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

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

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Content STUDIES IN PRELIMINARY DESIGN OF FENESTRATION: BALANCING DAYLIGHT HARVESTING AND ENERGY CONSUMPTION by Geman Wu A Thesis Presented to the FACULTY OF THE USC SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF BUILDING SCIENCE May 2012 Copyright 2012 Geman Wu ii Acknowledgements I would like to express my sincere gratitude to everybody who helped me to complete this work and two years of graduate study in USC. It was developed as part of Southern California Edison’s Emerging Technologies program. I would like to express my deepest thanks to Prof. Karen Kensek, the committee chair of my thesis, for her guidance and encouragement during the whole process. Thanks to my committee member Prof. Marc Schiler, the director of building science department, for helping me determine parameters and metrics. Also thanks to my committee member, Prof. Peter Simmonds, and my advisor James Benya for help me solve technical problems and keep me work on the right direction. Thanks to J. Alstan Jakubiec and Jon Sargent for their help on DIVA for Rhino and DIVA for Grasshopper. Also thanks to the Prof. Ed Woll, Lisa Heschong, and Mudit Saxena for their help and ideas. And finally, thanks to my parents and families for giving me support when I most needed it. iii Table of Contents Acknowledgements ............................................................................................................. ii List of tables ........................................................................................................................ v List of figures ..................................................................................................................... vi Abstract ............................................................................................................................. xii Chapter 1: Introduction ....................................................................................................... 1 1.1. Background ............................................................................................................ 1 1.1.1. Indoor Artificial Lighting ................................................................................ 5 1.1.2. Daylight Harvesting ........................................................................................ 8 1.1.3. Trade-Offs ..................................................................................................... 10 1.2. Current Energy And Daylight Simulation Tools ................................................. 16 1.3. Research Objective .............................................................................................. 19 1.4. Conclusion ........................................................................................................... 19 Chapter 2: Research .......................................................................................................... 21 2.1. Building Codes .................................................................................................... 21 2.1.1 Title 24 .............................................................................................................. 21 2.1.2 Ashrae 90.1-2007.............................................................................................. 22 2.1.3 Leed Nc 2009.................................................................................................... 24 2.2. Preliminary Analysis ............................................................................................ 27 2.2.1 Comfen 4.0 ....................................................................................................... 28 2.2.2 Equest 3.64 ....................................................................................................... 31 2.2.3 Diva For Grasshopper (Viper Component) ...................................................... 34 2.2.4 Conclusion ........................................................................................................ 40 Chapter 3: Methodology ................................................................................................... 41 3.1 Introduction ............................................................................................................. 41 3.2 Model Description .................................................................................................. 42 3.2.1 Geometry .......................................................................................................... 42 3.2.2 Main Parameters ............................................................................................... 42 3.3 Energy Simulation Parameters ................................................................................ 43 3.3.1 Climate Zones ................................................................................................... 43 3.3.2 Lighting Design Level ...................................................................................... 44 3.3.3 Window Parameters And Shading Devices ...................................................... 44 Chapter 4: Simulation Results .......................................................................................... 50 4.1. Window Height (Placement) ............................................................................... 50 4.1.1. 0.1m From Top Of The Wall ........................................................................ 51 4.1.2. 0.7m From Top Of The Wall ........................................................................ 54 4.1.3. Middle Of The Wall (1.5 M From Top) ........................................................ 57 4.2. Illuminance Level ................................................................................................ 61 4.2.1 500 Lux Vs 350 Lux ......................................................................................... 61 iv 4.3. Window Aspect Ratio .......................................................................................... 65 4.3.1. South Facing Window ................................................................................... 66 4.3.2. East Facing Window ..................................................................................... 69 4.3.3. West Facing Window .................................................................................... 72 4.3.4. North Facing Window ................................................................................... 74 4.4. Glazing ................................................................................................................. 76 4.4.1. South.............................................................................................................. 77 4.4.2. East ................................................................................................................ 78 4.4.3. West ............................................................................................................... 78 4.4.4. North.............................................................................................................. 79 4.5. Exterior Shading .................................................................................................. 79 4.5.1. Exterior Overhang-60% Projection ............................................................... 80 4.5.2. Exterior Overhang-100% Projection ............................................................. 82 4.6. Summary .............................................................................................................. 84 Chapter 5: Analysis ........................................................................................................... 85 5.1. Impact Of Variables ............................................................................................. 85 5.1.1. Window Placement And Illuminance Level ................................................. 85 5.1.2. Window Aspect Ratio ................................................................................... 86 5.1.3. Window Glazing ........................................................................................... 87 5.1.4. Exterior Overhang ......................................................................................... 88 5.2. Fenestration Guidelines ....................................................................................... 89 5.3. Building Code Compliance .................................................................................. 91 Chapter 6: Conclusion And Future Work ......................................................................... 93 6.1. Conclusion ........................................................................................................... 93 6.2. Limitation ............................................................................................................. 94 6.3. Future Work ......................................................................................................... 95 6.3.1. Study Of Daylight Autonomy And Over-Illumination ................................. 95 6.3.2. Study Of Occupant Behavior ........................................................................ 96 6.3.3. Study Of Interior Blinds And Schedule ........................................................ 97 6.3.4. Study Of Glare And Visual Comfort............................................................. 97 Bibliography ..................................................................................................................... 98 Appendix A-Parametric And Simulation Tool Description............................................ 101 Appendix B-Energy Performance Results From Equest ................................................ 106 Appendix C-Energy Performance Results Of Cz 15 From Diva .................................... 114 v List of Tables Table 1 Basics of glazing properties ................................................................................. 14 Table 2 A selection of existing papers on the topic of trade-off between daylight harvesting and energy demand .......................................................................................... 15 Table 3 Summary of software regarding lighting and energy consumptions ................... 17 Table 4 Summary of Title 24-2008 ................................................................................... 21 Table 5 Window requirement of Title 24, source: Title 24 Nonresidential and residential fenestration stakeholder meeting June 9, 2011 ............................................... 22 Table 6 Summary of ASHRAE 90.1-2007 ....................................................................... 23 Table 7 ASHRAE 90.1-2007 baseline for modeling ........................................................ 24 Table 8 Summary of LEED NC 2009-lighting and energy .............................................. 25 Table 9 Basic settings for office model in COMFEN ....................................................... 28 Table 10-Results from COMFEN-cooling, lighting and total energy .............................. 30 Table 11 Basic settings of office model in EQUEST ....................................................... 32 Table 12 Results of parametric runs in EQUEST ............................................................. 33 Table 13 Basic settings in DIVA for Grasshopper ........................................................... 38 Table 14 Monthly energy consumption from DIVA for Grasshopper ............................. 38 Table 15 Settings of main parameters ............................................................................... 43 Table 16 Glazing properties .............................................................................................. 46 Table 17 Fixed parameters used in all simulations ........................................................... 50 vi List of Figures Figure 1 Energy Consumption and Electricity Consumption by Sector (Architecture 2030, 2011) ................................................................................................... 1 Figure 2 2030 Challenge- Energy Reduction (Architecture 2030, 2010) ........................... 2 Figure 3 End use energy break down (ENERGY STAR Building Manual, 2006) ............ 5 Figure 4 Demand for energy (Southern California Gas Company, 1996) .......................... 8 Figure 5 DFcalc daylight calculation results-window on the top and window in the mid-height ................................................................................................................... 11 Figure 6 DFcalc daylight calculation results-rectangular window and square window .............................................................................................................................. 12 Figure 7 Villa Savoya, horizontal windows VS vertical windows (Wikipedia database, 2008) ................................................................................................................. 13 Figure 8 Basic settings in COMFEN ................................................................................ 29 Figure 9 Summary of annual energy use for WWR 0%, 10%, 20% and 30% ................. 29 Figure 10 Simulation results of all scenarios, including heating, cooling, lighting, fans and peak demand ........................................................................................ 30 Figure 11 Annual energy consumption results-COMFEN-South window ....................... 31 Figure 12 3D geometry of office ...................................................................................... 32 Figure 13 Parametric runs in detail wizard for WWR 0%, 10%, 20%, 30%, 40%, 50%, 60% and 80% ........................................................................................................... 32 Figure 14 Annual energy consumption results-EQUEST-South window ........................ 33 Figure 15 3D geometry in Rhino and Grasshopper definition .......................................... 35 Figure 16 Viper component definitions ............................................................................ 36 Figure 17 Construction Assembly-default options and custom options ........................... 36 Figure 18 Window unit component-default and custom option of glass layers ............... 37 vii Figure 19 Window unit component-custom options of glazing properties, and fixed shade component ..................................................................................................... 37 Figure 20 Excel exporter-export cooling and lighting use to Excel ................................. 38 Figure 21 Annual energy consumption results-DIVA-South window ............................. 39 Figure 22 Model of the office and parameters of this study ............................................. 42 Figure 23 Diagram of WWR, window height and window w/h ratio ............................... 46 Figure 24 Exterior overhang-South WWR 10%-60% projection, depth of shade=0.6m ....................................................................................................................... 47 Figure 25 Exterior overhang-South WWR 10%-100% projection, depth=0.75m ............ 47 Figure 26 Exterior overhang-South WWR 20%-60% projection, depth=0.65m .............. 48 Figure 27 Exterior overhang-South WWR 20%-100% projection, depth=0.85m ............ 48 Figure 28 Exterior overhang-South WWR 30%-60% projection, depth=0.75m .............. 49 Figure 29 Exterior overhang-South WWR 30%-100% projection, depth=1m ................. 49 Figure 30 Window variations of window height and window-to-wall ratios ................... 51 Figure 31 Annual Energy Consumption-window on top-500 lux-South .......................... 51 Figure 32 Annual Energy Consumption-window on top-500 lux-East ............................ 52 Figure 33 Annual Energy Consumption-window on top-500 lux-West ........................... 53 Figure 34 Annual Energy Consumption-window on top-500 lux-North .......................... 53 Figure 35 Annual Energy Consumption-window 0.7m from top-500 lux-South ............. 54 Figure 36 Annual Energy Consumption-window 0.7m from top-500 lux-East ............... 55 Figure 37 Annual Energy Consumption-window 0.7m from top-500 lux-West .............. 56 Figure 38 Annual Energy Consumption-window 0.7m from top-500 lux-North ............. 56 Figure 39 Annual Energy Consumption-window in the middle-500 lux-South ............... 57 Figure 40 Annual Energy Consumption-window in the middle-500 lux-East ................. 58 viii Figure 41 Annual Energy Consumption-window in the middle-500 lux-West ................ 59 Figure 42 Annual Energy Consumption-window in the middle-500 lux-North ............... 60 Figure 43 Annual Energy Consumption-window on top-350 lux-South .......................... 62 Figure 44 Annual Energy Consumption-window 0.7m from top-350 lux-South ............. 62 Figure 45 Annual Energy Consumption-window on top-350 lux-East ............................ 63 Figure 46 Annual Energy Consumption-window on top-350 lux-West ........................... 64 Figure 47 Annual Energy Consumption-window on top-350 lux-North .......................... 64 Figure 48 Window variations for w/h ratios ..................................................................... 66 Figure 49 Annual Energy Consumption-WWR 10%-window aspect ratio-South ........... 66 Figure 50 Annual Energy Consumption-WWR 20%-window aspect ratio-South ........... 67 Figure 51 Annual Energy Consumption-WWR 30%-window aspect ratio-South ........... 67 Figure 52 Annual Energy Consumption-Optimal window aspect ratio-South ................. 68 Figure 53 Annual Energy Consumption-WWR 20%-window aspect ratio-East .............. 69 Figure 54 Annual Energy Consumption-WWR 30%-window aspect ratio-East .............. 70 Figure 55 Annual Energy Consumption-WWR 40%-window aspect ratio-East .............. 70 Figure 56 Annual Energy Consumption-Optimal window aspect ratio-East ................... 71 Figure 57 Annual Energy Consumption-WWR 20%-window aspect ratio-West ............ 72 Figure 58 Annual Energy Consumption-WWR 30%-window aspect ratio-West ............ 72 Figure 59 Annual Energy Consumption-WWR 40%-window aspect ratio-West ............ 73 Figure 60 Annual Energy Consumption-Optimal window aspect ratio-West .................. 73 Figure 61 Annual Energy Consumption-WWR 20%-window aspect ratio-North ........... 74 Figure 62 Annual Energy Consumption-WWR 30%-window aspect ratio-North ........... 75 Figure 63 Annual Energy Consumption-WWR 40%-window aspect ratio-North ........... 75 Figure 64 Annual Energy Consumption-Optimal window aspect ratio-North ................. 76 ix Figure 65 Annual Energy Consumption-Optimal WAR-better glazing-South................. 77 Figure 66 Annual Energy Consumption-Optimal WAR-better glazing-East ................... 78 Figure 67 Annual Energy Consumption-Optimal WAR-better glazing-West .................. 78 Figure 68 Annual Energy Consumption-Optimal WAR-better glazing-North ................. 79 Figure 69 Annual Energy Consumption-60% overhang-base glazing-South ................... 80 Figure 70 Annual Energy Consumption-exterior overhang-base glazing-WWR 20%-South......................................................................................................................... 81 Figure 71 Annual Energy Consumption-60% overhang-better glazing-South ................. 82 Figure 72 Annual Energy Consumption-100% overhang-base glazing-South ................. 82 Figure 73 Annual Energy Consumption-100% overhang-better glazing-South ............... 83 Figure 74 Analysis of window placement and illuminance level ..................................... 85 Figure 75 Analysis of window aspect ratio ....................................................................... 86 Figure 76 Analysis of window glazing ............................................................................. 87 Figure 77 Analysis of exterior overhang .......................................................................... 88 Figure 78 Fenestration guidelines for Climate Zone 6 (Los Angeles) and for Climate Zone 15 (Blythe) ................................................................................................. 89 Figure 79 Energy savings based on different conditions .................................................. 91 Figure 80 Summary of credits and prerequisites that this study would help achieve .............................................................................................................................. 92 Figure 81 Settings in Galapagos ..................................................................................... 102 Figure 82 Galapagos Editor-Evolutionary Solver........................................................... 102 Figure 83 Viper component definitions .......................................................................... 104 Figure 84 Construction Assembly-default options and custom options ......................... 105 x Figure 85 Window unit component-default and custom option of glass layers ............. 105 Figure 86 Window unit component-custom options of glazing properties, and fixed shade component ................................................................................................... 105 xi Abstract The early decisions made during the design phase of a building regarding the choice of windows have a large impact on future energy consumption. Although the final selection depends on many issues not directly related to energy concerns including aesthetics, cost, material, views, and client preferences, energy consumption is a major factor for several reasons. These include environmental concerns, financial aspects, code compliance, operations and maintenance over the lifetime of the building, and occupant comfort. One technique for saving energy is to harvest daylight; this lessens the amount of electricity needed for indoor artificial lighting while maintaining adequate lighting levels. There are trade-offs, however, as larger windows that allow more daylight can be detrimental in other areas, such as increased heating and cooling loads depending on the location of the building, the climate, and even the season as benefits and drawbacks change over the year. This thesis explores balancing daylight harvesting and energy demands of fenestration in the early design stage for office buildings in two climate zones in California. Window orientation, height, aspect ratio, window-to-wall ratio, lighting design level, glazing, and exterior shading are parameters that were analyzed by DIVA for Grasshopper, EQUEST, and COMFEN. The simulation results provide guidelines for designers reducing cooling loads and electric lighting use throughout the year. These guidelines are, for example, window-to-wall ratio of 10%-30% is recommended for south and window-to-wall ratios xii of 30%-60% promise better energy performance on north, a window-aspect-ratio of 2/1 saves most energy load for all orientations. Hypothesis There is an optimal window-to-wall ratio, window height, window aspect ratio, glazing and exterior shading devices for office buildings in specific climate zones in California that take into account the trade-off between better daylight performance with less energy load of electric lighting and cooling. 1 Chapter 1: Introduction 1.1. BACKGROUND Buildings in the U.S. use 49 % of all primary energy consumption compared with 11.7% for transportation and 22.7% for industry according to the U.S. Energy Information Administration (EIA). (Figure 1) The building energy consumption has grown quickly in the past 50 years, and it is expected to grow faster than the other sectors in the coming 20 years. Building operations consume 77% of the electricity consumption in U.S. (Figure 1) Furthermore, 76% of building energy consumption is supplied by fossil fuels, and buildings emit 46% of the total greenhouse gases, which contribute the most to climate change. Figure 1 Energy Consumption and Electricity Consumption by Sector (Architecture 2030, 2011) The 2030 Challenge’s main goal is to reduce building energy consumption from 60 % (today) to 100 % (2030) through fossil fuel energy reduction. (Figure 2) Energy efficient design strategies, on-site renewable technologies, and off-site renewable energy systems are recommended to meet the target of carbon neutral by 2030. As buildings are large consumers of energy, savings in this area will have a big impact. 2 The EUI (energy use intensity), a unit that measures a building’s energy use, is nearly twice as high for commercial buildings as it is for residential buildings. Moreover, the buildings consume 34 % of the total commercial building energy in California. This percentage is based on the results from CEC commercial end use forecasting database. Figure 2 2030 Challenge- Energy Reduction (Architecture 2030, 2010) Early decisions when designing a building have a great impact on future energy consumption. With the upswing in concern for energy efficient buildings, it is useful to have architects be able to study decisions like building orientation, window/wall ratios, glazing choices, and even shading devices earlier in the design process. There has also been increasing sophistication, accuracy, and user friendliness of software available for performance-based simulation including day lighting and energy calculations, with the 3 possibility of exploring trade-off in design – for example between increased daylight harvesting but perhaps worse thermal performance. In addition, building information modeling (BIM) is becoming used more in the architecture profession and may even be of help in the early stages of the design process as a gateway for using energy software. Especially important in office buildings is the choice of a fenestration system. This final selection is dependent on many issues that are not directly related to energy concerns: aesthetics, sizing, cost, material, transmittance, and daylight performance. The appearance of fenestration system should be harmonious with building façade. Sizing of the windows is key factor affecting daylight illuminance of the interior. The cost and choices transmittance of glass materials are related to daylight availability and life cycle cost of the fenestration system. However, energy consumption is a major factor for environmental and moral reasons, building code compliance, choice of HVAC system, operations and maintenance over the lifecycle of the building, and occupant comfort. Reduction of energy consumption will also lead to the reduction of CO 2 emission to the environment. Lower energy usage helps to meet higher levels in building code. The first cost of HVAC system is decided by the amount of heating and cooling consumption. The operation and maintenance system is also regulated based on the energy consumption. The energy usage may also provide better occupant comfort. 4 In past studies of fenestration systems, many favored the research and development of new types of glass to cut energy consumption and lessen HVAC requirements. Glass research tended to focus on two environmental factors: the visible transmittance of daylight and the ability of the glass to block heat. This development produced a standard of glass performance-light to solar gain (LSG). There are insulating glass types that improve thermal performance by providing a thermal break, laminated glasses that are bonded by heat and pressure, and heat-strengthened glass that provides strength against wind and thermal load, etc. These types of glass bring more design and performance choices than ever before to fenestration systems, but while they cut down the energy costs, they can increase manufacturer, transportation, and maintenance costs. This research will focus on other factors in addition to the type of glass being used. In early design, the window size and window height are the foremost parameters because they are usually determined at the initial stage of design. Choices made at this stage can help reduce operation and maintenance cost. An effective fenestration system to balance daylight and energy demand can dramatically affect electrical lighting usage, energy use intensity, and peak load of HVAC system and daylight occupant comfort of the office space. There are many techniques for lowering the amount of energy a building uses even when just considering the fenestration: efficient windows, daylight harvesting to save on electricity for indoor lighting, window-to-wall ratio, and shading devices can lower the 5 energy consumption caused by excessive solar gain. However, solutions good for one item, for example, larger windows letting in more daylight can be detrimental to another, increased heat load. The balance of the trade-off between increased daylight harvesting and reduced energy consumption can be calculated for comfort impacts of various scenarios for windows in office buildings. Six parameters of fenestration and utility system will be studied: orientation, window-to-wall ratio, window height, window aspect ratio, glazing system, and exterior shading devices. 1.1.1. Indoor artificial lighting Electric lighting uses a large amount of electricity in office buildings. Breaking down the end use energy of commercial building by IOU (investor-owned utility), the electrical lighting uses 35% of total energy and cooling consumed 16 % (Figure 3). Some measures that have already been used to reduce this include the use of more efficient light source for application, the design of lighting systems that provide appropriate amount of light for tasks in office, the use of automatic or scheduled lighting control system to turn off or dim lights, the commissioning of all lighting system to ensure performance, and the maximum use of natural light with the daylight. Figure 3 End use energy break down (ENERGY STAR Building Manual, 2006) 6 Many studies of electric lighting focus on the installation of specific lighting application, such as electronic ballasts or compact fluorescent for saving energy. But the interaction and control of the lighting system as a whole decides the energy usage and operating cost while maintaining lighting quality and quantity. In order to design lighting systems efficiently, the quantity and quality of light and light source need to be decided based upon the office orientation and local climate. The major purpose of lighting control is to provide the appropriate amount of light, where it is needed, and when it is needed. Moreover, a lighting control strategy should be applied to minimize energy usage. The lighting control strategies are basically in three categories: active on/off (switching), and active dimming control (dimming), and the combination system of both types of equipment. Active on/off control system turns off the electric lights when there is adequate daylight at the work plane height and turn lights on when additional lighting is needed to meet illuminance levels. A lighting control schedule can be implemented to cut down excessive electric energy usage by hourly daylight simulation results. Occupancy sensors, timed switches, and energy management systems (EMSs) are typical on/off control system. Occupancy sensors are most effective for private offices and lecture halls, restrooms and warehouses, where people often move in and out. But occupant sensor may not be energy-effective to open-plan office buildings, where people stay throughout daytime. The sensors can be categorized by applications, such as ceiling mount, corner 7 mount, wall switch, narrow view and high mount. A case study of installing sensors in office in Beverly Hill indicates that the saving of electric lighting estimates 3,920 kWh/year and cooling usage reduction is 1,253 kWh/year. (ENERGY STAR Building Manual-Lighting, 2006) Active dimming control system is also known as dimming system, which adjusts electric lighting intensity by sensoring daylight levels to get adequate illuminance for the working plane. The typical dimming is accomplished by stepped dimming or continuous dimming. There are two methods of stepped dimming. One includes banks of lamps, which make levels of switches and operate one level each switch. Another uses step-dimming ballasts, which offer more control of lighting levels and reduced lighting. Continuous dimming is more flexible than stepped dimming, and the dimming ballast reduces electric light output whenever daylight is available. Energy saving dimmers can dim down to 20% of the light level. According to the results from Encelium’s six energy management strategies, office spaces can save up to 50%-75% energy by adding lighting controls. (Encelium, 2011) Different energy management strategies can be applied to various office types. The lights in many office spaces should be switched off completely when they are not occupied. Workdays begin and end at different times of day, depending on the orientations and seasons, and different tasks require different light levels. There is opportunity to adjust task lighting in each cubicle as needed by the occupant. Daylight harvesting is one of 8 those strategies that would help maximize lighting load reduction for open office and private offices with windows, however, finding an adequate amount of daylight is a critical challenge to avoid excessive solar heat gain. The typical relationship of electric utility usage and daylight availability in Southern California is shown in the graph (Figure 4). The peak electric usage hours are around noon to 4 or 5 pm. Obviously the daylight availability hours is matching peak electric usage period. If electric lights are turned off or lighting control systems are adopted during sufficient daylight period, it will save energy. This coordination of energy saving strategy is called daylight harvesting. Most of the HVAC systems are sized based on peak heating and cooling load of office building, so integrating daylight harvest strategies the HVAC system can be improved from the beginning. Figure 4 Demand for energy (Southern California Gas Company, 1996) 1.1.2. Daylight harvesting Sufficient daylighting is an energy-conserving strategy to reduce electric lighting. Daylighting is a technique source of lighting that direct, diffused, or reflected daylight to provide or supplemental lighting. Daylight improves lighting quality, occupant 9 productivity, and helps reduce energy consumption for electric lighting. An experiment involving lighting and HVAC system for commercial building was conducted by the Energy Center of Wisconsin in Ankeny, Iowa. The results showing savings of lighting, cooling, heating and fans were measured in full-scale tests for standard and high performance configurations of window, glazing, lighting systems and lighting controls in seasonal variations of Summer, Fall and Winter. The major savings are for lighting and cooling (Energy Center of Wisconsin, 2012). Studies as well as common sense show that daylight helps reduce lighting costs and cooling costs. For typical commercial, industrial or institutional buildings, daylight harvesting provides the greatest single opportunity to reduce cooling consumption and to promote occupant productivity. Generally windows are the major source of daylight in building. According to the results from RPI lighting research center (Leslie, RP, et al, 2005), estimates show that 30% to 50% of the spaces in commercial building have access to daylight through window or skylight. Many daylight technologies like active and passive daylighting from National Lighting, integrated technologies of smart sensors and intelligent building systems have been developed. Daylight penetration is one key factor of daylight harvesting, and it can be improved by adding light shelves, light pipes, controlled shades and blinds, and other active sun- tracking systems. Although there are the concerns of additional heat and glare, well- designed fenestration system can maximize the daylight harvesting while block the excessive heat and unnecessary glare. 10 1.1.3. Trade-offs With the growing studies on daylight issues, the conflicts between daylight harvesting and cooling energy demand for office buildings are important. The overall analysis on energy performance of electric lighting and cooling by defining an efficient fenestration system has been widely accepted as an importance energy-saving strategy. Annual energy consumption and peak hour loads are two primary factors in reducing energy demand of an office building. Reduction in annual energy and increase of daylight availability is one concern, and another concern is reduction of electrical lighting demand and cooling demand when providing adequate daylight. Excessive daylight brings more solar gain when additional air-conditioning is needed. In the study of fenestration systems, there are several parameters, such as the type of window and its optical properties, size, aspect ratio, placement and orientations, affect the performance of daylight. Depending on the location of the building, window orientations affect the performance of daylight and energy consumption differently. Generally, windows facing south, east, and west capture more solar energy than north-facing windows; thus these windows would cause an increment of cooling energy consumption in hot climate zones. On the other hand, the harvested daylight can help reduce electrical lighting use. 11 Window size, also expressed as window- to-wall ratio (WWR), is the most direct parameter that affects both daylight performance and energy demand, especially for office buildings. The window size determines the daylight levels of the office interior. When increasing window-to-wall ratio, daylight availability ratio and thermal energy loads are both increased for all orientations, which means the electric lighting energy decreases and cooling for lighting increases. Specifying an ideal WWR for an office space in which there is a balance between daylight performance and electric lighting load would lead to a minimal cooling load for electric lighting. Window height is a parameter that affects lighting use and lighting distribution. A window placed higher on a wall is likely to provide more evenly distributed daylight than a lower window. The figure below shows that a small area window in the middle of walls provides a limited portion of concentrated daylight near the window. It is likely to cause visual discomfort and more lighting consumption of inner space. (Figure 5) Figure 5 DFcalc daylight calculation results-window on the top and window in the mid-height 12 Window perimeter, also known as window aspect ratio, is also a key factor that would affect daylight availability and heating and cooling usage. With the same window-to-wall ratio, a long and narrow shape is preferable to a square one, because the former ones provide more distributed daylight. According to the study of Le Corbusier’s “Architecture 5 points” (Corbusier Le ed, 1986), rooms are daylit more copiously with horizontal windows (rectangular openings in the façade). His experiments also indicate that a room with horizontal windows has much stronger illumination than the room with vertical windows of the same window area. Figure 6 DFcalc daylight calculation results-rectangular window and square window 13 Figure 7 Villa Savoya, horizontal windows VS vertical windows (Wikipedia database, 2008) Selecting the correct types of window glazing is considered essential to improve glare, discomfort, and control solar heat gain. After choosing window sizes, placements and window shapes, glazing gives another opportunity to maximize daylight efficiency and minimize energy use. According to the suggestions- “Tips for daylighting with windows” (Jennifer O'Connor, Eleanor Lee, Francis Rubinstein, Stephen Selkowitz, 1997), basically, three glazing properties are critical in the selection of glazing for the evaluation of energy tradeoffs. These are window U-factor, visible transmittance and Solar Heat Gain Coefficient (SHGC). U-factor measures the ability that windows help prevent heat from escaping buildings. It is important for heating-dominated climates. U-factor (or U- value) ranges from 0.1 to 1.20, and generally the lower the U-factor, the better a window is at keeping heat in. Visible transmittance (VT) measures the amount of daylight comes through a window. Higher visible transmittance provides sufficient daylight but it would potential cause glare problems. SHGC measures how well a window in blocking solar gain. Lower SHGC indicates a lower heat transfer from solar radiation. It is a key 14 property in choosing glazing for cooling-dominated seasons. One glazing property that is not mentioned in the glazing selection tips is the ratio of Lighting to Solar Gain (LSG), which is the ratio of VT to SHGC. The higher LSG is, the better glazing is hot climates. Table 1 Basics of glazing properties U-Factor VT SHGC LSG Range 0.2-1.2 0-1.0 0-1.0 >0 Measurement The lower the U-factor, the better it is at keeping heat in. The higher the VT, the higher the potential for daylighting. The lower the SHGC, the better it is at blocking unwanted heat gain. When LSG is larger than 1.0, it transmit more light and heat Direct sunlight tends to cause visible discomfort, lower working efficiency, and brings in unwanted solar gain. So shading devices are necessary for south-facing windows in most office buildings. As it is stated in LBNL “Tips for daylighting with windows” (Jennifer O'Connor, Eleanor Lee, Francis Rubinstein, Stephen Selkowitz, 1997), there are various choices and innovations of shading devices. Suggestions of shades are orientation- dependent. To minimize air-conditioning loads, typically, it is more efficient to choose exterior shades instead of interior blinds. Generally, the tips suggest using horizontal exterior shades for south windows, using vertical fins on east and west windows and at least shading south and west windows to cut majority of sunlight and solar gain if short of budgets (O'Connor J. et al., 1997). However, when daylight is blocked by shades, more 15 artificial lighting would be wanted in office building. This study is trying to find good window configurations in balancing lighting use and AC load for different orientation and climate zones. Table 2 A selection of existing papers on the topic of trade-off between daylight harvesting and energy demand Date Author Publisher Summary DIVA 2.0: INTEGRATING DAYLIGHT AND THERMAL SIMULATIONS USING RHINOCEROS 3D, DAYSIM AND ENERGYPLUS 2011 J. Alstan Jakubiec and Christoph F. Reinhart, Building Simulatio n 2011 in Sydney, Australia An example of using DIVA to analyze trade-off between daylight and energy usage (using Radiance/daysim with EnergyPlus within DIVA a plugin for Rhino) The results are annual occupied hours blinds are closed, Weekly lighting use intensity, annual lighting/cooling/heating energy use. DAYLIGHT METRICS AND ENERGY SAVINGS Receive d 14 March 2009; Revised 23 April 2009; Accepte d 7 May 2009 J Mardaljev ic PhDa, L Heschong M Arch and E Lee MAc Lighting Research and Technolo gy 2009 The paper discussed daylight metrics and criteria: daylight factor and sustainability and climate- based daylight modeling. Two main methods are cumulative (predicting measure of daylight, such as total annual luminance, by the effect of hourly sky and sun conditions derived from climate dataset) and time-series CURRENT STATE-OF-THE ART OF INTEGRATED THERMAL AND LIGHTING SIMULATION AND FUTURE ISSUES 1999 Milan Janak and Iain Macdonal d Sixth Internatio nal IPBSA The paper describes a simulation based method for integrated performance appraisal of buildings an incorporating daylight utilization technology. Set climate parameters sky model in radiance zone parameters window model. 16 Table 2 Continued Date Author Publisher Summary AN ANALYSIS OF DAYLIGHT ING AND SOLAR HEAT FOR COOLING- DOMINATE D OFFICE BUILDINGS Received 15 Decembe r 1997; revised version accepted 26 October 1998 JOSEPH C. LAM† and DANNY H. W. LI Building Energy Research Group, Hong Kong Solar Energy Vol. 65, No. 4, pp. 251– 262, 1999 “Computer simulation techniques are used to correlate the peak electricity demand and annual incremental electricity use with two fenestration variables: solar aperture and the daylighting aperture. The baseline simulation results indicate that artificial lighting consumes the most peak cooling load, and window solar energy is the second. Optimizations are suggested to use different glass types for different orientations. THE IMPACT OF FENESTRA TION ON ENERGY USE AND PEAK LOADS IN DAYLIHTE D COMMERC IAL BUILDINGS Jun-83 S. Selkowit z, R. Johnson, R.Sulliva n, and S.Choi PASSIVE 83, the National Passive Solar Conference, Florieta NM, September 7- 9, 1983 The paper focuses on the study of the tradeoffs involved in using fenestration to daylight perimeter zones. The parameters include climate, orientation, window area, u- value, shading coefficient, visible transmittance, lighting power density, and lighting control strategy. The result indicates that daylighting's contribution to cooling load is approximately equal to electric lighting's, which means daylight strategies doesn't produce lower cooling load than electric lighting. 1.2. CURRENT ENERGY AND DAYLIGHT SIMULATION TOOLS Several simulation tools were tested before the study. Many daylight analysis software programs provide hourly daylight distribution and annual daylight availability ratio. They also provide space heating, cooling and electric lighting usage data. But for the purpose of this study, one software program must be able to calculate both daylight performance and energy usage of electric lighting and cooling on a monthly basis. 17 Table 3 Summary of software regarding lighting and energy consumptions Name of Softwar e Compan y Features Lighting Energy (Annual, Peak demand) Daysim GSD Annual daylight simulations, electric lighting energy use, lighting controls, linked to a series of CAD environments Control of lighting and blinds in offices, automated and manual lighting controls, based on Radiance. Schedules can be directly coupled with popular thermal simulation programs Energy Plus EERE Whole building energy simulation Advance fenestration calculation (blinds, glazing, solar energy, library of commercial windows; Daylghting controls of interior illuminance calculations, glare simulation and control, luminaire controls Sub-hourly, user- definable time steps for interaction between the theal zones and the environment; DIVA GSD Daysim, EnergyPlus, Rhino Input: CSV file, lighting control system; Output: internal heat gains, cooling energy use and heating energy use. Daysim daylighting schedule inputs into EnergyPlus Single-zone analysis. Simple calculation. If complicated energy model, using Open studio or Design Builder. EQUES T James J. Hirsch & Associat es Detailed comparative analysis of building designs; schematic and design development creation wizard; energy efficiency measure wizard Daylight zoning Annual/Monthly energy consumption by end use; Annual/ Monthly peak demand by end use Desktop Radianc e LBNL Most accurate Lighting simulation and rendering directly from AutoCAD. Architectural lighting and daylighting. Dynamic radiance method; BSDF (Lisa Heschong, Mudit), Thesis of validation of dynamic radiance-based daylight simulation for a test office 18 Table 3 Continued Name of Softwar e Com pany Features Lighting Energy (Annual, Peak demand) Design Builder Building models (realistic 3-d elements); can import 3d CAD models from ArchiCAD, microstation, Revit and other gbXML files. HVAC& lighting; control the design level; EnergyPlus thermal engine Optimal use of natural light; modelling lighting control systems; calculating savings in electric lighting Energy consumption broken down by fuel and end-use; internal temperatures, heating and cooling loads; co2 generation COMF EN LBN L Evaluation of fenestration systems for project- specific commercial building applications; Simulate energy consumption, peak energy demand and thermal visual comfort. Average houly daylight; Date and time daylight distribution (Window6) Energy Use intensity (Heating, cooling, fans, and lighting); Peak energy use (Gas and electricity); HVAC( packaged single zone, cannot change in COMFEN3.1); no specific date for scenarios Vasari Auto desk Performance-based design via integrated energy modeling and analysis feature. Anylasis for energy and carbon, wind tunnel analysis IES- VE-pro IES -RadianceIES Detailed 3D visualisation of daylight and electric light levels; Maximize daylight, minimize glare and levels for dimming controls; Apply dimming profiles to lighting gains in -ApacheSim Advanced dynamic thermal simulation at sub-hourly time steps for better computation of building components, Assess solar gain on surfaces, surface temperatures and radiant exchanges, The chart provides several choices for daylight and energy simulation study. Considering lighting and energy features, parameters in this study, efficiency and cost, three tools 19 were chosen for a preliminary study. These are DIVA, EQUEST and COMFEN, all of which can be used for the calculation of energy load on a monthly basis by defining daylight control system of simple energy models. 1.3. RESEARCH OBJECTIVE There are three objectives of this thesis: • To develop a general simulation methodology for analyzing energy consumption of cooling and lighting for office building during early design stages. This method is intended for energy load reduction of different fenestration systems. • To provide early design guidelines for selection of a fenestration system (window-to-wall ratio, window height, glazing, window aspect ratio and exterior shading) for office buildings in California climate zones. The results of the study can reduce energy demand for cooling and electric lighting; • To reduce the unnecessary complexity of parameters of fenestration systems and thus reduce computation by considering the relationships and importance of detailed parameters for simulation in the early design stages. 1.4. CONCLUSION The balance of the trade-off between increased daylight harvesting and reduced energy consumption can be calculated for impacts of various scenarios for windows in office buildings. Six parameters of fenestration and utility system will be studied: orientation, 20 window-to-wall ratio, window height, window aspect ratio, glazing and exterior shading. Cooling load and lighting load are qualified and analyzed by the computer simulation tools (EQUEST, DIVA for Grasshopper and COMFEN are compared, DIVA for Grasshopper and EQUEST were used in this study). Future work includes adding guidance to help architects study these trade-offs in the early stages of design using EQUEST, integrating BIM software with fenestration simulation tools and glazing and shading devices study of trade-offs for later design stages. 21 Chapter 2: Research 2.1. BUILDING CODES 2.1.1 Title 24 Table 4 Summary of Title 24-2008 Title 24-2008 Overview The California Energy Commission (CEC) created a policy that standardizes environmentally sound building practices. Entitled 2008 Building and Energy Efficiency Standards/Regulations for Residential and Nonresidential Buildings (Title 24), the revised code requires mandatory lighting controls for all newly constructed or altered buildings. Reference http://www.energy.ca.gov/title24/ Daylight “Lighting power will be reduced in areas where the daylight can help illuminate the space. Daylit areas in enclosed spaces greater than 250 ft2 must have a light control that controls at least 50% of the power in the daylit areas separately from other lighting in the space 1.Controls luminaires in vertically daylit areas separately from horizontally daylit areas 2.Maintains a reasonable uniform level of illuminance in the space 3.Daylit areas in enclosed spaces under skylights that are larger than 2,500 ft2 must use a multi-level daylighting control or astronomical timeclock device with override capability.” Lighting Control “1. Section 119-Mandatory requirements for lighting control devices, ballasts and luminaires: Multi-level lighting controls will be used for any enclosed space 100 ft2 or larger that has a connected lighting load greater than 0.8 W/ft2, and that has more than one luminaire. The multi-level lighting controls must have one control step that is between 50% and 70% of design lighting power and at least one step of minimum output operating at less than 35% of full rated lighting system power (this could be completely off). 2. Automatic daylight control devices: Have a setpoint control that easily distinguishes settings to within 10 percent of full scale adjustment; and have a light sensor that has a linear response with 5percent accuracy over the range of illuminance measured by the light sensor; 3.Dimmers. Dimmers used to control lighting shall be capable of reducing power consumption by a minimum of 65 percent when the dimmer is at its lowest light level;” 22 Table 4 Continued Title 24-2008 Building Envelope and Energy Saving “1.Section 140-Choice of performance and prescriptive approaches: The envelope and the space-conditioning, lighting, and service water-heating systems of all nonresidential, high-rise residential, and hotel/motel buildings subject to Title 24, Part 6, shall be designed, constructed, and installed in accordance with either: (a) Performance Approach-to use no more TDV (time dependent valuation) energy from depletable sources than the energy budget, calculated according to Section 141; or (b) Prescriptive Approach-in accordance with all the applicable requirements of Sections 142 through 148. 2. Prescriptive envelope criteria for nonresidential buildings are listed in Table143-A in Title 24 Title 24 (California Energy Commission, 2008) is a building and energy efficiency standard for residential and nonresidential buildings in California. It provides daylight regulation according to daylit area and lighting power reduction, and mandatory lighting controls are required for all buildings. Performance and prescriptive approaches are described in Section140. The basic criteria of windows for nonresidential buildings are shown in the table. The mandates of Title 24 are required. Specific issues that affect this study are the mandatory requirements of maximum window-to-wall ratio and glazing parameters. This study will determine if some of these numbers are better for energy reduction. Table 5 Window requirement of Title 24, source: Title 24 Nonresidential and residential fenestration stakeholder meeting June 9, 2011 2.1.2 ASHRAE 90.1-2007 23 Table 6 Summary of ASHRAE 90.1-2007 ASHRAE/IESNA Standard-2007 Overview The American Society of Heating, Refrigerating, and Air Conditioning Engineers Inc. (ASHRAE) and the Illuminating Engineering Society of North America (IESNA) jointly sponsor the ASHRAE/ IESNA Standard 90.1-2007, “Energy Standard for Buildings Except Low-Rise Residential Buildings," Reference http://www.ashrae.org/publications/page/2728 Daylight “Proposed Requirements for 2010 Specific daylit areas must be separately controlled by at least 1 multi-level photo control (including continuous dimming devices) that have the following characteristics: 1.Light sensors for the photo control will be remote from where calibration adjustments are made 2.Calibration adjustments will be readily accessible 3.The multi-level photo control will reduce electric lighting in response to available daylight with at least one control step that is between 50 – 70% of design lighting power and another control step that is no greater than 35% of design power” Lighting Control “1.Current Requirements For the following spaces*, the control device must be an occupancy sensor, unless the area already has a multi-level lighting control: 1) Classrooms (not including shop classrooms, laboratory classrooms, and preschool through 12th grade classrooms) 2) Conference / meeting rooms 3) Employee lunch and break rooms *Connection to other automatic shut-off controls is not required for these spaces. For all other spaces, the control device can be a manual control or occupancy sensor. The control device can operate a maximum of 2,500 ft2 for a space 10,000 ft2 or less, and a maximum of 10,000 ft2 for a space greater than 10,000 ft2. The control must be capable of overriding any scheduled shut-off for no more than 4 hours. Some specialty lighting within the space, such as display / accent lighting and lighting required for plant growth (non-visual lighting), requires a separate control device. 2. Automatic Shut-off Applies to buildings larger than 5,000 ft2. The device can be: 1) Time clock control device (an independent program schedule will be provided for areas no more than 25,000 ft2 but not more than 1 floor) 2) Occupancy sensor that turns off lighting within 30 minutes of an occupant leaving a space 3) A signal from another control or alarm system that indicates when an area is unoccupied 3. Lighting power density of office is 1.0w/ft2 by using the building area method; If using space-to-space method, office LPD is 1.1w/ft2.” 24 Table 6 Continued ASHRAE/IESNA Standard-2007 Building Envelope and Energy Saving “1.Building Envelope: 5.5, Prescriptive Building Envelope Option, provided that 1) the vertical fenestration area does not exceed 40% of the gross wall area for each space-conditioning category and 2) the skylight fenestration area does not exceed 5% of the gross roof area for each space-conditioning category, 3) fenestration U-factor and SHGC shall not be greater than the specified in Tables5.5-1 through 5.5-8 for different climate zones. 2. Building Envelope Trade-off Option: 5.6.1 The building envelope complies with the standard if the proposed building satisfies the provisions of Section 5.1,5.4,5.7 and 5.8 and the envelope performance factor of the proposed building is less than or equal to the envelop performance factor of the budget building” Optional incentives “The ASHRAE/ IESNA Standard contains optional lighting incentives that can be satisfied by the following: Multi-level occupancy sensor (5% increase in Lighting Power Density [LPD]) Manual dimming or programmable multi-scene dimming (5 –10% increase in LPD) Automatic daylighting controls where not required (10 – 20% increase in LPD depending on effective aperture and LPD requirement)” ASHRAE provides a baseline of design strategies. Most of the parameters for this study, such as glazing parameters, lighting power density, equipment load and illuminance level are chosen according to ASHRAE’s recommendations. The table shows modeling assumptions for internal loads and illuminance level. Table 7 ASHRAE 90.1-2007 baseline for modeling HVAC (baseline) Cooling: EER=9.5 Heating: AFUE=0.78 Set point Temperature: 70-75 F Lighting Power Density 1.0 w/ft2 Equipment Load 0.75 w/ft2 Continuous dimming illuminance level 50 fc 2.1.3 LEED NC 2009 25 Table 8 Summary of LEED NC 2009-lighting and energy LEED NC 2009 Overview “Leadership in Energy and Environmental Design (LEED) is a rating system the United States Green Building Council (USGBC) administers to provide a national standard for what constitutes a green building. LEED offers scientific performance criteria and a point system for LEED project certification. Many businesses have programs to ensure all their facilities are LEED compliant, through new construction and renovation programs.” Reference http://www.usgbc.org/DisplayPage.aspx?CMSPageID=220 Daylight “Daylight & Views Credit 8.1 & 8.2: Daylight and Views (1 point each) Intent: • Introduce daylight and views into occupied areas to provide a connection to the outdoors Requirements: • 75% of occupied spaces daylight illuminated with a minimum of 25 foot- candles • Direct line-of-site to the outdoors for 90% of regularly occupied spaces • Provide glare control” Lighting Control “Indoor Environmental Quality: Controllability of System; Credit 6.1: Controllability of Systems, Lighting (1 point) Intent: • Provide lighting system control by individual occupants or groups to promote productivity, comfort and well-being Requirements: • Individual controls for 90% of occupants • Lighting controls in shared, multi-occupant spaces • Enable lighting adjustment to meet needs and preferences” 26 Table 8 Continued LEED NC 2009 Building Envelope “Energy & Atmosphere: Prereq 1 and Credit 3: Commissioning (2 points) Intent: • Verify that building operates as intended (Prereq 1) • Begin commissioning early and execute additional activities (Credit 3) Requirements: • Develop and implement commissioning plan (Prereq 1) • Develop a systems manual (Credit 3) • Verify that the training requirements for operating personnel are in place (Credit 3) • Review building performance within 10 months of substantial completion (Credit 3) Credit 5: Measurement and verification (3 points) Intent: • Provide ongoing accountability and optimization of energy consumption over time Requirements: • Measure and track actual energy performance • Provide corrective action if desired savings are not achieved” Energy saving “Energy Performance; Prereq 2: Minimum Energy Performance Intent: • Establish minimum level of energy efficiency Requirement: • Comply with mandatory lighting control requirements in section 9.4 of ASHRAE 90.1 2007. (Automatic lighting shut-off; Space control) • Demonstrate a 10% minimum energy reduction compared to an ASHRAE 90.1-2007 (or CA Title 24 2005) compliant building. Credit 1: Optimize Energy Performance (1 to 19 points) Intent: • Further reduce energy use below the ASHRAE 90.1 baseline Requirements: • Option 1 - Whole Building Energy Simulation (1-19 points) • Option 2 – Prescriptive path -ASHRAE Advanced Energy Design Guides (1 point) • Option 3 – Prescriptive path -Advanced Buildings Core Performance Guide (1-3 points) • Whole Building Energy Simulation - demonstrate energy performance better than ASHRAE 90.1 • One point for every 2% reduction in energy cost (see graph)” 27 Table 8 Continued LEED NC 2009 Optional incentives “1. Sustainable Site: Light Pollution Reduction Credit 8: Light Pollution Reduction (1 point) Sustainable Sites Intent: • Minimize light trespass Requirements: • Interior lighting—No light shining out windows OR all non-emergency interior lighting power reduced by at least 50% during non-business hours • Exterior lighting—Must comply with ASHRAE 90.1 2007 Lighting Power Densities and lighting zone requirements in IESNA RP 33. 2. Materials & Resources: Recycled Content Credit 4: Recycled Content (1-2 points) Intent: • Increase demand for building products that incorporate recycled materials. Requirements: • Use materials such that the sum of the recycled content constitutes at least 10% or 20%, based on cost, of the total value of the materials cost in the project. 3. Innovation in Design 4. Regional Priority” Unlike Title 24 and ASHRAE 90.1 2007, LEED is not a mandatory code; however, some LEED credits are based on Title 24, ASHRAE, and other green building regulations. The results of this analysis, for instance, would illustrate choices of fenestration systems for energy conservation credits, daylight and views credits, and lighting control credits. A summary of potentially achievable credits for LEED-NC is included in Chapter 5. 2.2. PRELIMINARY ANALYSIS The preliminary analysis starts with a simple office with one south-facing window in Climate Zone 6 (Los Angeles). The purpose is to find out an optimum window-to-wall ratio for the reduction of cooling and lighting electrical usage. Three simulation tools are 28 used and compared: COMFEN, EQUEST and DIVA for Grasshopper (Viper component). 2.2.1 COMFEN 4.0 COMFEN is a free tool designed by LBNL for systematic evaluation of commercial fenestration systems. It is based on EnergyPlus, a complete analysis engine for simulations of key variables of energy consumption, peak demand, visual and thermal comfort. The results are shown to users in a simplified graphs and charts for comparative fenestration designs. It is easy to define fenestration parameters in COMFEN. One can select scenarios for comparative analysis, and the graphical results can be displayed in different formats. COMFEN is an easy-to-start software for fenestration case design. The limitation is that the HVAC default system, packaged single zone, cannot be changed. Only four scenarios can be compared at one time, and internal load and schedules are not user customizable. The advantage of COMFEN is there are many choices in the window, glazing, shading and wall libraries, and they are editable by users. • Setting Table 9 Basic settings for office model in COMFEN Office: 6.1*4.57*3.05m=27.88m2=20'*15'*10'=300f2 Lighting load =1.0w/f2=10.76w/m2 (ASHRAE90.1-2007 LPD standard) Equipment load=8.07w/m2=0.8w/f 2 People=1(0.033peo ple/f2) Lighting control: dimming to 10% Light level: 500lux HVAC=Packaged single zone Exterior wall& Roof: Wall R=19 Schedule: 9am-5pm weekdays 29 Figure 8 Basic settings in COMFEN Figure 9 Summary of annual energy use for WWR 0%, 10%, 20% and 30% 30 Figure 10 Simulation results of all scenarios, including heating, cooling, lighting, fans and peak demand • Results Table 10-Results from COMFEN-cooling, lighting and total energy cooling lighting total 0% 0.57 3.13 3.70 10% 0.82 1.56 2.38 20% 1.42 1.12 2.54 30% 1.93 1.05 2.98 cooling lighting total 40% 1.97 1.02 2.99 31 • Chart Figure 11 Annual energy consumption results-COMFEN-South window • Conclusion The simulation results of COMFEN indicate that the lowest lighting and cooling energy consumption is between 0% to 10% window-to-wall ratios. As window area becomes larger than 10%, the lighting usage increases, the cooling usage reduces and the total usage of cooling and lighting increases, but there is not much difference between 30% and 40% window-to-wall ratio. 2.2.2 EQUEST 3.64 EQUEST is a free, comprehensive, professional simulation program. The study is conducted using EQUEST version 3.64 with the DOE-2.2 simulation engine. DOE-2.2 provides accurate simulation results of whole building systems such as envelope mass, interior mass, fenestration, shading, HVAC, and lighting. Two wizards, schematic and design development creation, exist for different purposes of studies. The detailed interface has the capability to perform parametric runs and compare up to 13 different 0.57 0.82 1.42 1.93 1.97 3.13 1.56 1.12 1.05 1.02 3.70 2.38 2.54 2.98 2.99 0.00 1.00 2.00 3.00 4.00 0% 10% 20% 30% 40% Annual Energy Consumption(kwh/sf) Window-to-wall Ratio Annual Energy Consumption-COMFEN-South(kwh/sf) cooling lighting total 32 scenarios at one time. The modeling capability is limited, but it is an accurate simulation tