed in Appendix B. Table 4-2 Operating hours per day of the main activity area in Watt Hall Spring & Fall Summer Winter & Spring Unit: hrs/day M-F Weekend M-F Weekend M-F Weekend Classroom 9 0 4 0 0 0 Corridor 24 24 24 24 24 24 Library 13 8 8 0 8 0 Office 9 0 9 0 9 0 Seminar 6 0 0 0 0 0 Studio 24 24 24 24 24 24 50 4.4 Envelope Profile of Watt Hall “A heavy exposed-concrete savings and loan pavilion that does battle with the 1939 Harris Hall to the west (note that Harris Hall easily wins). The interior public areas of Watt Hall convey a funereal atmosphere—a rather strange environment in which to educate future architects and artists.” (Winter & Gebhard, 2003) The main building envelope Watt Hall is composed of concrete elements such as columns and fins combine with large portions of glazed facade, as shown in Figure 4-15. Figure 4-15 The exterior of Watt Hall 51 Generally, the envelope of Watt Hall can described as three separated façade conditions regarding interior spaces. The first type is the façade on the first and second floor enwrapping studio and class room spaces. The location and the pictures of the first façade type are shown in Figure 4-16. The details of this façade condition are shown in Figure 4-17. The second type glass façade can be found on the first and second floor along the east side of the office spaces, as shown in Figure 4-18. It should be noted that the glass used for both the first and second façade condition was ¼” single pane tempered glass. However no further information regarding product specifics of this glass was available. Therefore, this study assumed the industry standard at the time of construction with regards to input required for the simulation model. 52 Figure 4-16 Location of Watt Hall glass façade type 1: 1 st & 2 nd floor studio façade Figure 4-17 Details of Watt Hall glass façade type 1: 1 st & 2 nd floor studio façade (Killingsworth, Brady & Associates, Architects Inc., 1971; Lin, Revit Model of Watt Hall, 2008) 53 Figure 4-18 Watt Hall glass façade type 2: 1 st & 2 nd floor Office S façade Figure 4-19 Details of Watt Hall glass façade type 2: 1 st & 2 nd floor studio façade (Killingsworth, Brady & Associates, Architects Inc., 1971; Lin, Revit Model of Watt Hall, 2008) 54 Figure 4-20 Watt Hall glass façade type 3: 3rd Floor office façade Figure 4-21 Details of Watt Hall glass façade type 3: 3rd floor office façade (AC Martin Partners, Inc, 2005; AC Martin Partners, Inc, 2005; Lin, Revit Model of Watt Hall, 2008) 55 The third façade condition was found on the third floor perimeter office spaces, shown in Figure 4-20 and Figure 4-21. At this location the façade is composed of aluminum framed double paned glass with operable windows available for natural ventilation. The envelope of the third floor is in contrast with the first two floors which possess no operable windows. Therefore, before the addition of the third floor, Watt Hall was designed to rely solely on the HV AC system to maintain indoor comfort levels. In order to define the building envelope profile of Watt Hall, this study selected twenty primary construction materials and referenced as-built architecture drawings. The U-value of the envelope materials was then calculated by generating the material in eQUEST and ECOTECT, as shown in Appendix C and Appendix D. In order to ensure the input values of the two simulation tools were equal, this study created specific materials and construction layers in both simulation tools. This study ensured the input of materials properties are the same in both simulation tools, such as width, density, specification as to heat transfer, conductivity, etc. However, the default time lag effect, surface roughness and exterior color settings are defined differently in each software. As a result, the calculated U-value from the two separate tools yielded slightly different values. The input details of each tool were listed in Appendix D. 56 As mentioned previously, the distinct lack of information available presented many challenges. One being that some construction details failed to have cross referencing data available to locate the provided details. Thus, for unknown materials, this study was forced to make assumptions based on observation for later use as input for the simulation model for current building situation. Table 4-3 lists the summary of Watt Hall’s envelope properties, and compares those values to the standard value as defined in ASHRAE 90.1-2004. Although it may be considered inappropriate to compare Watt Hall’s existing envelope with current ASHREA standards, as opposed to the standards used at time of construction, such a comparison can aid in the revelation of the current situation of the building and assist the subsequent retrofits. The compared U-value mainly relied on the calculated results of eQUEST. More details of selected materials were listed in Appendix C. According to the table shown, the majority of the envelope’s performance did not meet that standard set by ASHRAE 90.1-2004. Only the third floor demonstrated a better performance. This performance was in part due to the first two floors possessing no insulation and utilizing only single tempered glass. Also, upon further inspection, serious thermal bridges were uncovered, as the roof detail shown in Figure 4-22 illustrates. Other details were listed in Appendix C. While this condition may not be revealed or addressed in the simulation model, consideration for this issue as a source of problematic heat loss was necessary. 57 Table 4-3 Envelope profile of Watt Hall (ASHRAE Standard 90.1-2004, 2004) Material Type Watt Hall ASHRAE Standard 90.1-2004 Climate Zone 3B Opaque Element U-Value Insulation R-Value Max. U-Value Insulation Min. R-Value Roofs Insulation Entirely above Deck 0.092 19 0.063 15.0 Wall, Above-Grade Steel Framed 0.075-0.668 0-11 0.124 13 Wall, Below-Grade Below-Grade Wall 0.595 NR 1.140 NR Floor Mass 0.157-0.403 0 0.137 R-4.2 Doors Swinging 0.820 U-0.7 Fenestration U-Value SHGC Max. U-Value Max. SHGC All/North Fixed Vertical Glazing, 40.1-50.0% of Wall 0.29-0.956 0.29-0.94 1.22 0.17 0.44 Figure 4-22 The roof detail of Watt Hall causes thermal bridge (AC Martin Partners, Inc, 2005; Lin, Revit Model of Watt Hall, 2008) 58 4.5 Non-User Related Internal Heat Gain Profile of Watt Hall The internal heat gained from lighting, equipment, and other appliances is an important contributing factor towards the overall load on Watt Hall’s heating and cooling system which in turn affects the energy consumption profile of the building. In order to understand this aspect of the internal heat gains of Watt Hall, this EMS baseline research team investigated the lighting and appliances of each room at the beginning of the project. However, during this research period, this study found multiple discrepancies between the original survey and current conditions. In response a new survey was taken regarding energy consumption related appliances. In terms of the lighting fixtures of Watt Hall, only the lighting fixtures on third floor have detailed information documented. Apropos of other floors, this study proceeded on-site investigation. Referencing the research of similar products found online, this study assumed the types, lamps, and wattages of the lighting fixtures for the later lighting power density calculation. For the inaccessible spaces this part of study was forced to add “assume” in the lighting fixture description area for the Revit model while waiting for further confirmation. According to the research results of this study, there are 45 different lighting fixtures throughout the whole building, as listed in Table E- 1 in Appendix E. The full lighting Schedule of Watt Hall was listed in Appendix E. Regarding requirements of other appliances in Watt Hall this study relied on wattage consumption information according to product specifications provided by 59 manufacturers of similar products. The assumption values were documented in the Revit model as listed in Appendix F. The documented appliances categories included coffee maker, copier, drill, fan, scanner, PC, plotter, etc. Although not every appliance in the same categories had the exact same performance and electric consumption value, this study assumed a negligible difference between similar appliances, such as coffee makers or printers. Therefore only one consumption value was used for each component of each appliance categories. For example, if three printers were accounted for instead of using a different consumption profile for each printer one value was determined and multiplied by three. This was perceived as the most effective way of handling the appliance section of Watt Hall’s energy profile considering the transient nature of such components. With the purpose of revealing the level of lighting power density (LPD) of Watt Hall, this study compared the lighting power density of Watt Hall with ASHREA standard, as shown in Table 4-4. As indicated, Watt Hall’s LPD of every accounted space is consistently above the standard value. As result there exists significant potential for improvement in the energy consumption profile through a possible different approach to the lighting. 60 Table 4-4 Interior Lighting Power Densities of Watt Hall compare with the space-by space method of ASHRAE 90.1-2004 (ASHRAE Standard 90.1-2004, 2004) Building Space Type LPD of Watt Hall (W/ft 2 ) LPD of ASHRAE (W/ft 2 ) Classroom 2.4 1.4 Corridor 1.3 0.5 Gallery 1.5 1.0 Library Reading 1.6 1.2 Library Stack 2.5 1.7 Kitchen 2.0 1.2 Office 1.5 1.1 Restroom 1.9 0.9 Stor./Mech. 0.37 0.8 Studio 2.1 1.9 4.6 HV AC System of Watt Hall Within the scope of this study, information concerning the existing HV AC conditions proved the most difficult to obtain. This was due to several causes. One critical reason this information was difficult to obtain and verify was because during the multiple construction phases of Watt Hall, the current mechanical system was renovated repeatedly. USC Facilities Management Services (FMS) provided upon request no less than five sets of drawings which demonstrated inconsistencies with the as-built of Watt Hall upon inspection. Secondly, there appeared to be no single source responsible for compiling and organizing construction documents during each of Watt Hall’s many construction phases and renovations. As a result there existed no single set of drawings that accurately recorded the existing conditions of Watt Hall. Prior to this particular study, the EMS Baseline research team requested all available HV AC information from the FMS and IBE Consulting Engineers, the 61 mechanical engineering firm responsible for the design of the 3 rd floor mechanical systems. Preceding this study the only information regarding Watt Hall’s HV AC system that was available on hand were 3 rd floor drawings provided by Prof. Christoph Kapeller. However, these drawings were only in regards to the recently completed 3 rd floor and did not include the HV AC conditions for the entire building. Thus, more information was sought from the two perceived main sources, IBE and FMS. Unfortunately, the knowledgeable parties at IBE were unable to be reached during the course of this study and therefore any information they might have been able to provide could not be obtained and included at this time. However, in December of 2007, Craig Drown from FMS provided the following description of Watt Hall’s current situation; “The main air handler on the 3rd floor does have chilled water cooling coils. The chilled water comes from the campus loop. The heating coils are hot water. The hot water comes from a steam to hot water heat exchanger in the basement. Other than the 3rd floor the air side is a double duct constant volume system. The 3rd floor has 2 zones which are V A V with reheat. I do not have any data on temperature within the building. Other than the 3rd floor the thermostats are pneumatic and have local set points that we do not monitor. The cooling and heating supply air temperature are reset by the return air temperature. The cooling is reset from 55 to 65 and the heating is reset from 85 to 95. I am not sure but I would think the fans are backward curve. As of now the AC system is on 24/7 requested by the users.” (Drown, 2007) While useful in providing basic information regarding the source and settings of Watt Hall’s HV AC system, this description lacked enough detail to be entered into the simulation software. In order to acquire more detailed information necessary for the simulation models, this study attempted to contact the general contractor for Watt 62 Hall’s 3rd floor, a Chad Herrick from Western Allied Corporation Mechanical Contractors/ Engineers. However, they were unable to provide any further information than was previously gathered. Upon continued request, FMS dispatched Mike Guzman, an engineer hired in September of 2007 to provide assistance in the attempt to discern the current systems of Watt Hall. In February of 2008 Mike Guzman completed his analysis of previous sets of HV AC drawings collected over the course of various renovations and multiple construction phases of Watt Hall. At the time of this study Guzman was in the process of compiling accurate documentation of the current HV AC system. Unfortunately, due to the time constraints of this research the results of the second phase of Guzman’s work was not available in time to be included in this study. However, the information will be available to future studies and should be included in any subsequent energy simulations. Generally, it was determined that Watt Hall was cooled primarily by utilizing chilled water and hot water to maintain indoor comfort levels. The chilled water was provided by USC via campus loop, the hot water originating from the steam to hot water heat exchanger located in the basement. Not including the 3rd floor, the air supplied in Watt Hall is through a double ducted constant volume system. Only the 3rd floor was noted as a Variable Air V olume system (V A V).Also, only the system on the 3rd floor possessed Direct Digital Controls (DDC) and was monitored by the campus building management system. Until the current research stage, the AC 63 system of Watt Hall was operated twenty-four hours a day seven days a week due to request made by the School of Architecture. Although the USC Facility Management Services claimed that the HV AC system could be controlled by users, it was discovered that there was no detectable response to local thermostat settings. 4.7 Watt Hall Energy Consumption Profile In addition to exploring the parameters effecting Watt Hall’s energy consumption, it is also important to determine actual energy consumption. Considering that different simulation tools account for different aspects of the energy consumption profile, a comparison of simulated results and actual energy consumption can help to calibrate the model to match the actual building situation. Thus, this study collects actual electricity and gas bills from the university to use for said comparison. The information not only provided the model calibration requirement, but also assisted the energy baseline determination of Watt Hall via the comparison with other buildings in similar climate zones within the US. In addition the study proceeded with a comparison to European standards to reveal the energy consumption level of Watt Hall on the international scale. 64 4.7.1 Current Energy Consumption Data of Watt Hall The electricity bill acquired from the University was from June 1997 to December 2007, as shown in Figure 4-23. The electricity consumption recorded by the University not only included Watt Hall, but also included the wood shop, the MacDonald Becket Center (MBC), located on the south side of Watt Hall and the welding area of the School of Fine Art (SOFAW) on the west side of Watt Hall. As the figure illustrated, higher electricity consumption occurred during Fall and Spring semester when full classes were in session. From the overall electricity consumption pattern shown in Figure 4-24, the recorded electricity consumption of Watt Hall and its related area is in the lower trend. Figure 4-23 Electricity consumption data recorded by FMS, USC from June 1997- December 2007 65 Figure 4-24 Over all electricity consumption pattern recorded by USC FMS An interesting phenomenon is that the completion of the 3 rd floor at the end of 2006 didn’t increase the total electricity consumption of Watt Hall. This following provides possible explanations for this phenomenon. According to Prof. Marc Schiler’s description, a number of lamps were in the original floors changed from incandescent lamp to compact fluorescent lamps. Also, according to the investigation of this study, the previously non-user controlled lighting in the studio was renovated so as to be controlled partially by the users. For example, the studio’s lighting on 1 st and 2 nd floor can be controlled to turn all on or leave two lamps on by the switches. Also, as previously noted by this study, upon initial completion the third floor did not provide user controlled lighting. However, there is a continuous improvement project at the time of this study going on throughout the entire building to rectify this dilemma. While the improvement 66 timeline was unable to be determined in this study, the impact of these renovations is in need of further exploration by future studies. Even though the decreasing energy consumption pattern was very encouraging, there still proved to be significant room for improvement in reducing the energy consumption of Watt Hall. As previously described, the recorded electricity consumption is not only for Watt Hall but also included required power for the adjacent woodshop and welding area. The machinery available for student use in MBC and SOFA was determined to consume a significant amount of electricity that shouldn’t be included in Watt Hall’s electricity consumption profile. Thus, the total Watt Hall energy consumption needed to exclude this part of energy consumption. In order to obtain the electricity consumed by MBC and SOFAW, since there was no separate meter to record the electricity consumption levels, the EMS baseline research team collected the equipment information and the operation schedule of MBC and SOFAW to estimate the consumption of the wood shop. This part of research was done by Ian McCully. According to McCully’s research, the monthly electricity consumed by MBC and SOFAW were as shown in Figure 4-25. When calculating the energy consumption profile for Watt Hall, these values were excluded. 67 Figure 4-25 MBC & SOF AW electricity consumption estimated by Ian McCully (McCully, 2008) Since the 3 rd floor was completed in the end of 2006 any energy consumption information before then could not be utilize to determine the current trends in Watt Hall’s energy consumption. Another issue concerning the data this study was able to obtain concerned the energy requirements for operating Watt Hall’s HV AC system. Due to all utilized chilled water and heating steam were provided by the campus loop, this study was unable to determine if the energy necessary to supply the heating and cooling load of Watt Hall was reflected in the electricity bill. Regarding the gas bill provided by the university, the available data was from March 2005 to January 2008, as shown in Figure 4-26. After continuously tracking with the FMS, the gas consumption was finally determined to only represent the gas consumption of the SOFA kiln area. As the figure shown, the higher consumption month occurred during the end of the Fall and Spring semester. The pattern matched with the higher operation demand during that period. Therefore, for the following 68 energy consumption baseline research of Watt Hall, the recorded gas consumption shouldn’t be included. Figure 4-26 Gas consumption data recorded by USC FMS from March 2005-January 2008 4.7.2 Benchmarking the Energy Consumption of Watt Hall with Energy Start and CAL-ARCH The purpose of benchmarking the energy of Watt Hall was to compare Watt Hall’s energy performance to similar buildings as a means of determining Watt Hall’s current performance levels and aiding in the definition of targeted performance levels. While there were numerous benchmarking tools available to California consumers, it was discovered that only Cal-Arch, http://poet.lbl.gov/cal-arch/, was Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2005 7811 4319 3079 3120 3307 2546 2634 2913 3552 4719 2006 4639 4978 4342 6046 4712 2949 2219 2760 2954 3999 4764 4991 2007 5844 5161 5015 5262 3920 2985 2416 2511 2861 3445 3998 6612 2008 4944 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Therms 69 based solely on California data. The Energy Star, https://www.energystar.gov/ was selected as it is based on nationally available data. Table 4-5 provides a brief summary of the Energy Star and Cal-Arch benchmarking system. Both of them are used to derive the buildings energy use intensity (EUI, kBtu/ft 2 -year). (Matson & Piette, 2005) Table 4-5 Summary of Energy Star and Cal-Arch Attributes (Matson & Piette, 2005) 70 Utilizing the 2007 electricity bill of Watt Hall and the above benchmarking tools this study was able to obtain the current energy performance of Watt Hall. The Energy Start benchmarking of Watt Hall’s input and result were shown in Figure 4-27. Current Energy Start Baseline Rating of Watt Hall was 64. However these results are only based on the 2007 electricity bill and do not include the water and gas consumption. Figure 4-27 Energy Start benchmarking results of Watt Hall (ENERGY STAR, 2007) 71 For the Cal-Arch benchmarking of Watt Hall, this study explored comparisons between different building types in different zone areas. Table 4-6 listed the matrix of the benchmarking methods and the results of each of them. Figure 4-28 illustrated the results of the benchmarking Watt Hall with all building types in California. Others results were listed in Appendix G. Table 4-6 Watt Hall’ s Cal-ARCH Benchmarking results comparison Compare climate zone South Coast California All California with comparable floor area buildings with all buildings with comparable floor area buildings with all buildings Whole Building Electric Whole Building Electric Whole Building Electric Whole Building Electric Annual EUI of Watt Hall 54 kBtu/ft 2 16 kWh/ft 2 54 kBtu/ft 2 16 kWh/ft 2 54 kBtu/ft 2 16 kWh/ft 2 54 kBtu/ft 2 16 kWh/ft 2 All Building Types >58% >52% >50% >48% >35% >47% >38% >48% Office >83% >57% >67% >54% >53% >53% >51% >55% Education NA NA >100% >61% >30% >41% >52% >63% According to the 2007 electricity bill of Watt Hall, the annual energy consumption of Watt Hall was 54kBtu/ft 2 . This number was at least 30% higher than that of other buildings’ annual energy consumption. This is, of course, if the electricity bill was considered a representative of the entire building’s energy consumption. 72 There are, however, are many other building characteristics not included in both Energy Star and Cal-Arch that may affect a building's energy use. Factors such as structure, level of service, and occupancy might be different in the buildings represented on the histogram. While the exact level may differ, both tools agreed in the indication of energy savings potential of Watt Hall. Figure 4-28 The results of Cal-Arch benchmarking Watt Hall with all building types in California (CALARCH, 2003) 73 4.7.3 Benchmarking the Energy Consumption of Watt Hall with EU Energy Performance Certificate According to the energy consumption of Watt Hall, Wood Shop and the SOFA welding area the following analysis was completed by J.B. Cleveland: “According to the European Building Energy Performance Certificate, from April 2007-March 2008 (March Estimated): Watt Hall spent an astronomical $128,429 using 430 kWh/m 2 annually of combined electricity and natural gas. This number is a mere20 kWh/m 2 above the least efficient rating available. The CO 2 emissions indicator demonstrates that this building contributes heavily to global warming, emitting 131.3 kg (CO2)/m2 or 218,313 kg Carbon annually or 0.0135 ton (CO 2 )/ft 2 or 240.6 tons of carbon annually. As noted in the Chart below, the combined W AH, SOFA & MCB entity consumes more resources and creates more Carbon, yet individually WAH consumes and creates more per unit area indicating that WAH itself performs quite poorly and that the SOFA welding area and MCB woodshop are not as detrimental to the overall performance as initially estimated. The recent +/-15,000 ft 2 expansion helps to levy these totals by adding gross square footage to a previously extremely wasteful building. Unexpectedly the gross electrical consumption has diminished over the past 10+ years creating a declining trend in energy use. This data is based off of an as-built survey conducted by the Watt Hall EMS team and the utilities data collected by the School of Architecture from April 2005-March 2007” (Cleveland J. , 2008) 74 Table 4-7 The total CO 2 emission of Watt Hall and MCB (Cleveland J. , 2008) General Energy CO 2 Carbon Space Area Total kWh (therm+kWh) Btu KG Ton Ft 2 M 2 kWh Therms Total Ft 2 M 2 Ft 2 M 2 KG Ft 2 Ton KG Ton Total 71,895 6,614 1,400,074 49,179 2,841,388 40 430 134,728 131 868,585 0.013 957 218,313 241 MCB 06*2,135 196 30,414 0 30,414 14 155 48,562 6713,078 0.007 14.4 3,570 4 WAH 69,760 6,418 1,369,661 49,180 2,810,975 40 438 137,365.5 133 855,508 0.014 943 214,743 237 Figure 4-29 Watt Hall and nearby building energy performance benchmarking by EU Building Performance Certificate from April 2006- March 2007 (Cleveland J. , 2008; Directorate-General for Energy and Transport: The Directive, 2007) The above study, however, used the entire energy consumption of Watt Hall to determine the energy performance level. As previously determined, the energy consumption of the wood shop and SOFA welding area should be excluded in the 75 benchmarking of this particular study. This means the gas consumption should not be included in the energy consumption of Watt Hall. The above study also relied on data dating back to April 2006. Considering the completion schedule of the newly added 3 rd only the electricity consumption in 2007 should be considered as this was the only data provided which included the energy consumption of the 3 rd floor. Thus, the updated EU benchmarking result was shown in Figure 4-30. Although the revised building energy rating of Watt Hall is considered more acceptable, the calculated carbon dioxide emissions of Watt Hall still provide significant room for improvement. Figure 4-30 Watt building energy performance benchmarking by EU Building Performance Certificate from January 2007- December 2007 (Directorate-General for Energy and Transport: The Directive, 2007) 76 4.8 Summary of Current Watt Hall Energy Consumption Problems and Improvement Directions As previously determined, there is significant room for reducing the energy consumption of Watt Hall. In order to explore initial direction for possible improvement strategies, Climate Consultant 3.0 (Liggett, Alshaali, Lang, & Milne, 2007) was employed to isolate the most potentially effective directions of exploration, as shown in Figure 4-31. As indicated, offsetting the “Internal Heat Gain” appears to be most effective strategy available. The second recommendation from Climate Consultant was to utilize “Sun Shading” to reduce the necessary cooling load. While these strategies appear to be the most effective means of reducing the energy consumption of Watt Hall, the economical cost of each strategy is not taken into account by Climate Consultant. The accumulated effect of any strategy is also not taken into consideration. Such as, if one employs the “Sun Shading” strategy to reduce the cooling load, is there an increase in the necessary heating load? Therefore, the potential gain versus cost for each strategy requires further research through thorough energy simulation. 77 Figure 4-31 Design Strategies of Climate Zone 9 (Liggett, Alshaali, Lang, & Milne, 2007) Another aspect of Watt Hall’s energy consumption that Climate Consultant does not account for as a possible means of reducing energy consumption levels is modification made to the occupancy schedule or lighting schedule. In terms of occupancy schedule, despite the demanded long working hours in studio areas, the lighting operation schedule implied the lighting control mechanism need to be improved. Said improvement could then lead to a reduction in the energy needed to supply sufficient lighting levels for users. Another possible path of exploration is with regards to the envelope profile of Watt Hall, predominantly glass design enabling Watt Hall to receive more natural daylight. Theoretically, this might lower the lighting demand of the building during 78 daylight hours. However, due to the specific lighting requirements for the classes offered by of the School of Fine Art on the first floor open window areas are often covered by white board. Therefore an improvement in the available daylight available may not yield the expected results. Another setback for relying on improved daylighting to reduce the energy demand lies in the fact that artificial light controls for the remaining perimeter studios and office areas on the first and second floor are always on even when sufficient daylight was available. On the third floor lights in the perimeter offices are controlled by occupant sensors. If the space is occupied then the lights are on, even if there is enough daylight available. In addition, the direct sunlight in some spaces makes it necessary to rely on artificial lighting in order to reduce glare. Regarding the thermal profile of the envelope, the thermal properties and insulations were determined to be not compliant with ASHREA standard, as listed in Table 4-3. As a result there is an unnecessary increase in the cooling load during the summer and heating load during the winter. Therefore, it appears that exploring the impact of modifying the window design of the first and second floor would be a prudent method of reducing the heating and cooling loads on Watt Hall. 79 With regards to the internal heat gain profile of Watt Hall, the LPD was determined to be unacceptably high when compared to the ASHRAE suggested standard. The combination of the high LPD and the previous mentioned lighting control problems could be a source of great reduction in the energy consumed by Watt Hall. On the subject of the HV AC system of Watt Hall, the system still needs further research to determine its detailed specifications. However, the 24/7 operation hours of the system demand modification. In addition, the temperature thermostats in each area were not observed to have a noticeable effect on controlling the indoor temperature. According to the interview of building occupants, some spaces in Watt Hall were always colder than human comfort temperature. Although this study was unable to determine the efficiency of the HV AC system, the ability to control the operation schedule of the system might lower the energy consumption. The ground work research of Watt Hall revealed several important directions to improve the energy consumption of Watt Hall. However, with each new strategy employed there are possible side effects, both positive and negative. In order to determine the most overall effective solutions more in depth research is required to aid in understanding the impact of each solution. As a method of helping determine the overall impact of each possible means of reducing the energy consumed of Watt Hall, energy simulation were employed. It is only after analyzing the possible costs and benefits of each solution can the proper strategies can be proposed. 80 Chapter 5 Indoor Thermal Comfort Research of Watt Hall 5.1 Introduction of the Indoor Thermal Comfort Research In order to reveal the current indoor thermal comfort performance of Watt Hall, a Data Acquisition System (DAS) was adopted to monitor the indoor thermal comfort levels during this research period in accordance to Procedure for Measuring and Reporting Commercial Building Energy Performance provided by National Renewable Energy Laboratory (NREL) (Barley, M., Pless, & Torcellini, 2005). The DAS was also a requirement in the implementation of the Environmental Management System (EMS). Although the study duration wasn’t long enough to match the three year long monitoring requirement, an initial observation of the indoor thermal comfort performance could be acquired during this phase of the research. While far from complete, this brief energy study provided clear indications that major changes were necessary. This study primarily adhered to the ASHRAE Standard 55-2004 to install the DAS and utilized the comfort definition of ASHRAE Standard 55-2004 to determine the comfort range of Watt Hall. Since the ASHRAE Standard 55-2004 is in close agreement with the ISO Standards 7726 and 7730, adhering to the ASHRAE provided standards can be perceived as simultaneously complying with standards put forth by ISO. In order to determine indoor thermal comfort levels of a space, ASHRAE has put forth a series of combined indoor environmental factors and personal factors that produce 81 thermal environmental conditions acceptable to the majority of occupants within the space. (ASHRAE 55-2004, 2004). In order to obtain validated indoor thermal environmental conditions, the parameters required to be measured according to ASHRAE standard 55-2004 include air temperature, radiant temperature, surface temperature, humidity, and air speed. Occupants’ clothing and activity also need to be considered. However, this phase of the study was only able to measure the temperature and humidity of the main activity zones of Watt Hall. Despite lacking all information deemed critical by ASHRSAE Standard 55-2004, the preliminary results revealed enough information for action to be taken. Through the placement of data loggers in each primary activity zone this study recorded both the temperature and humidity levels of each zone. Through a comparison of the recorded data to exterior temperatures as recorded by the USC weather station and to the ASHREA standard 55-2004 and psychrometric chart, the indoor comfort and mechanical system performances were obtained. 82 5.2 Data Acquisition System (DAS) Installation of Watt Hall 5.2.1 DAS Equipment The DAS was composed of several programmable data loggers and transducers set up to record both temperature and humidity levels of given areas. For the purpose of this study the Onset HOBO and StowAway were selected as said data loggers. While HOBOs are capable of recording both temperature and humidity levels, StowAways only records temperatures. Both were used due to the initial availability of the StowAways before the HOBOs and the limited number of HOBOs accessible for this study. The BoxCar 3.7 software was used to record and interpret the data collected by the data loggers. The list of all equipment used was as follows in Figure 5-1. Figure 5-1 DAS Equipment (Lin, DAS Equipment, 2008) 83 1. HOBO RH/Temp: The HOBO used in this study was a 2-channel temperature and relative humidity data logger. It measured and recorded up to 7,943 readings. The reading rate was user selectable with the ability to be set to sampling intervals being 0.5 seconds to 9 hours, and recording times up to 1 year. Additional features include programmable start time/date, and battery level indication at launch. Operating range: -4°F to +158°F (-20°C to +70°C), 0 to 95% relative humidity, non-condensing, non-fogging, time accuracy: ±1 minute per week at +68°F (+20°C), size/weight: 2.4 x 1.9 x 0.8". (68 x 48 x 19 mm)/approx. 1 oz.(29 gms). The accuracy is ±1.27°F (±0.7°C) at +70°F. Resolution: 0.7°F (0.4°C) at +70°F. The response time still in air: 15 min. (MicroDAQ.com, 2008) 2. StowAway XTI: Each StowAway XTI Data logger was a dual purpose temperature logger that included an internal sensor and a jack for use with an external temperature sensor. When used, the external sensor overrode the internal sensor, increasing the versatility of the logger. Replaceable batteries were used as a power source. Two temperature ranges were available and read in ° C and ° F, with a best accuracy of: ±0.2° C. Dimensions: 1.8" x 1.9" x 0.6". (The Rickly Hydrological Company, 2008) 3. Transducer cable: This cable was used to transfer data from the data-loggers to the computer in use by this study and launch the settings from computer to data loggers. 84 4. USB 1.1 Serial Adapter: This worked as a bridge between USB port and standard RS232 Serial port. This device was for a computer without RS232 Serial port; 5. BoxCar 3.7: This was the software used to provide the basic launching, data read out, plotting, and data exporting capabilities. It provided a user friendly interface, which included the ability to select from predefined sampling intervals (0.5 seconds to 9 hours) or customized intervals, verifying logger operation before launching, synchronizing logger and data shuttle clocks to computer clock, and checking the battery. It also provided a summary of saved data logger files, readout and data analysis, and exporting data files to spreadsheets for further analysis. (MicroDAQ.com, 2008) 85 5.2.2 The Implementation Method & Process of the Watt Hall’s DAS The standard implementation process is illustrated as Figure 5-2. Figure 5-2 DAS Installation Flow Chart 1. Software Installation Load the BoxCar 3.7 and run the setup.exe program. For the computer which needs the USB 1.1 serial adapter, also need to install the adopter driver. Try to launch a data logger to make sure the program can function normally. 2. Normalization Before the installation of the DAS, the data loggers should be normalized. That means each data logger read out value when placed in identical conditions can be compared. If a data logger has a different read out value from the others, its value must be adjusted. This procedure ensures that the final comparison results 86 are not influenced by any discrepancies between individual devices. The normalization procedure was as follows: a. Launch data loggers; b. Set recording time interval to 10 min; c. Delay starting recording time to the same time for every data loggers. This step is for future data analysis convenience; d. Place all the data loggers in the same low temperature place, such as a refrigerator, for 24 hours; e. Relocate the data loggers in the same high temperature place for another 24 hours. f. Use BoxCar3.7 to read out the data from data loggers. g. Export the BoxCar3.7 recorded data file, “.dtf” file, to “.txt” file, as shown in Figure 5-3. h. Open Microsoft Excel 2007, and then import the “.txt” file into Excel, in which all the data loggers data can be generate to further comparison chart, shown as Figure 5-4. i. From the excel comparison chart, find the average reading. Find difference between each data logger and the average. Mark the difference for final monitoring results adjustment. Determine the appropriate adjustment coefficient (if any) for each data logger. 87 Figure 5-3 BoxCar3.7 exporting interface (BoxCar, 2002) Figure 5-4 Microsoft Excel 2007 Text Import Interface (Microsoft, 2007) 88 3. Data Loggers Installation This step was to plan where data loggers should be placed. In this study, locations and the arrangement of data loggers were according to the suggestion of ASHRAE Standard 55-2004 and the 2005 Solar Decathlon Rules and Regulations. 4. Launch Data Loggers Before placing the data loggers in the planned location, this study used BoxCar 3.7 and cable to launch the data loggers. This step was to synchronize each data logger and the computer. As a result all data loggers were set to record at the same time at the same time interval for future convenience in analysis of the recorded data. 5. Read Out Data After a specific time period all data from each data logger was downloaded into the computer via BoxCar3.7 and saved as a data .dtf file. 6. Export File In order to begin the analysis, each .dtf file had to be exported as a .txt file from BoxCar3.7, as shown in Figure 5-3. In the export set up dialog, users can set up the export format. According to the format, users can then import the .txt file into Microsoft Excel. 7. Data Adjustment and Analysis This step was to import the .txt file into Microsoft Excel by using the “Text 89 Import Wizard” to set up the import format of data, as shown in Figure 5-4. After importing all the recorded data, the comparison psychrometric chart can be generated for analysis. Via further comparison of each zoning single day performance and zooming in to observe the temperature performance while the outside temperature is warmer and cooler, then the indoor thermal comfort performance of Watt Hall can be revealed. 5.2.3 Data Loggers Installation 5.2.3.1 Location of Measurements According to ASHRAE standard 55-2004: “7.2.1 Location of Measurements. Measurements shall be made in occupied zones of the building at locations where the occupants are known to or are expected to spend their time. Such locations might be workstation or seating areas, depending on the function of the space. In occupied rooms, measurements shall be taken at a representative sample of occupant location spread throughout the occupied zone. In unoccupied rooms, the evaluator shall make a good faith estimate of the most significant future occupant locations within the room and make appropriate measurements. If occupancy distribution cannot be estimated, then the measurement locations shall be as follows: In the center of the room zone. 1.0m (3.3ft) inward from the center of each of the room’s walls. In the case of exterior walls with windows, the measurement location shall be 1.0m (3.3ft) inward from center of the largest window. 90 In either case, measurements shall be taken in locations where the most extreme values of the thermal parameters are estimated or observed to occur. Typical examples might be near windows, diffuser outlets, corners, and entries. Measurements are to be made sufficiently away from the boundaries of the occupied zone and from any surfaces to allow for proper circulation around measurement sensors with positions as described below. Absolute humidity need to be determined at only one location within the occupied zone in each occupied room or HV AC-controlled zone, provided it can be demonstrated that there is no reason to expect large humidity variations within that space. Otherwise, absolute humidity shall be measured at all locations defined above.” (ASHRAE 55-2004, 2004) Following the defined principle in ASHRAE 55-2004, in this study, data loggers were placed throughout each of the pre-defined zones. For each data logger, the definable enclosure is roughly 500ft 2 . A zone was assigned a single data-logging sensor if its enclosure was less than 500ft 2 and with expected uniform temperature and humidity. A zone was assigned multiple sensors as defined by the testing individual if its enclosure was greater than 500ft 2 , the location was hard to define as singly occupied spaces, or there appeared to be expected lack of uniform temperature or humidity. (The 2005 Solar Decathlon, 2005) However, because of the limitation of the research budget, and the availability of the equipment, this study divided the measuring period into two phases. The first measuring phase was from 10/26/07 to 12/10/07 with 12 data loggers available. The second phase was from 12/10/07-02/15/08 with 25 data loggers available. Generally, the installation of each phase still followed the principle described above, but the recording of main activity zones was the priority of this phase of the research. 91 5.2.3.2 Height of Measurements In terms of the measurements height, according to the ASHRAE 55-2004 description: “7.2.2 Height Above Floor of Measurements. Air temperature and air speed shall be measured at the 0.1, 0.6, and 1.1m (4, 24, and 43 in.) levels for sedentary occupants at locations specified in Section 7.2.1. Standing activity measurements shall be made at 0.1, 1.1, and 1.7m (4, 43, and 67in.) levels. Operative temperature or PMV-PPD shall be measured or calculated at the 0.6m (24in.) level for seated occupants and the 1.1m (43in.) level for standing occupants.” (ASHRAE 55-2004, 2004) However, in this study, because only temperature and humidity were measured and because of the limitation of the data loggers, this study was unable to strictly adhere to the guidelines provided by ASHRAE Standard 55-2004. The data loggers were installed between 4 and 5 ft above the floor, which is near and within the human comfort sensible range. This 4-5 ft range was determined by a precedent used in the 2005 Solar Decathlon Rules and Regulations, in the section on Instrumentation and Monitoring: Design Consideration for Teams. (The 2005 Solar Decathlon, 2005) 92 5.2.4 Data Loggers Monitoring Time Period & Procedure Note Because of the availability of the data loggers, the study separated the monitoring plan into two phases: First monitoring phase: 10/26/07-12/10/07 with 12 data loggers. Second monitoring phase: 12/10/07-02/15/08 with 25 data loggers. Originally, the normal procedure of reading and launching the data is in fixed time duration, such as launching and reading out the data every 30 days. However, the study encountered several reported timing difficulties which resulted in an adjustment when the data were needed. Thus, in the first phase, the data loggers were launched and read out for four times. Each of their duration was 10/26/07-10/31/07, 10/31/07-11/19/07, 11/19/07-12/05/07, and 12/05/07-12/10/07. In the second phases, the data loggers were launched and read out for two times. Each of their duration was 12/10/07-01/18/08 and 01/18/08-02/15/08. Normally, the data loggers are set to record the data in a fixed time interval to provide consistent data for future analysis. Although the study intended to set the time interval of all the data loggers to be 30 min, when examined it became apparent that the actual readout data did not match the original setting. This was attributed to a glitch in the launching software or a compatibility issue residing within the software between it and the data loggers. While the cause was not isolated, the resulting discrepancies between the data loggers in the read outs was taken into consideration. On said result that was discovered and subsequently dealt with was a variation in the set monitoring time period. 93 Each data logger ended up with a different time interval when they should have been synchronized by the software used. As a result a method of compensating for this complication was necessary for the final data organization and analysis. At the conclusion of the study, a comparison was made between the data recorded by the data loggers and external environmental conditions provided by the USC weather station, which had recorded time intervals of one hour. In order to make the monitoring data comparable with the data recorded by the USC weather station, this study had to reorganize all the data into the same time interval. The efficient method appeared to be to adjust the data recorded by USC weather station so as the recorded time interval of the USC weather station matched that of the data loggers. In this process, the study assumed the temperature and the humidity were the same within the hour as the recorded value. 94 5.2.4.1 First Monitoring Phase 10/26/07-12/10/07 The first monitoring phase was from 10/26/07 to 12/10/07. The locations of the data loggers are illustrated in Figure 5-5. More detailed descriptions of each recorded point are listed in Appendix H. Figure 5-5 Phase I HOBO installation location 95 In this phase, there were four recording time period: 10/26/07-10/31/07, 10/31/07-11/19/07, 11/19/07-12/05/07, and 12/05/07-12/10/07. The notes of importance with regards to this time period of testing are listed in Table 5-1. Normalization of this data in accordance to the results of 02/16/08-02/18/08 is discussed in section 5.2.4.3. Table 5-1 Phase I DAS recording note Recording Time Period Time Interval Note 10/26/07-10/31/07 30min WAT3-O no data: out of battery. WATB-3 unable to launch. WAT2-2 no readout: operation mistake 10/31/07-11/19/07 50min WAT2-1 no data: wrong setting WAT3-1 no data: wrong setting WAT3-2 no data: wrong setting WAT3-3 no data: wrong setting 11/19/07-12/05/07 50min WAT3-O no data: out of battery. WAT2-2 start from 19:00 12/05/07-12/10/07 50min WAT3-O no data: out of battery. 96 5.2.4.2 Second Monitoring Phase 12/10/07-02/15/08 The second monitoring phase was from 12/10/2007 to 02/15/08. The installation location of the data loggers are shown in Figure 5-6. More detailed descriptions of each recording point are listed in Appendix H. Figure 5-6 Phase II HOBO installation location 97 In this phase, there were two recording time periods: 12/10/07-01/18/08 and 01/18/08-02/15/08. The notes of importance during this time period are listed in Table 5-2. Normalization of this data was done according to the results from 02/16/08-02/18/08 record. Table 5-2 Phase II DAS recording notes Time Period Time Interval Note 12/10/07-01/18/08 50min WAT3-O out of battery 01/18/08-02/15/08 50min WATB-2 1.5hr WATB-1, WATB-2, WATB-3, WATB-4, WATB-5, WAT1-1, WAT1-2, WAT1-3, WAT1-4, WAT1-5, WAT1-6, WAT1-7, WAT2-1, WAT2-2, WAT2-3, WAT2-4, WAT2-5, WAT2-6, WAT3-3, WAT3-6 2hr WAT3-1, WAT3-2, WAT3-4, WAT3-5 98 5.2.4.3 Normalization Data Due to the availability of the data loggers and in the interest of collecting as much indoor environmental data as possible, the normalization of the data loggers was left to the end of the study, as opposed to the preferred beginning of the study. The duration of the normalization is from 10:00 AM, 02/16/08 to 10:00 AM, 02/18/08. All the data loggers were located together in the same environmental condition during the normalization. They were placed into the refrigerator from 10:00 AM, 02/16/08 to 08:00 AM, 02/17/08 and relocated to normal shaded indoor environment from 08:00 AM, 02/17/08 to 10:00 AM, 02/18/08. The two phases for normalizing the performance of the data loggers are illustrated from Figure 5-7 to Figure 5-10. Figure 5-7 Phase I data loggers temperature normalization 99 Figure 5-8 Phase I data loggers RH normalization Figure 5-9 Phase II data loggers temperature normalization 100 Figure 5-10 Phase II data loggers RH normalization According to overall temperature normalization results of this study, the data loggers which were able to record the temperature generally follow the same pattern. Nonetheless, the recorded values of the data loggers have a differentiation range from 2.26°F to 21.15°F. It can be noted that the largest temperature differentiation occurred during the period of rapid temperature change within the testing environment. This differentiation in the recorded results can be attributed to each data-logger’s individual response speed and differences in the micro-environment. However, even with these factors marked for consideration, the resulting differentiation was still approximately 2.26°F to 5°F. This range of temperatures not only exceeded the accuracy of the devices but also exceeded the human sensible temperature differentiation. Thus, the values used for later analysis require normalization in order to be considered comparable data and to yield viable results. 101 The majority of the necessary normalization was achieved through a minor addition or subtraction of the recorded value in regards to a calculated average. This was done to compensate for discrepancies in the recorded values of data loggers. This response was selected due to a perceived consistent ratio compared to the average value. In order to understand each data logger’s response to the temperature change, this study used the average temperature as a norm to define each data logger’s trend. The comparison chart of each data logger and the average value was listed in Appendix I. If a data logger presented a non-linear condition, then the results had to be adjusted through a combination of a linear coefficient and a constant. After the aforementioned comparison, each data logger was examined to determine if the trend acted in a linear or non-linear fashion. Depending on the observation a different formula was applied in order to achieve the desired normalization of each data logger. For example, Phase I WATB-3’s data performance had approximately constant differentiation with the average value both in low temperature and in high temperature environment, as shown in Figure 5-11. In this case, the normalization can simply be achieved through use of a constant to adjust the data to match the average value. On the other hand, Phase I WAT3-3’s data had different differentiation constant with the average value in low temperature environment and high temperature environment, as shown in Figure 5-12. In this case, the normalization should be carried out via a formula which can describe the temperature differentiation change. However, instead of applying said formula to normalize the non-linear data, all of the data-loggers were normalized by a certain constant. The reasons this method was applied were as followed; the first was to 102 simplify the normalizing process, the second reason was because the recorded temperature range of this study is from 52.49°F to 92.46°F which is within the higher temperature environment area in the normalization. Therefore, there is no need to describe the temperature differentiation behavior lower than that. Thus, the adjusting constant of each data-logger was determined by the average differentiation between the recorded data and the average value from 9:00AM, 02/17/08 to 10:30PM, 2/18/08 instead of from the beginning of the normalization. The adjusting constant of each data-logger was listed in Table 5-3. Figure 5-11 Phase I normalization: WATB-3 and average comparison 103 Figure 5-12 Phase I normalization: WAT3-3 and average comparison 104 Table 5-3 Temperature normalization constant of each data loggers Phase I Phase II Mark Temperature normalized constant (°F) Mark Temperature normalized constant (°F) WAT B-1 -0.57 WAT B-1 -0.45 WAT B-2 -0.55 WAT B-2 -0.54 WAT B-3 -0.22 WAT B-3 -0.48 WAT B-4 -0.35 WAT B-5 -0.42 WAT B-6 -0.42 WAT 1-1 -1.04 WAT 1-1 -0.70 WAT 1-2 -0.48 WAT 1-2 -0.44 WAT 1-3 -0.20 WAT 1-4 -0.01 WAT 1-5 +0.03 WAT 1-6 -0.11 WAT 1-7 -0.33 WAT 2-1 +0.82 WAT 2-1 +0.96 WAT 2-2 +0.59 WAT 2-2 +0.26 WAT 2-3 -0.79 WAT 2-3 +0.14 WAT 2-4 -0.37 WAT 2-5 -0.21 WAT 2-6 -0.75 WAT 3-1 NA WAT 3-1 -0.32 WAT 3-2 +2.78 WAT 3-2 +0.11 WAT 3-3 -0.57 WAT 3-3 +2.92 WAT 3-4 +0.47 WAT 3-5 +0.29 WAT 3-6 +0.46 WAT 3-O NA WAT 3-O NA 105 With regards to the normalization of the relative humidity (RH) data, the differentiation range of both research phases was from 0.4% to 22.4%. Similar to the temperature normalization, because relative humidity is affected by the temperature change, the maximum RH differentiation occurred during the rapid environment change period. Due to each device’s individual response speed and the slight differentiation of its micro-surrounding environment, the larger RH differentiation was understandable. Also, according to the RH normalization data, data loggers in low temperature area had smaller differentiation than in high temperature area. Because the recorded higher temperature ranges were found in high temperature areas, instead of using a formula to describe the temperature differentiation in all temperature data, this study chose to adjust a constant according to the normalization data from 11:00AM, 02/17/08 to 10:30PM, 02/18/08. With one note, the HOBO WAT2-2 acted extraordinarily different from others in both research phases. Thus, in response to the outlander data, WAT 2-2 were determined unable to reflect the accurate relative humidity and excluded in the normalization process. The RH normalization of the rest data loggers was similar in approach to the temperature normalization. The RH adjusting constant of each data-logger was listed in Table 5-4. 106 Table 5-4 Relative Humidity normalization constant of each data loggers Phase I Phase II Mark RH normalized constant (%) Mark RH normalized constant (%) WAT B-1 NA WAT B-1 +0.16 WAT B-2 NA WAT B-2 +0.32 WAT B-3 NA WAT B-3 -0.06 WAT B-4 +0.12 WAT B-5 NA WAT B-6 NA WAT 1-1 NA WAT 1-1 NA WAT 1-2 NA WAT 1-2 +1.04 WAT 1-3 +0.43 WAT 1-4 +0.21 WAT 1-5 -0.58 WAT 1-6 -0.11 WAT 1-7 -0.56 WAT 2-1 -0.83 WAT 2-1 +0.11 WAT 2-2 NA WAT 2-2 NA WAT 2-3 NA WAT 2-3 -1.41 WAT 2-4 -0.07 WAT 2-5 +0.19 WAT 2-6 +0.22 WAT 3-1 NA WAT 3-1 +0.01 WAT 3-2 +0.74 WAT 3-2 -0.36 WAT 3-3 +0.32 WAT 3-3 +1.69 WAT 3-4 -1.03 WAT 3-5 -0.34 WAT 3-6 -0.04 WAT 3-O NA WAT 3-O NA 107 5.3 Data Logger Results Analysis 5.3.1 Temperature Comparison Figure 5-13 and Figure 5-14 illustrated the overall performance of all the data during two research time phases. Figure 5-13 Phase I all data performance 108 Figure 5-14 Phase II all data performance The overall recorded data indicated that only a few days (10/28/07, 10/29/07, 11/12-15/07, 12/04/07, etc.) were recorded with outside temperatures measuring higher than acceptable comfort levels allowed. However, the majority of the data was collected with exterior temperatures below acceptable comfort levels. After the first general analysis there became apparent several significant peaks in both monitoring periods. These were determined to have occurred when data loggers were exposed to direct sunlight. Data loggers affected by this condition were WAT3-3 during Phase I and WATB-1, WAT3-3, WAT3-5, and WAT3-6 during Phase II. The time and location of peak data recorded by each data logger is listed in Table 5-5. Because the 109 peak value was the value affected by the direct sunlight, the recorded temperature cannot be considered a reasonable representation of the thermal comfort of the overall space where the data logger was located. However, this data is still valid as it is indicative of other issues regarding the indoor environment, such as discomfort due to glare caused by direct sunlight in the working environment. This issue can also be related to inaccurate responses of the Direct Digital Controls (DDC) of the HV AC system due to the DDC being exposed to direct sunlight and misinterpreting the conditions of the indoor space the controls are set to respond to. Table 5-5 Data logger location and time of recorded peak data Monitoring Phases Data logger Mark Location Peak occurred trimming Phase I WAT3-3 3 rd floor South Studio 362 15:40 Phase II WATB-1 Basement South Studio B10 14:40-15:00 WAT3-3 3 rd floor South Office 316 15:20-16:30 WAT3-5 3 rd floor North Studio 372 10:00-10:40 WAT3-6 3 rd floor Atrium Gallery 300 16:10-16:40 According to the October recorded data, as shown in Figure 5-15, most of the locations followed a temperature stratification which indicated that the lower levels of Watt Hall maintained lower temperatures while upper floors maintained higher temperatures. This type of temperature stratification can be in part explained by the natural tendency of air to rise when heated and sink when cooled. However, certain locations did not adhere to this trend, demonstrated by the data recorded by WAT2-2 and WAT1-1. After further investigation, the study found out that data logger WAT2-2, 110 located in the southwest studio, Studio 208, on the second floor, was located under the HV AC duct where it was directly exposed to AC leakage from said duct. While the exact temperatures recorded can be brought into question, it must be noted that the vent duct not only affected the data logger, but also affected the occupants in the space. The same situation was recorded in the first floor southwest studio, Studio 107, by data logger WAT1-1, as shown in Figure 5-16. Although the Studio 107 was the space for pottery making with several rangers and heavy equipment and was supposedly with higher temperature than other space in the same level, the recorded temperature was on the lowest of all the first floor recorded data. This anomaly in the expected thermal stratification of Watt Hall was attributed to the poor insulation levels of the HV AC ducts. Figure 5-15 Phase I all data temperature performance from 10/26/07 to 10/31/07 111 Figure 5-16 Phase II first floor temperature performance from 01/09/08-01/11/08 The other data logger that recorded data not adhering to the expected temperature stratification in Figure 5-15 was WAT1-1. In phase I, WAT 1-1 was located in Studio 108E on the first floor. This studio is used primarily for pottery classes or other classes involving use of the provided kilns located on the west side of Watt Hall. Thus, the two doors in that studio were kept open to the kiln area when needed. As a result the data recorded by WAT1-1 was higher than that of other spaces and even higher than the outside temperature at the time. This can be indicative of a potential source of energy waste since the space is often left exposed to outdoor conditions while the air conditioning system is still in use. 112 In order to understand the temperature performance of each space in the context of the performance of each floor, this study separated the data by floor for analysis. The first thermal performance analysis is with regards to the Basement. Figure 5-17 shows the monitoring results recorded during November compared to the exterior temperatures as recorded. WATB-3, located in the library, recorded the lowest temperatures. This is a common occurrence that has been noted by users. One possible aspect of the space that could be responsible for these lower temperatures was a lower temperature setting to conserve the books. However, since neither the settings nor the actual temperature zone affected could be verified there was no way to readily test this theory and would require future research. The other two data loggers were WATB-1, located in the South studio B10, and WATB-2, located in Lecture B1. Generally, it can be observed that WATB-1 was more influenced by outside conditions since the recorded data appeared to follow exterior temperature trends. Another interesting phenomenon was recorded to have occurred during 11/12/08 to 11/15/08. During this period significantly warmer temperatures were recorded for the outside conditions, but the inverse was recorded for interior conditions, as shown in Figure 5-18. A possible explanation for this phenomenon was proposed that because the upper floors received higher thermal gains due to the increased exterior temperatures, the upper floors were forced to increase the AC in order to maintain indoor comfort levels. However, since the basement would not share in these increased thermal loads due to it underground nature and limited exposure to above ground conditions, the increased AC would be unnecessary. In addition, since stratification has already been noted upon to be, in part, due 113 to the natural movement of air, there is also the possibility that the increase in AC from the upper floors would increase the amount of cooled air flowing down into the basement. Without a higher thermal load to compensate, the basement could be perceived as acting as cold air trap. This situation didn’t happen on other floors in the same period of time. Figure 5-17 Phase I basement temperature data in November, 2007 114 Figure 5-18 Phase I basement temperature data from 11/12/07 to 11/15/07 Data recorded during Phase II are illustrated in Figure 5-19. As before, the data logger located in the library, W A TB-4, continued to record the coolest temperatures overall. In Studio B10 the data logger W A TB-1 was placed in a different location than during Phase I. During Phases II WATB-1 recorded temperatures that followed the exterior temperature trends even more closely than were observed during Phase I. There also appeared several peaks caused by direct sunlight as previously mentioned. This was an unexpected result as it indicated that Studio B10 did in fact have solar thermal gains from the few South facing skylights available. The other data demonstrated that WATB-5, located in Lecture B1, recorded the highest temperatures in the basement. The second highest was WATB-2, located in Clipper Lab where the highest overall temperatures were recorded during Phase 115 I. The increased temperatures in the Clipper Lab were attributed to the increased thermal gains due to the large amount of computers and appliances running in the space. Another monitoring point was WATB-3, located in the library stack area. WATB-3 recorded higher temperatures than W ATB-4 which was located in the reading area of the Library. However, this could in part be due to the location of the data logger was shielded from the HV AC duct and vent opening by a stack of books. Figure 5-19 Phase II basement temperature data in January, 2008 Data as recorded during Phase I on the First Floor is shown in Figure 5-20. For the First Floor there were only two monitoring points available. One of them, WAT1-1, in Studio 108E, and was noted to be significantly affected by the outside kiln areas. The other one, WAT1-2, was located at the end of the corridor and recorded notably less 116 fluctuation than WAT1-1. This more consistent temperature was in part due to the data logger located inside the building, where the impact of exterior temperatures was reduced. In order to obtain a better understanding of the performance of the First Floor, more reference points were required and gathered during Phase II, shown in Figure 5-16. From the Figure 5-16, the same situation as previously described can be observed. It should be noted that WAT1-1 was exposed under a duct and therefore recorded lower temperatures than might have been available in the space overall. However, WAT1-7, located near the kiln area, did not perform as Figure 5-20 had previously implied with expected higher temperatures. This unexpected result was in part due to that this monitoring period took place during the winter recess of the University. With no classes in session the classrooms were typically closed off to exterior weather conditions in direct contrast to the tyipcal open doors observed when class was in session. Although there was still observalble impact from the exterior weather conditions on the interior temperatures, during Phase II this influence was significantly reduced than previously observed during Phase I. WAT1-3 continued to record higher temperatures during 01/09/08 to 01/11/08. This could in part be due to WAT1-3’s location in the office area, which continued regular operating hours during the winter recess, and sustained user presence even when the students were not expected on campus. Later monitoring records, taken from 01/09/08 to 01/22/08 and shown in Figure 5-21, demonstrate the raised temperature conditions previously expected by WAT1-7 during Phase I. Since this data was taken after classes were once again in session a correlation between the conditions of the classroom when in use and the overall indoor comfor levels of the space can be drawn. Besides WAT1-7, WAT1-3 also recorded 117 higher temperature than other spaces throughout whole Phase II monitoring period. This condition was attributed to WAT1-3 being located in a space without vent duct exposure. Also, both Figure 5-16 and Figure 5-21 indicated WAT1-4 had less fluctuation. WAT1-4 was located in the center gallery space on the first floor. With no direct or indirect exposure to outside conditions and buffered on all sides by classrooms and other program, WAT1-4 recorded a significantly reduced impact of outside conditions on the indoor thermal comfort levels of the center gallery space. This corresponds with WAT1-2’s results from Phase I, in Figure 5-20. Figure 5-20 Phase I first floor temperature data from 10/26/07-10/31/07 118 Figure 5-21 Phase II first floor temperature data from 01/19/08-01/22/08 Figure 5-22 and Figure 5-23 illustrate the interior conditions recorded for the Second Floor. Figure 5-22 shows the temperature performance on second floor during Phase I. As previously explained, WAT2-3 had the lowest temperature results because of the exposure due to its location under the HV AC duct. WAT2-2 was located in Gallery 214 which was equipped with incandescent lighting. The thermal gains due to the lighting combined with the dropped down nature of the lighting system, which exposed users more directly to said gains, translated to higher temperatures being recorded for this space than otherwise expected. It should also be noted that there was no direct HV AC service to this space. Concerning to the Phase II results, Figure 5-23, WAT2-3, Studio 208, still performed lowest temperature. The next was WAT2-5, located in an open corridoor facing the 119 entrance that is used as pin up space for design reviews. Since this space is directly adjacent to the entrance doors it is visibly impacted by exterior temperature conditions, demonstrated by the data recorded on 12/17/07. WAT2-2, located in Gallery 214, continued to record the highest temperatures when compared to other spaces on the Second Floor. The second warmest space was recorded by WAT2-6, located in the Office 203 right beside the thermostat. One of the causes for these elevated readings was in part due to the exposure to exhaust heat eminating from the printer directly below the data logger. As a result the data recorded by WAT2-6 may not be an accurate representation of the thermal comfort levels for this space. However, what must be considered is the fact that the temperatures recorded by the data logger do reflect the temperatures available to the thermostat sensor. This translates to the fact that the thermostat was possibly not adjusting the HV AC to compensate for actual indoor thermal comfort levels but rather for the elevated temperatures due to the heat exhaust from the printer. A sensor located where it might be able to have an accurate reading of the conditions of the space might provide a more appropriate response with regards to necessary HV AC loads to maintain indoor comfort levels for users. 120 Figure 5-22 Phase II second floor temperature data from 12/01/07-12/10/07 Figure 5-23 Phase II second floor temperature data from 12/10/07-12/31/07 121 The data gained for the Third Floor is illustrated in Figure 5-25 to Figure 5-27. Figure 5-25 also provides the results from the only outside temperature recorded by this research. W A T3-O was placed on the outside of the southeast office terrace and protected from direct sunlight as shown in Figure 5-24. Although there was only a little more shielding provided by the parapet, the results indicated W A T3-O had less temperature fluctuation compared to the data recorded by USC weather station. Both Figure 5-25 and Figure 5-26 indicated that W AT3-3 was hit by direct sunlight. Despite the peaks value on W AT3-3, the Phase I results showed that the south studio area, where WAT3-1 and WAT3-3 were located, was colder than the north studio area, where WAT3-2 was located. Regarding the results of Phase II, Figure 5-27, WAT3-3 was located in the south office area, where the user stated that the air-conditioning was never used. Thus, temperatures of this office space recorded a more direct correlation to exterior conditions than other office space. As aforementioned, WAT3-3, WAT3-5, and WAT3-6 were hit by direct sunlight at various points over the data collection period. Besides the peaks, the figure indicated WAT3-1, located on the west side studio, recorded the coolest temperatures. WAT3-6, located in the center atrium on third floor, had the highest temperatures recorded. This was expected because the atrium was originally design as an open space to the Second Floor without additional air-conditioning. WAT3-4, located on the east side studio on the Third Floor, had the second lowest temperatures. These reduced temperatures when compared to other locations within the Third Floor were attributed to the distribution of solar gains throughout the space. However, it must be noted that during Phase II the trend of reduced temperatures was not observed. This was due to a change in the location of the data logger 122 as a method of reducing temperatures recorded with direct sunlight exposure. The unfortunate result was the data logger was located near the computer equipment available to the students and was therefore exposed to the exhaust heat emanating from the equipment. As a result warmer temperatures were recorded than were available to users within the space. Nonetheless, W AT3-4 still had lower temperatures compared with others. Comparing the north, WAT3-5, and south, WAT3-2, studio temperatures, the figure illustrates that the temperatures in south studio were lower than the temperature in north studio. This was the same as the results in Phase I. These results go against the expected since there would be higher solar gains in the South facing studios and therefore the studios would be expected to maintain slightly warmer temperatures than the other spaces. Instead, the North facing studio recorded the warmest temperatures. In order to explain this phenomenon it must be noted that the Third Floor HV AC system is controlled by sensors facing the four cardinal directions. Temperature control and adjustments are made according to the data of these sensors. During the research process it was discovered that over the course of the day three of these four thermostat sensors were exposed to direct sunlight and subsequently to increased solar gains. As a result the temperatures recorded during this time were significantly elevated beyond what the actual temperatures in the space were as they were being experienced by the users. In response to the elevated temperatures sensed by the thermostat sensor, an increased load beyond what was appropriate at the time was placed on the HV AC system. The result was users complaining of the constant cooler temperatures of the space. 123 Even though there were several issues, the indoor comfort of each space needed to be determined via further analysis. Figure 5-24 WAT3-O location and placement Figure 5-25 Phase I third floor temperature data in November, 2007 124 Figure 5-26 Phase I third floor temperature data from 12/01/07 to 12/10/07 Figure 5-27 Phase II third floor temperature data from 12/10/07 to 12/31/07 125 5.3.2 Indoor Comfort Analysis In accordance to the indoor comfort research data gathered though the Watt Hall Energy Management Implementation Initiative from 10/26/07 to 02/15/08, the indoor comfort performance was generated. As previously mentioned, the comfort range is related to various factors, such as temperature, humidity, wind speed, etc. What is considered comfortable also varies between individual perception, clothing insulation, metabolism, etc. In order to obtain a general observation of each space’s thermal comfort, this study relied on a combination template to reveal the comfort performance of Watt Hall. The template was a combination of the Psycho Tool (Square One Research, 2005) and the comfort boundary defined by B. Givoni (Stein, Reynolds, Grondzik, & Kwol, 2006). The Psycho Tool is the comfort range defined by ISO 7730-1993 which is used by the ANSI/ASHRAE Standard 55-2005. The templates considered not only temperature and humidity, but also clothing insulation, activity rate, air velocity, radian temperature and the barometric pressure. In order to reveal the thermal performance reflected by the recorded temperature and humidity, this study assume the clothing ensembles (CLO) was 0.8, activity rate was 1.2 met, wind speed/air velocity was 40 ft/min, mean radian temperature (MRT) was 70°F, and the barometric pressure was 14.7 psi. The detail definition of each factor was listed in Table 5-6. 126 Table 5-6 Definitions of thermal comfort factors and related terms (ASHRAE 55-2004, 2004) Factor/Term Definition/Description Metabolic Rate The rate of transformation of chemical energy into heat and mechanical work by metabolic activities within an organism, usually expressed in terms of unit area of the total body surface. This rate is expressed in met unit. Met is a unit used to describe the energy generated inside the body due to metabolic activity, defined as 18.4 Btu/h ∙ft 2 , which is equal to the energy produced per unit surface area of an average person, seated at rest. The surface area of an average person is 19 ft2. In this study, the metabolic rate was set as 1.2 met which is the activity rate of seated filing office activities and equals 22 Btu/h ∙ft 2 . Insulation, Clothing/Ensemble The resistance to sensible heat transfer provided by a clothing ensemble. Expressed in CLO unit. CLO is a unit used to express the thermal insulation provided by garments and clothing ensembles, where 1 CLO=0.88 ft 2 ∙h°F/Btu. This study assumed the CLO=0.8 which is the insulation level of overall long-sleeve shirt clothing. Air Temperature The temperature of the air surrounding the occupant. This factor was the recorded temperature data in this study. Radiant temperature This is the mean radiant temperature of surfaced within the building, such as ceilings, windows and walls that radiate their own heat and re-radiate heat from other sources. This study assumed the mean radiant temperature was 70°F. Air Speed The rate of air movement at a point, without regard to direction. Air speed was assumed to be 40ft/min in this study. Humidity Humidity ratio is the ratio of the mass of water vapor to the mass of dry air in a given volume. Relative humidity is the ratio of the partial pressure of the water vapor in the air to the saturation pressure of water vapor at the temperature and the same total pressure. The two values were obtained from the recorded data in this study. Predicted Mean V ote (PMV) Predicted Percentage of dissatisfied (PPD) PMV is an index that predicts the mean value of the votes of a large group of persons on the seven-point thermal sensation scale: +3 hot, +2 warm, 0 neutral, -1 slightly cool, -2 cool, and -3 cold. PPD is an index that establishes a quantitative prediction of the percentage of thermally dissatisfied people determined from PMV. Acceptable thermal environment for general comfort: PMV range is -0.5<PMV<0.5. Psycho Tool mainly uses above range to color coding the thermal comfort. In the tool. PMV=o present fine human comfort. Applying aforementioned template, the overall indoor temperature and humidity performance are illustrated in Figure 5-28. The data relied on for this section of the analysis is primarily from Phase II because the majority of the devices used in Phase I were unable to record humidity. 127 Figure 5-28 Overall Watt Hall comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) In order to obtain further understanding of the indoor comfort performance of each space, the following was the results of individual spaces performance. Figure 5-29 illustrates the overall basement thermal comfort performance during the Phase II research period. As shown it can be observed that half of the data points were lower than the comfort zone. According to the individual performance of each basement space, as shown in Figure 5-30, WATB-1, located in basement Studio B10, and WATB-4, located in the library reading area, supplied the majority of the data recorded cooler than the defined comfort range permitted. Some higher temperatures recorded in WATB-1 were because of the influence of the direct sunlight. The other spaces, WATB-3 and WATB-2, were within the thermal comfort. This comfort situation might be contributed 128 by the internal heat gain of the space, especially true for WATB-2, placed in Clipper Lab WATB-2. Figure 5-29 Basement spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) 129 WATB-1: South Studio B10 WATB-2: Clipper Lab B7 WATB-3: Library Stack Area B4 WATB-4: Library Reading Area B4K Figure 5-30 Basement individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) Figure 5-31 First floor spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) 130 Figure 5-31 and Figure 5-32 illustrate the overall and individual spaces thermal comfort performance on the First Floor during Phase II research period. As demonstrated, the majority of the spaces were recorded within the allowable thermal comfort range. WAT1-2: Southeast Studio 105 WAT1-3: Office 103 WAT1-4: Gallery 103 WAT1-5: Class Room 102B WAT1-6: Class Room 118 WAT1-7: Class Room 108E Figure 5-32 First Floor individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) 131 Figure 5-33 illustrates the overall Second Floor thermal comfort performance during Phase II research period. There were only a few data points under the comfort range. After examining the thermal performance of individual spaces on the second floor, Figure 5-34, it was determined that the uncomforted data points were contributed by the WAT2-5, Pin Up Area. As aforesaid, this location would be affected by the outside weather directly if the entrance door was opened. Another space under the thermal comfort range was WAT2-3 because of the exposed HV AC vent duct. For the unusual pattern appeared in WAT2-2, this was because the data logger unable to record the humidity, mentioned in the normalization section. Thus, all the data points appeared in the same humidity level. Despite this, the space still can be determined within the comfort range according to the temperature performance. Figure 5-33 Second floor spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) 132 WAT2-1: North Studio 200 WAT2-2: Gallery 214 WAT2-3: South Studio 208 WAT2-4: West Studio 209 WAT2-5: Pin Up Area 202 WAT2-6: Office 203 Figure 5-34 Second floor individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) Figure 5-35 illustrates the overall Third Floor thermal comfort performance during the Phase II research period. According to this figure half of the data points were lower than the comfort zone. According to the individual performance of each space on the third floor, as shown in Figure 5-36, the data points below the thermal comfort range were recorded by WAT3-1 and WAT3-3. For WAT 3-3, the thermal performance was 133 understandable because the data logger was located in a space without air-conditioning. However, WAT3-1 was located in the space along side of the Direct Digital Control (DDC) HV AC control mechanism. This confirmed the issue of the sensor’s location. WAT3-4 also had some data points outside the thermal comfort boundary. If WAT3-4 was placed far from the computer equipment, it might have had the same read out as WAT3-1. Figure 5-35 Third floor spaces thermal comfort condition and outside temperature psychrometric chart comparison (Square One Research, 2005) 134 WAT3-1: West Studio 368 WAT3-2: South Studio 362 WAT3-3: South Office 316 WAT3-4: East Studio 356 WAT3-5: North Studio 372 WAT3-6: Center Atrium 300 Figure 5-36 Third floor individual spaces thermal comfort performance psychrometric chart (Square One Research, 2005) 135 5.4 Summary According to the research results, most of the spaces in Watt Hall were within the allowable comfort zone, however there were still areas in need of improvement, such as in the library and the some of the studios. With regards to the library, more data is needed to confirm the cause of the library’s consistent state outside the allowable comfort zone. Whether it is the settings of the HV AC system or other cause, this must be isolated before recommendations can be made. For the Second Floor south studio, the primary reason discovered that led to the uncomfortable conditions of the space was determined to be caused by the exposed ventilation duct. This indicates that improved insulation of the ventilation ducts would lead to improved conditions within the space. The data results of the west studio on the First Floor indicated the space was opened to the kiln area during operating hours. That meant energy loss through open doors leading to the outside and thermal gains due to the exposure to the heat emanating from the kilns themselves. Regarding the peak values appearing in the data, this revealed the inherent problem in the location of the digital control sensor and also implicated the possibly indoor uncomfortable temperature and glare caused by direct sunlight exposure. The influence on the sensor might able to be demonstrated by the temperature performance on the third floor. Generally, the temperatures on third floor, west and east studio were colder. The preliminary reason was determined as the sensor affected by the direct sun light. However, 136 this study has not confirmed if there was any difference temperature setting in the four orientations. This study has also not confirmed that this is the only viable reason for the difference in the recorded temperatures. Higher temperatures recorded when the data logger was placed near appliances reflects the continuing issue of the location of thermostats. The purpose of this study was to understand current indoor environment thermal comfort levels of Watt Hall and reveal the inherent issue of the HV AC system of the building for future energy management and indoor air quality improvement. The final goal is to not only achieve energy efficiency but also maintain thermal comfort levels for the interior environment of the building. Although the study duration wasn’t long enough to match the three year long monitoring requirement and also not long enough the cover a whole year’s climate change, an initial observation still revealed observable trends in the indoor thermal comfort performance of Watt Hall. While far from complete, this brief energy study determined some preliminary issues that are in need improvement or further research. 137 Chapter 6 Building Energy Consumption Simulation Models After the ground work research of Watt Hall was completed, two energy simulation tools, eQuest and ECOTECT, were employed to determine the current energy end-use breakdown of Watt Hall. Proposals were then generated based on these finding that were believed would reduce the overall energy consumption of the building. Each implemented strategy possessed its own embodied energy cost. Therefore, any strategy had to be carefully analyzed before installed. In order to achieve a sustainable environment only the strategies with the lowest embodied energy cost with the highest expected positive impact should be considered. In order to determine which design strategies would have the most impact with the least embodied energy, all strategies were then compared to each other. The goal of the research was to build a detailed simulation model which could reflect the actual energy performance of Watt Hall. With current software a computer model is capable of simulating the present energy performance of Watt Hall, in addition to the performance of the building in response to different proposed strategies. However, some important building information was unable to be obtained during this research period, such as HV AC system, lighting fixture, appliances, etc. Also, the acquired operation schedule of each space was too detailed to be implemented into the software as is, and so this study could only generalize the approximate schedule according to the occupancy classified by this study. Thus, the simulation results were not as accurate as would be otherwise 138 expected. The other issue was concerning the calibration. Because of lacking information regarding clarification of the energy usage of Watt Hall from the electricity and gas bill provided by the university, this study was unable to calibrate the simulated results to actual recorded results. Even then the simulation still provided solid references regarded the effectiveness of each possible strategy. This study primarily employed both eQUEST and ECOTECT to simulate the energy performance of Watt Hall and varying design strategies. Due to their inherent strengths and weaknesses, eQUEST was adopted to simulate the whole building energy performance while ECOTECT was employed to assist in proposing passive improvement strategies. This study has helped in establishing Watt Hall’s current energy performance as well as proposing feasible energy consumption improvement strategies. The effectiveness of these strategies are demonstrated through detailed hourly energy modeling, which takes into account the various physical elements of the design, internal load profiles and systems and their interactive implication on the overall energy consumption of the building. 139 6.1 eQUEST Simulation Model of Watt Hall 6.1.1 Tool Introduction This study selected eQUEST as one of the simulation tool. The primary reason was because it has already been broadly applied to improve several buildings by major architecture and engineering consulting firms and was also approved by the California Energy Commission as a 2005 Title-24 Nonresidential Alternative Calculation Method (ACM). Besides aforementioned, eQUEST provides a user friendly input interface with combining schematic and design development building creation wizards, an energy efficiency measure (EEM) wizard. (Hirsch, eQUEST, 2006) Comparing to DOE-2, it provides a more user-friendly interface but still professional-level results with an affordable level of effort. eQUEST calculates heating and cooling loads for each hour of the year base on the factors such as: walls, windows, glass, people, plug loads, and ventilation. eQUEST also simulates the performance of fans, pumps, chillers, boilers, and other energy-consuming devices. The simulation of eQUEST also offers several graphical formats for viewing simulation results. For example, graphing the simulated overall building energy on an annual or monthly basis or comparing the performance of alternative building designs. In addition, eQUEST allows users to do multiple simulations and view the alternative results through side-by-side graphics. It offers energy cost estimating, daylighting and lighting system control, etc. (Crawley, Hand, Kummert, & Griffith, 2005) 140 6.1.2 Simulation Process eQUEST provides two types of modeling wizards that simplified the modeling procedure. One of them is the schematic design wizard (SDW); the other is the design development wizard (DDW). The schematic wizard is more useful to assist at the planning stage because it can only provide one building envelope shape and it provided the input also simplified the definition of the building envelope and operation schedule. The design development wizard of eQUEST allows user to input more detailed information. Both wizards provide clear categorized factors needed to be considered in the building energy consumption simulation. These wizards helped this study walk through the process of creating an effective building energy model. At the beginning, this study started generating the model through the SDW. However, the allowable input parameters in SDW were too limited that the results were unable to define the building thoroughly. Thus, the study established the main structure of the model in DDW. The simulation steps included the input of architectural design, HV AC equipment, building type and size, floor plan layout, construction materials, area usage and occupancy, and lighting system. All information regarding the input for these factors was acquired through the aforementioned baseline research. Yet, as previously mentions, the model built in DDW was still unable to describe the building very well due to the 3 rd floor atrium, building façade materials, HV AC system, etc. Those variations were unable to be defined in the DDW mode. Thus, the following step was to switch the edit mode from “Wizard Data Edit” to “Detailed Data Edit” to modify the model. The benefit of using the wizard was it leads users through every critical parameter necessary for the energy 141 simulation and is easier to modify the building geometry afterward. However, the wizard also generates any necessary corresponding “child component,” such as wall, roof, glazing types, room schedules, etc., to each defined space. If there are more spaces in the model, there will be more “child components,” even though there only were 20 needed to be defined in the whole building. The situation occurred during this study. Thus, in the “Detailed Data Edit” mode, the study not only modified the geometry to make the model closer to the as-built conditions of Watt Hall, but also redefined each component’s properties to match with previous research results, as shown in Appendix B and Appendix C. After modifying the model, the study ran each strategy separately and compared the generated results with the previous results. Also, the comparison with the available utility bill was generated. During the modeling aspect of the research there were several other conditions that lead to questioning the validity of the results generated by eQUEST. This issues persisted despite the provided very detailed input options, and even more, the ability for users to create new materials, schedules, systems, geometries, etc,. The most apparent reason is the lack of HV AC system information. Nonetheless, all the reasons point to the insufficient detailed definition of materials properties. For example, eQUEST allowed the user to define a new construction that users can input the wall construction according to the as-built construction drawings. However, there is no record from the as-built documentation to provide further required detailed information in eQUEST, such as conductivity, density, absorbance, surface roughness, etc. eQUEST does provide a material 142 library composed of information for the properties of major construction materials. However, for those properties unavailable in the eQUEST library, this study had to seek out other resources. Unfortunately, without reliable documentation, there is some question to the validity of the properties inputted for various materials used by Watt Hall as many of these properties were forced to be approximations as opposed to documented values. Since the source of the data used was the source of the questionability to the validity of the results, these issues repeated themselves during the ECOTECT modeling. Because several important parameters at this research stage were still unavailable, the model might not reveal the actual energy consumption of Watt Hall. However, this study still provided the comparison with current available energy consumption bill for further discussion. More importantly, since any inaccuracies were consistent through all simulations the simulated results regarded the effects of potential proposals remained valid. The final eQUEST model is illustrated in Figure 6-1. After compiling a building description, eQUEST generated a detailed simulation of the building and estimated how much energy it would use. 143 Figure 6-1 eQUEST Model of Watt Hall eQUEST provided the Energy Efficiency Design Wizard (EEDW) function to evaluate each possible improvement strategy explored. However, EEDW was only able to be utilized when the model was generated through either the SDW and DDW. Thus, this study tested each strategy one by one and compiled the comparison in a table for comparison. This study tested several possible improvement strategies suggested in accordance to the results of previous ground work research. The input information was according to simplified data gathered and defined during ground work research. The testing of alternatives included adjustments made to the user operation schedule, lighting density control, temperature setting of the HV AC system, insulation levels of the Wall, and glass type. The Table 6-1 listed the tested strategies and its reason. 144 Table 6-1 Tested Strategies in eQUEST # Strategies Descriptions 1 Insulation Add “Exterior Wall Batt R-13” in 1st & 2nd floor. While most of the insulation performances of Watt Hall’s envelope were lower than the value suggested by ASHRAE 90.1-2004 standard, especially for 1 st and 2 nd floor. Thus, this study tested the impact of improving the insulations. For Watt Hall’s condition, to add exterior wall insulation was actually to add the insulation inside the tack board in studio area. 2 Lighting Lower LPD It was observed that the majority of the LPD recorded were higher than the value suggested by ASHRAE 90.1-2004 standard, this study tested the impact of adjusting the LPD value to the suggested levels by the standard. 3 HVAC Control temperature set point For the baseline model, while this study was unable to obtain the thermostat temperature setting of the HV AC system, the simulated temperature setting was according to the Indoor Thermal Comfort Research results: 65-75°F. According to previous research, this setting is too low that made some space’s temperature lower than comfort range, such as basement and 3 rd floor. Thus, this study tested the results of increase the temperature setting in basement and 3 rd floor to 70-80°F to see the energy consumption performance. 4 Shading Add 3rd Office exterior overhang 2ft shading on W, S and E 5 Glass Change 1st & 2nd floor glass from single clr/tint to Double Low-E 6 Operation Schedule-HV AC Adjust HV AC operation schedule During the Fall and Spring semesters: operate 24 hours. During the Summer semester: Operate from 8:00 to 17:00. Turn off the AC during the break 145 6.1.3 Comparison Results The baseline simulation results of Watt Hall were shown in Figure 6-2. Although this study tried to input the information as thoroughly as permitted by the software utilized, such as information regarding the building envelope, lighting power density, appliance, and occupancy schedule, the simulated results were unable to confirm the actual energy consumption at the current research period due to unavailability of information regarding the HV AC equipment details. Therefore, when comparing the simulated results with the available electricity bill, the simulated results consumed an extra 4,000,000 kWh of electricity. Despite the inaccuracies regarding the input for certain systems, these results implied there might have been more energy consumed by the HV AC system that was not included in the electricity bill. This is quite possible since the heating equipment and chilled water are both delivered from a central campus loop that provides steam and chilled water. However, how much energy is consumed through these two sectors requires a more in depth investigation and further research. With regards to the final energy consumption profile of Watt Hall this information will be critical. However, with regards to the impact of design proposals this information is not critical though it may explain the discrepancy between the simulated energy consumption levels of Watt Hall and the actual energy consumption recorded. 146 Figure 6-2 Watt Hall preliminary baseline simulation results in eQUEST The results of the tested improvement strategies are shown in Figure 6-3. The results of each tested strategy lowered the simulated energy consumption level. However, adjustments to the HV AC operation schedule had the most drastic results. 147 Figure 6-3 Total energy consumption of each alternative 6.1.4 Summary The simulation results of eQUEST indicated that each strategy could improve the current building energy consumption level. However, the most economical method was to adjust the operation schedule radically. For further improvement strategies, the cumulative effect should be considered for further study. The study was unable to calibrate the simulated building energy consumption level with the actual bill because there were kilns and a wood shop mixed into the energy usage. Yet, the simulation still proved effective in assisting the evaluation of retrofitting strategies. 148 6.2 Ecotect Model 6.2.1 Tool Introduction ECOTECT v.5.5 is a highly visual and interactive complete building design and analysis tool. Its analytical functions include thermal, energy, lighting, shading, and acoustics analysis. Its main advantage is it provides variety color coding graphics in 2D and 3D. It provides the designer with useful performance feedback both interactively and visually. In addition to the standard graph and table-based reports, analysis results can be mapped over the building surfaces or displayed directly within the spaces that generated them, giving the designer the best chance of understanding exactly how their building is performing and from that basis make real design improvements. ECOTECT also provides an advanced scripting engine. This engine enable users to program ECOTECT in order to simulate other aspects of the building performance not included in the standard program (Crawley, Hand, Kummert, & Griffith, 2005). For this study this engine was not utilized in favor on using the already tested scripts provided within ECOTECT. 6.2.2 Simulation Process ECOTECT allows the user to import 3D geometry from other CAD tools. However, even after importing the whole geometry, users still need to redefine each element individually. Thus, this study built the entire Watt Hall in ECOTECT in an attempt to reduce corruption or loss of information often present when moving models across various software. Unlike eQuest, ECOTECT did not provide a wizard function. That meant that 149 each element needed to be drawn in ECOTECT one by one. Not only each geometry required definition, but each zone and material element also had be defined within the program. The resulting completed ECOTECT model of Watt Hall is shown in Figure 6-4. Figure 6-4 Sun path illustration of Watt Hall ECOTECT model (Lin, The ECOTECT Model of Watt Hall, 2008) While the purpose of generating this model was to process the following simulation, the model proved too complicated to simulate. Attempts made took more than 24hours apiece to obtain even the most basic of results. In addition, each thermal connection had to be carefully redefined. Due to the nonuser friendly interface of ECOTECT the learning path of ECOTECT was significantly longer than eQUEST. Thus, this study relied on eQUEST to assist in solving the visual comfort issues observed on the 3 rd floor. 150 According to previous research completed by Jay Yong Suk, it was discovered that while there was sufficient natural light available on the 3 rd floor, glare caused by direct sun exposure caused certain spaces to become difficult to work in at different times of the day. Thus, this study mainly focused on testing improvement strategies where this issue was recorded to be most persistent, primarily the southeast corner of Watt Hall 3 rd Floor. With the completion of the ECOTECT model this study moved on to calculate the natural lighting levels inside the 3 rd floor. Once completed the next step was to record the shadow range inside the 3 rd floor’s southeast corner. Possible strategies involving louvers on the upper window and a deep overhang outside the studio door were then tested for their effectiveness in shading the space in question. Lastly, the study recalculated the daylight level inside the building with the selected alternative to understand the natural lighting performance after installing the strategy in question. Also, the simulation of the selected strategy was tested in the eQUEST model to understand the impact on the overall building energy consumption. 6.2.3 Data Analysis Figure 6-5 illustrates the resulting shadow range of each month on the 3 rd floor. During the winter time, due to the lower sun angle, the space acquires the most direct sunlight, especially notable during afternoon hours. This study tested both the louver and overhang on the south façade on December 1 st 14:00 to 15:00, as shown in Figure 6-6. The louver was applied on the clerestory with 151 aspect ratio=7, and the deep overhang was applied on the sky garden with aspect ratio=1.16. The figure also illustrated the cumulative daylighting level on the third floor. The results can be seen in Figure 6-7. The space with deep overhang demonstrated a greater reduction in space subjected to direct sunlight. Therefore the testing indicated that the sky garden overhang worked more effectively to avoid glared resulting from direct sunlight exposure than the louver system on the clerestory, even though the aspect ratio of the louver is much larger than the sky garden overhang. Figure 6-5 3 rd floor southeast corner shadow range study (Lin, The ECOTECT Model of Watt Hall, 2008) 152 Figure 6-6 Daylighting levels and testing alternatives on the Watt Hall 3 rd floor from ECOTECT model (Lin, The ECOTECT Model of Watt Hall, 2008) Figure 6-7 Shading alternative comparison in ECOTECT (Lin, The ECOTECT Model of Watt Hall, 2008) 153 The study recalculated the indoor cumulative natural lighting level, as shown in Figure 6-8, to determine if the resulting indoor cumulative natural light was still at usable levels for users. Compared to the original results, the lighting levels of the space with louvers and the overhang decreased, but remained high enough to provide usable natural light. In order to understand the impact of the selected shading device on the building energy consumption, this study ran the shading strategy in the eQUEST model. Instead of increasing the heating load of Watt Hall, the result indicated the shading on the south façade of 3 rd floor lowered both the electricity and gas consumption of Watt Hall. Figure 6-8 Daylighting levels of the model with louver and overhang from ECOTECT model calculation (Lin, The ECOTECT Model of Watt Hall, 2008) 154 Figure 6-9 The simulation impact of 3 rd floor shading 6.2.4 Summary The ECOTECT simulation results demonstrated that sky garden overhang was more effective than the clerestory louvers in offsetting direct solar gains in December during 14:00 to 15:00 on the 3rd floor in the southeast corner. However, the study did not test varying angles available to the louvers at different times. A more thorough analysis is needed to understand the full potential affect of the louver strategy and to see if possible adjustment of available variances could make them more effective. In addition, the opportunity to compare the simulation results and the actual shading performance in order to evaluate the accuracy of the simulated model would be useful. 155 6.3 Summary The simulation results of eQUEST indicated that each strategy could improve the current building energy consumption level to varying degrees, the most economical method being to adjust the operation schedule radically. For further improvement strategies the cumulative effect should be considered for further study. This study was unable to calibrate the simulated building energy consumption level with the actual recorded energy bill due to elements whose impact could not be accounted for, such as kilns and the wood shop. Yet, the simulation still proved effective in assisting in the evaluation of the retrofitting strategies. The ECOTECT simulation results demonstrated that the sky garden overhang was more effective than the clerestory louvers in offsetting direct solar gains in December during 14:00 to 15:00 on the 3 rd floor in the southeast corner where the most solar gains were previously recorded. However, the study did not test available variables such as depth and angle to the louvers at different times. A more thorough study is needed to determine the full impact potential of the louver approach before a final determination can be made. In addition, the opportunity to compare the simulation results and the actual shading performance in order to evaluate the accuracy of the simulated model would be useful in determining which method would be more appropriate. A cost analysis would also be useful. 156 Chapter 7 Conclusion & Future Work The ground work research and preliminary building energy consumption simulation of Watt Hall revealed several important directions to improve the energy consumption of Watt Hall. While this study generated critical information with regards to developing a comprehensive Environmental Management System, continued research in needed in order to pursue the carbon neutral status originally sought by the USC-ARCH EMS research team. The results of this study breakdown into the following: Building Envelope The majority of the building envelope of Watt Hall did not meet that standard set by ASHRAE 90.1-2004. The fixed window design of the 1 st and 2 nd floor was unable to provide any natural ventilation. Although to improve this aspect would require costly renovations, this strategy was decided worthy of consideration for future retrofitting strategies. Lighting Power Density (LPD) With the exception of the third floor there is no individual lighting control available in Watt Hall. This condition translates to the entire building being completely lit twenty four hours a day seven days a week. The LPD of most of areas were recorded to exceed the ASHRAE standard therefore providing significant room for improvement. To improve this sector, a proper lighting control mechanism should be applied to balance the extra 157 energy consumption of the lighting. Manually controlling the lighting operation schedule is the most efficient method available to ease the consumption of unnecessary lighting without inducing the added cost additional automatic sensors. Other future improvement items would include the replacement of currently light bulbs to more energy efficient ones and placing occupancy sensors to control lighting levels. HVAC The fixed window design of the first and second floor forces the complete reliance on the HV AC system to maintain indoor comfort levels. However, some indoor temperature control degree settings were recorded under the comfort zone and resulted in reports of uncomfortable indoor conditions. Maintaining indoor environmental temperatures below the comfort zone and at the discomfort of the users can be perceived as a waste of energy. Thus, it is important to clarify the required indoor environment conditions and thereby diminish the over air-conditioning caused by anthropogenic sources that we can process further improvements. Also, the temperature thermostats in each area didn’t have a noticeable effect on the indoor temperature, thereby reducing their perceived effectiveness. According to the interview of building occupants, some spaces in Watt Hall were always colder than human comfort temperature. Although this study was unable to determine the efficiency of the HV AC system, to control the operation schedule of the system would perceptibly lower the energy consumption. 158 Indoor thermal Comfort According to the research results, the majority of the spaces in Watt Hall were within the allowable comfort zone. However, there were still areas in need of improvement, such as in the library and the some of the studios. With regards to the library, more data is needed to confirm the cause of the library’s consistent state outside the allowable comfort zone. For the Second Floor south studio, the primary reason discovered that led to the uncomfortable conditions of the space was determined to be caused by the exposed ventilation duct. This indicates that improved insulation of the ventilation ducts would lead to improved conditions within the space. This approach or relocation of the thermostat sensor would be able to improve this condition. The data results of the west studio on the First Floor indicated the space was opened to the kiln area during operating hours. This translated to energy loss through the open doors leading to the outside and thermal gains due to the exposure to the heat emanating from the kilns themselves. Regarding the peak values appearing in the data, this revealed the inherent problem in the location of the digital control sensor and also implicated the possibly indoor uncomfortable temperature and glare caused by direct sunlight exposure. The influence on the sensor might able to be demonstrated by the temperature performance on the third floor. Generally, the temperatures on third floor’s west and east studio were colder. The preliminary reason was determined to be the sensor affected by direct sun light. In order 159 to absolve this issue either the relocation of the sensor or a method of shading said sensor from direct solar exposure would be appropriate. Energy Simulations The simulation results of eQUEST indicated that each strategy could improve the current building energy consumption level. However, the most economical method was to adjust the operation schedule radically. For further improvement strategies, the accumulative effect should be considered for future study. The study was unable to calibrate the simulated building energy consumption level with the actual bill because there were kilns and a wood shop mixed into the energy usage. Yet, the simulation still proved effective in assisting the evaluation of retrofitting strategies. The ECOTECT simulation results demonstrated that sky garden overhang was more effective than clerestory louvers in offsetting direct solar gains in December during 14:00 to 15:00 on the 3 rd floor in the southeast corner where the most solar gains were previously recorded. However, the study did not test available variables such as depth and angle to the louvers at different times. A more thorough study is needed to determine the full impact potential of the louver approach before a final determination can be made. In addition, the opportunity to compare the simulation results and the actual shading performance in order to evaluate the accuracy of the simulated model would be useful in determining which method would be more appropriate. A cost analysis would also be useful. 160 This study was meant to serve as only the ground work of the Energy Management System within the Environmental Management System. There is still extensive research required before a comprehensive approach to the EMS can be developed. With regards to the building information, the HV AC profile of Watt Hall needs to be completed. In order to manage the entire building effectively, it is essential to carefully document every lighting fixture, appliance, equipment cost and types, etc. With the inclusion of the HV AC, the detailed specification of the materials and appliances were significantly lacking in availability for this study. For the indoor comfort research, the continued monitoring of the indoor temperature over the course of an entire year is necessary to obtain a complete understanding of the indoor comfort profile of Watt Hall. Regarding the energy simulation, the detailed eQUEST model should be generated after obtaining the HV AC system. The ECOTECT model of Watt Hall should be used to do a more in-depth analysis than was available by this study especially with regards to the thermal analysis. 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Earthscan Publications, Limited. 166 Appendix A The Room Schedule of Watt Hall Figure A- 1 The room schedule of Watt Hall 167 Figure A- 1, continued 168 Figure A- 1, continued 169 Figure A- 1, continued 170 Figure A- 1, continued 171 Figure A- 1, continued 172 Appendix B Space Operation Schedules of Watt Hall Table B- 1 The Schedule list of Watt Hall Schedule Name Description 1 Class1 S1 The Operation Schedule of RM212 during Spring & Fall semester 2 Class2 S1 The Operation Schedule of RM214 during Spring & Fall semester 3 Class2 S2 The Operation Schedule of RM214 during Summer semester 4 Class3 S1 The Operation Schedule of RM218 during Spring & Fall semester 5 Class3 S2 The Operation Schedule of RM218 during Summer semester 6 Class4 S1 The Operation Schedule of RM102A during Spring & Fall semester 7 Class5 S1 The Operation Schedule of RM102B during Spring & Fall semester 8 Class6 S1 The Operation Schedule of RM118 during Spring & Fall semester 9 Class6 S2 The Operation Schedule of RM118 during Summer semester 10 Class7 S1 The Operation Schedule of RMB1 during Spring & Fall semester 11 Corridor S The Operation Schedule of the corridor and restrooms in Watt Hall 12 Library S1 The Operation Schedule of AFA Library during Spring & Fall semester 13 Library S2 The Operation Schedule of AFA Library during Summer semester & Break 14 Office S S The Operation Schedule of Office Ss 15 Seminar S The Operation Schedule of the meeting areas during Spring & Fall semester 16 Studio S1 The Operation Schedule of the studios during Spring & Fall semester 17 Studio S2 The Operation Schedule of the studios during Summer semester 18 Studio S3 The Operation Schedule of the studios during the break Table B- 2 The list of the operation schedules of each room in Watt Hall Table B- 2 The list of the operation schedules of each room in Watt Hall No. Rm. Name Operation Schedule Name Spring/Fall Semester Summer Semester Break WATT 3RD FLR. 300 GALLERY 300 Office S Office S Office S 302 STUDIO 302 Studio S 1 Studio S 2 Studio S 3 304 OFFICE S 304 Office S Office S Office S 306 OFFICE S 306 Office S Office S Office S 309 OFFICE S 309 Office S Office S Office S 310 OFFICE S 310 Office S Office S Office S 312 SEMINAR 312 Seminar S NA NA 315 OFFICE S 315 Office S Office S Office S 316 OFFICE S 316 Office S Office S Office S 318 OFFICE S 318 Office S Office S Office S 319 OFFICE S 319 Office S Office S Office S 321 OFFICE S 321 Office S Office S Office S 173 Table B- 2, Continued No. Rm. Name Operation Schedule Name Spring/Fall Semester Summer Semester Break 324 SEMINAR 324 Seminar S NA NA 327 OFFICE S 327 Office S Office S Office S 328 OFFICE S 328 Office S Office S Office S 330 OFFICE S 330 Office S Office S Office S 333 OFFICE S 333 Office S Office S Office S 334 OFFICE S 334 Office S Office S Office S 336 OFFICE S 336 Office S Office S Office S 337 OFFICE S 337 Office S Office S Office S 339 SEMINAR 339 Seminar S NA NA 342 OFFICE S 342 Office S Office S Office S 345 OFFICE S 345 Office S Office S Office S 346 OFFICE S 346 Office S Office S Office S 348 OFFICE S 348 Office S Office S Office S 349 OFFICE S 349 Office S Office S Office S 351 SEMINAR 351 Seminar S Seminar NA NA 354 OFFICE S 354 Office S Office S Office S 356 STUDIO 356 Studio S 1 Studio S 2 Studio S 3 358 STUDIO 358 Studio S 1 Studio S 2 Studio S 3 362 STUDIO 362 Studio S 1 Studio S 2 Studio S 3 364 STUDIO 364 Studio S 1 Studio S 2 Studio S 3 366 STUDIO 366 Studio S 1 Studio S 2 Studio S 3 368 STUDIO 368 Studio S 1 Studio S 2 Studio S 3 370 STUDIO 370 Studio S 1 Studio S 2 Studio S 3 372 STUDIO 372 Studio S 1 Studio S 2 Studio S 3 374 STUDIO 374 Studio S 1 Studio S 2 Studio S 3 380 GENERATOR 380 NA NA NA 381 TRANSFORMER 381 NA NA NA 382 MEN'S 382 Corridor S Corridor S Corridor S 383 KITCHENETTE 383 Corridor S Corridor S Corridor S 383A STORAGE 383A NA NA NA 384 WOMEN'S 384 Corridor S Corridor S Corridor S 385 FAN RM. 385 NA NA NA 386 ELECT. RM. 386 NA NA NA WATT 2ND FLR. 200 STUDIO 200 Studio S 1 Studio S 2 Studio S 3 201 STUDIO 201 Studio S 1 Studio S 2 Studio S 3 202 PINUP Corridor S Corridor S Corridor S 203 OFFICE S 203 Office S Office S Office S 203A OFFICE S 203A Office S Office S Office S 203B OFFICE S 203B Office S Office S Office S 204 OFFICE S 204 Office S Office S Office S 204A OFFICE S 204A Office S Office S Office S 174 Table B- 2, Continued No. Rm. Name Operation Schedule Name Spring/Fall Semester Summer Semester Break 205 FACULTY LOUNGE 205 Office S Office S Office S 207 STUDIO 207 Studio S 1 Studio S 2 Studio S 3 208 STUDIO 208 Studio S 1 Studio S 2 Studio S 3 208A CLOSET 208A NA NA NA 209 STUDIO 209 Studio S 1 Studio S 2 Studio S 3 209A OFFICE S 209A NA NA NA 209B CLOSET 209B NA NA NA 210 WOMEN'S 210 Corridor S Corridor S Corridor S 211 OFFICE S 211 Office S Office S Office S 212 CLASS 212 Class1 S1 NA NA 212A STORAGE 212A NA NA NA 212B STORAGE 212 B NA NA NA 213 MEN'S 213 Corridor S Corridor S Corridor S 213A VESTIBULE Corridor S Corridor S Corridor S 214 LINDHURST 214 Class2 S1 Class2 S2 NA 215 JANITOR NA NA NA 216 STORAGE 216 NA NA NA 217 CORRIDORS Corridor S Corridor S Corridor S 217A CORRIDORS Corridor S Corridor S Corridor S 217B CORRIDORS Corridor S Corridor S Corridor S 217C CORRIDORS Corridor S Corridor S Corridor S 217D CORRIDORS Corridor S Corridor S Corridor S 218 FISHBOWL 218 Class3 S1 Class3 S2 NA WATT 1ST FLR. 101 GALLERY Office S Office S Office S 101A STORAGE NA NA NA 101B STORAGE NA NA NA 102 VESTIBULE 102 Corridor S Corridor S Corridor S 102A CLASSROOM 102A Class4 S1 NA NA 102B CLASSROOM 102B Class5 S1 NA NA 103 OFFICE S 103 Office S Office S Office S 103A OFFICE S 103A Office S Office S Office S 103B OFFICE S 103B Office S Office S Office S 103C OFFICE S 103C Office S Office S Office S 140 OFFICE S 104 Office S Office S Office S 104A CONF 104A Office S Office S Office S 104B OFFICE S 104B Office S Office S Office S 104C COPY RM 104C Office S Office S Office S 105 STUDIO 105 Studio S 1 Studio S 2 Studio S 3 107 STUDIO 107 Studio S 1 Studio S 2 Studio S 3 108 LOCKER 108 Corridor S Corridor S Corridor S 108A OFFICE S 108A Office S Office S Office S 175 Table B- 2, Continued No. Rm. Name Operation Schedule Name Spring/Fall Semester Summer Semester Break 108B OFFICE S 108B Office S Office S Office S 108C EQUIP 108C NA NA NA 108D TOOL RM NA NA NA 108E STUDIO 108E Studio S 1 Studio S 2 Studio S 3 109 WOMEN'S 109 Corridor S Corridor S Corridor S 109A VESTIBULE Corridor S Corridor S Corridor S 110 OFFICE S 110 Office S Office S Office S 111 OFFICE S 111 Office S Office S Office S 112 OFFICE S 112 Office S Office S Office S 113 JAN 113 NA NA NA 114 EQUIP 114 NA NA NA 114A MENS 114A Corridor S Corridor S Corridor S 114B VESTIBULE Corridor S Corridor S Corridor S 115 CLOSET 115 NA NA NA 116 WORK RM 116 NA NA NA 116A OFFICE S 116A Corridor S Corridor S Corridor S 117 VESTIBULE 117 Corridor S Corridor S Corridor S 117A OFFICE S 117A Office S Office S Office S 117B OFFICE S 117B Office S Office S Office S 118 CLASSROOM 118 Class6 S1 Class6 S2 NA 119 LOBBY Corridor S Corridor S Corridor S WATT MEZ. M14 MECH. RM. M14 NA NA NA M14A MECH. RM. M14A NA NA NA M14B ELEV. LOBBY M14B Library S1 Library S2 Library S2 M15 STORAGE M15 NA NA NA M16 LIBRARY Library S1 Library S2 Library S2 M16A DARKRM. M16A Library S1 Library S2 Library S2 M16B READING RM. M16B Library S1 Library S2 Library S2 M16C BRIDGE M16C Library S1 Library S2 Library S2 WATT BSMNT. B1 LECTURE B1 Class7 S1 NA NA B1A STORAGE B1A NA NA NA B1B STORAGE B1B NA NA NA B1C TEL. EQUIP. B1C NA NA NA B1D VESTIBULE B1D Corridor S Corridor S Corridor S B1E STORAGE B1E NA NA NA B1F STORAGE B1F NA NA NA B1G STORAGE B1G NA NA NA B1L CORRIDOR B1L Corridor S Corridor S Corridor S B2 DARKRM. B2 Studio S 1 Studio S 2 Studio S 3 B2A VESTIBULE B2A Studio S 1 Studio S 2 Studio S 3 176 Table B- 2, Continued No. Rm. Name Operation Schedule Name Spring/Fall Semester Summer Semester Break B2B OFFICE S B2B Studio S 1 Studio S 2 Studio S 3 B2C COPY RM. B2C Studio S 1 Studio S 2 Studio S 3 B2D DARKRM. B2D Studio S 1 Studio S 2 Studio S 3 B2E DARKRM. B2E Studio S 1 Studio S 2 Studio S 3 B2F DARKRM. B2F Studio S 1 Studio S 2 Studio S 3 B2G STORAGE NA NA NA B3 MEN'S B3B Corridor S Corridor S Corridor S B3A STORAGE B3A NA NA NA B3B MEN'S B3B Corridor S Corridor S Corridor S B3C WOMEN'S B3C Corridor S Corridor S Corridor S B4 STACK AREA Library S1 Library S2 Library S2 B4A OFFICE S B4A Office S Office S Office S B4B OFFICE S B4B Office S Office S Office S B4C LOUNGE Office S Office S Office S B4D OFFICE S B4D Office S Office S Office S B4E STORAGE B4E NA NA NA B4F READING RM. B4F Library S1 Library S2 Library S2 B4G STACK AREA B4G Library S1 Library S2 Library S2 B4H STACK AREA B4H Library S1 Library S2 Library S2 B4I VESTIBULE B4I Library S1 Library S2 Library S2 B4J AFA LIBRARY Library S1 Library S2 Library S2 B4K READING RM. B4K Library S1 Library S2 Library S2 B4L SEMINAR RM. B4L Library S1 Library S2 Library S2 B4M STORAGE B4M NA NA NA B4N COPY RM B4N Library S1 Library S2 Library S2 B4O STORAGE B4O NA NA NA B5 STORAGE B-5 NA NA NA B6 CPU LAB B6 Office S Office S Office S B7 CLIPPER LAB B7 Office S Office S Office S B8 ELECT EQ B8 NA NA NA B9A OFFICE S B9A Office S Office S Office S B10 STUDIO B10 Studio S 1 Studio S 2 Studio S 3 B10A PHOTO LAB B10A Office S Office S Office S B10B OFFICE S B10B Office S Office S Office S B11 OFFICE S B11 Office S Office S Office S B12 STUDIO B12 Studio S 1 Studio S 2 Studio S 3 B15 WOMEN'S B15 Corridor S Corridor S Corridor S 177 Figure B- 1 The operation schedules of Watt Hall 178 Figure B- 1, Continued 179 Figure B- 1, Continued 180 Appendix C Envelope Material Details and Revit Input of Watt Hall Table C- 1 Main construction materials of Watt Hall Material Type Abbr. Construction Description U-value* (Btu/h-ft 2 -F°) Roof WAT NR New Roof: on the top of 3 rd floor 0.092 Exterior Wall WAT OE-1 Old Exterior Wall 1: center of the first façade type. Locate at the 1 st and 2 nd floor studio area. 0.365 WAT OE-2 Old Exterior Wall 2: upper of the second façade type. Locate at the eastside office area. 0.477 WAT OE-3 Old Exterior Wall 3: below grade wall. 0.595 WAT OE-4 Old Exterior Wall 4: the metal penal all on the west side of Watt Hall 0.155 WAT NE-1 New Exterior 1: facing out ward, lower part of the 3 rd floor office façade. 0.076 WAT NE-2 New Exterior Wall 2: facing patio, lower part of the 3 rd floor offices façade. 0.067 WAT NE-3 New Exterior Wall 3: Upper part of the 3 rd floor offices’ façade. 0.668 WAT NE-4 New Exterior Wall 4: the aluminum panel on the center of the 3 rd floor office façade. 0.075 Interior Wall WAT OI Old Interior Wall: represent the interior wall from basement to 2 nd floor. 0.111 WAT NI New Interior Wall: represent the interior wall on 3 rd floor. 0.062 Floor WAT OF-1 Old Floor: represent the floor on basement. 0.395 WAT OF-2 Old Floor: represent the floor from 1 st and 2 nd floor. 0.403 WAT NF New Floor: represent the floor on 3 rd floor. 0.157 Ceiling WAT OC Old Ceiling: the drop down ceiling from basement to 2 nd floor. 0.515 WAT NC New Ceiling: the drop down ceiling on 3 rd floor restroom and kitchen area. 0.805 Door WAT OD Old Door: the opaque door on the Westside of the building 0.820 Glazing WAT OG Old glazing: represent the glazing from basement to 2 nd floor. 0.956 WAT NG-1 New glazing: represent the glazing on 3 rd floor window. 0.285 WAT NG-2 New glazing: represent the glazing on 3 rd floor door. 0.285 * The U‐Values of materials mainly are the calculated results by eQUEST except the glazing. 181 Figure C- 1 The illustration of the location of the main construction materials in Watt Hall 182 Table C- 2 The details, Revit model input and thermal properties of Watt Hall’s envelope materials (AC Martin Partners, Inc, 2005; Killingsworth, Brady & Associates, Architects Inc., 1971; Lin, Revit Model of Watt Hall, 2008; Lin, The eQUEST Model of Watt Hall, 2008) Material Name & U-Value Material Details & Revit Input WAT NR U-value 0.092 Btu/h-ft 2 -F° 183 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OE-1 U-value 0.365 Btu/h-ft 2 -F° 184 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OE-2 U-value 0.477 Btu/h-ft 2 -F° 185 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OE-3 U-value 0.595 Btu/h-ft 2 -F° . 186 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OE-4 U-value 0.155 Btu/h-ft 2 -F° 187 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NE-1 U-value 0.076 Btu/h-ft 2 -F° 188 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NE-2 0.067 Btu/h-ft 2 -F° 189 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NE-3 0.668 Btu/h-ft 2 -F° 190 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NE-4 0.075 Btu/h-ft 2 -F° 191 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OI 0.111 Btu/h-ft 2 -F° 192 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NI 0.062 Btu/h-ft 2 -F° 193 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OF-1 0.395 Btu/h-ft 2 -F° 194 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OF-2 0.403 Btu/h-ft 2 -F° 195 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NF 0.157 Btu/h-ft 2 -F° . 196 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OC 0.515 Btu/h-ft 2 -F° 197 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NC 0.805 Btu/h-ft 2 -F° 198 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OD 0.820 Btu/h-ft 2 -F° 199 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT OG 0.956 Btu/h-ft 2 -F° 200 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NG-1 0.28-0.29 Btu/h-ft 2 -F° (PPG Industries, Inc., 2008) 201 Table C- 2, Continued Material Name & U-Value Material Details & Revit Input WAT NG-2 0.28-0.29 Btu/h-ft 2 -F° 202 Appendix D The Construction Materials Input and Calculated U-Values in eQUEST and ECOTECT Model of Watt Hall Table D- 1 The materials input and calculated U-values in eQUEST and ECOTECT model of Watt Hall (Lin, The ECOTECT Model of Watt Hall, 2008; Lin, The eQUEST Model of Watt Hall, 2008) Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT NR eQUEST 0.092 ECOTECT 0.104 203 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T OE-1 eQUEST 0.371 ECOTECT 0.250 204 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T OE-2 eQUEST 0.477 ECOTECT 0.474 205 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T OE-3 eQUEST 0.595 ECOTECT 0.497 206 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T OE-4 eQUEST 0.155 ECOTECT 0.144 207 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T NE-1 eQUEST 0.076 ECOTECT 0.074 208 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T NE-2 eQUEST 0.067 ECOTECT 0.063 209 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T NE-3 eQUEST 0.668 ECOTECT 0.364 210 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T NE-4 eQUEST 0.075 ECOTECT 0.076 211 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT OI eQUEST 0.111 ECOTECT 0.106 212 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT NI eQUEST 0.062 ECOTECT 0.060 213 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T OF-1 eQUEST 0.395 ECOTECT 0.349 214 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T OF-2 eQUEST 0.403 ECOTECT 0.35576 215 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT NF eQUEST 0.157 ECOTECT 0.1497 216 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT OC eQUEST 0.515 ECOTECT 0.440 217 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT NC eQUEST 0.805 ECOTECT 0.636 218 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT OD eQUEST 0.820 ECOTECT 0.491 219 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WAT OG eQUEST N/A ECOTECT 0.956 220 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T NG-1 eQUEST NA ECOTECT 0.285 221 Table D- 1, Continued Material Abbr. U-Value Btu/h-ft 2 -F° eQUEST and ECOTECT Construct Materials Input WA T NG-2 eQUEST NA ECOTECT 0.285 222 Appendix E Lighting Schedule of Watt Hall Figure E- 1 Lighting Schedule of Watt Hall (Lin, Revit Model of Watt Hall, 2008) 223 Figure E- 1, Continued 224 Figure E- 1, Continued 225 Figure E- 1, Continued 226 Figure E- 1, Continued 227 Figure E- 1, Continued 228 Figure E- 1, Continued 229 Figure E- 1, Continued 230 Table E- 1 Lighting Fixtures of Watt Hall DL1-INCAN.-120watt DL2-INCAN.-100watt DL3-INCAN.-60 watt DL4-INCAN.-60 watt DL5-INCAN.-60watt DL6-FLUOR-40watt DL7-INCAN.-65watt F1-1x FLUOR-54watt F2-48" FLUOR-64watt F3-2x FLUOR-2x32watt F4-3xFLUOR-100watt F5-9" FLUOR-40watt F6-1xFLUOR-60watt F7-1XHID-400watt F8-HID-400watt F9-1x9" FLUOR-30watt F10-4-FLUOR-4x40watt F11-2xT-8U-2x32watt F12-3xT-8-3x32watt F13-4xT-8-4x32watt 231 Table E- 1, Continued F14-1xFLOUR-54watt F15-3xT-8-3x32watt F16-2xT-5-2x28watt F17-1xFLUOR-64watt F18-2xT-8-2x32watt F19-FLUOR-64watt F20-3xFLUOR-3x32watt F21-3x48" FLUOR-3x32 F22-4xT-8-4x32 F23-2xT-8-2x32watt F24-2xT-8-2x32watt F25-2xT-8U-2x32watt F26-3xT-8-6x32watt F27-2xT-8-2x32watt F28-1xT-8-32watt SP1-1xINCAN.-40watt SP2-1xINCAN.-100 TL1-INCAN.-60watt TL2-INCAN.-100watt TL3-INCAN.-60watt 232 Table E- 1, Continued TL4-INCAN.-60watt TL5-INCAN.-60watt TL6-INCAN.-60watt TL7-INCAN.-60watt WW-INCAN.-60watt 233 Appendix F Devices Survey of Watt Hall Figure F- 1 Devices Survey of Watt Hall (Lin, Revit Model of Watt Hall, 2008) 234 Figure F- 1, Continued 235 Figure F- 1, Continued 236 Figure F- 1, Continued 237 Figure F- 1, Continued 238 Figure F- 1, Continued 239 Figure F- 1, Continued 240 Appendix G Cal-ARCH Benchmarking Results Figure G- 1 The results of Cal-Arch benchmarking Watt Hall with all building types in California (CALARCH, 2003) 241 Figure G- 2 The results of Cal-Arch benchmarking Watt Hall with office building types in California (CALARCH, 2003) 242 Figure G- 3 The results of Cal-Arch benchmarking Watt Hall with education building type in California (CALARCH, 2003) 243 Figure G- 4 The results of Cal-Arch benchmarking Watt Hall with all building types in California south coast climate (CALARCH, 2003) 244 Figure G- 5 The results of Cal-Arch benchmarking Watt Hall with office building types in California south coast climate (CALARCH, 2003) 245 Figure G- 6 The results of Cal-Arch benchmarking Watt Hall with education building types in California south coast climate (CALARCH, 2003) 246 Appendix H Data Acquisition System (DAS) Plans and Details of Watt Hall Figure H- 1 Data Acquisition System (DAS) plans and schedules of Watt Hall (Lin, Revit Model of Watt Hall, 2008) 247 Figure H- 1, Continued 248 Figure H- 1, Continued 249 Figure H- 1, Continued 250 Figure H- 1, Continued 251 Figure H- 1, Continued 252 Figure H- 1, Continued 253 Figure H- 1, Continued 254 Figure H- 1, Continued 255 Figure H- 1, Continued 256 Appendix I The Normalization Details of the Data Acquisition System Figure I- 1 Phase I all data loggers’ temperature normalization data with average 257 Figure I- 2 Phase I WATB-1 temperature normalization data with average Figure I- 3 Phase I WATB-2 temperature normalization data with average Figure I- 4 Phase I WATB-3 temperature normalization data with average Figure I- 5 Phase I WAT1-1 temperature normalization data with average Figure I- 6 Phase I WAT1-2 temperature normalization data with average Figure I- 7 Phase I WAT2-1 temperature normalization data with average 258 Figure I- 8 Phase I WAT2-2 temperature normalization data with average Figure I- 9 Phase I WAT2-3 temperature normalization data with average Figure I- 10 Phase I WAT3-2 temperature normalization data with average 259 Figure I- 11 Phase II all data loggers’ temperature normalization data with average 260 Figure I- 12 Phase II WATB-1 temperature normalization data with average Figure I- 13 Phase II WATB-2 temperature normalization data with average Figure I- 14 Phase II WATB-3 temperature normalization data with average Figure I- 15 Phase II WATB-4 temperature normalization data with average Figure I- 16 Phase II WATB-5 temperature normalization data with average Figure I- 17 Phase II WATB-6 temperature normalization data with average 261 Figure I- 18 Phase II WAT1-1 temperature normalization data with average Figure I- 19 Phase II WAT1-2 temperature normalization data with average Figure I- 20 Phase II WAT1-3 temperature normalization data with average Figure I- 21 Phase II WAT1-4 temperature normalization data with average Figure I- 22 Phase II WAT1-5 temperature normalization data with average Figure I- 23 Phase II WAT1-6 temperature normalization data with average 262 Figure I- 24 Phase II WAT1-7 temperature normalization data with average Figure I- 25 Phase II WAT2-1 temperature normalization data with average Figure I- 26 Phase II WAT2-2 temperature normalization data with average Figure I- 27 Phase II WAT2-3 temperature normalization data with average Figure I- 28 Phase II WAT2-4 temperature normalization data with average Figure I- 29 Phase II WAT2-5 temperature normalization data with average 263 Figure I- 30 Phase II WAT2-6 temperature normalization data with average Figure I- 31 Phase II WAT3-1 temperature normalization data with average Figure I- 32 Phase II WAT3-2 temperature normalization data with average Figure I- 33 Phase II WAT3-3 temperature normalization data with average Figure I- 34 Phase II WAT3-4 temperature normalization data with average Figure I- 35 Phase II WAT3-5 temperature normalization data with average 264 Figure I- 36 Phase II WAT3-6 temperature normalization data with average Figure I- 37 Phase I all data loggers’ RH normalization data with average 265 Figure I- 38 Phase I WAT2-1 RH normalization data with average Figure I- 39 Phase I WAT2-2 RH normalization data with average Figure I- 40 Phase I WAT3-2 RH normalization data with average Figure I- 41 Phase I WAT3-3 RH normalization data with average 266 Figure I- 42 Phase II all data loggers’ temperature normalization data with average 267 Figure I- 43 Phase II WATB-1 RH normalization data with average Figure I- 44 Phase II WATB-2 RH normalization data with average Figure I- 45 Phase II WATB-3 RH normalization data with average Figure I- 46 Phase II WATB-4 RH normalization data with average Figure I- 47 Phase II WAT1-2 RH normalization data with average Figure I- 48 Phase II WAT1-3 RH normalization data with average 268 Figure I- 49 Phase II WAT1-4 RH normalization data with average Figure I- 50 Phase II WAT1-5 RH normalization data with average Figure I- 51 Phase II WAT1-6 RH normalization data with average Figure I- 52 Phase II WAT1-7 RH normalization data with average Figure I- 53 Phase II WAT2-1 RH normalization data with average Figure I- 54 Phase II WAT2-2 RH normalization data with average 269 Figure I- 55 Phase II WAT2-3 RH normalization data with average Figure I- 56 Phase II WAT2-4 RH normalization data with average Figure I- 57 Phase II WAT2-5 RH normalization data with average Figure I- 58 Phase II WAT2-6 RH normalization data with average Figure I- 59 Phase II WAT3-1 RH normalization data with average Figure I- 60 Phase II WAT3-2 RH normalization data with average 270 Figure I- 61 Phase II WAT3-3 RH normalization data with average Figure I- 62 Phase II WAT3-4 RH normalization data with average Figure I- 63 Phase II WAT3-5 RH normalization data with average Figure I- 64 Phase II WAT3-6 RH normalization data with average

Abstract (if available)

Abstract As a place to cultivate future architects, the School of Architecture stands in the leading position to demonstrate how to renovate Watt Hall into a carbon-neutral and low-energy-consumption building through the implementation of the ISO14000 Environmental Management System. As a part of the EMS baseline research project led by Thomas Spiegelhalter, this initial study focuses on the Energy Management System. The main work of this study contains as-built data collection, generating a building information model, establishing energy consumption models, measuring and monitoring the indoor environmental comfort performance, and research on energy consumption profiles, and post-occupancy profiles. This study will not only reveal Watt Hall 's current energy performance but also set the baseline and propose feasible energy consumption improvement strategies. The effectiveness of thesis strategies will then be demonstrated through computer modeling, the most effective approaches then used to generate a long-term energy monitoring system and energy management plan.

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Asset Metadata

Creator Lin, Shih-Hsin (author)

Core Title Watt Hall energy management system implementation initiative

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Publication Date 07/21/2008

Defense Date 03/01/2008

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

Tag building energy consumption,building energy performance,energy management system initiative,OAI-PMH Harvest

Language English

Advisor Spiegelhalter, Thomas (committee chair), Kapeller, Christoph (committee member), Mozes, Karen (committee member), Schiler, Marc (committee member)

Creator Email shihhsinlin@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m1367

Unique identifier UC1128554

Identifier etd-Lin-20080721 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-200374 (legacy record id),usctheses-m1367 (legacy record id)

Legacy Identifier etd-Lin-20080721.pdf

Dmrecord 200374

Document Type Thesis

Rights Lin, Shih-Hsin

Type texts

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

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu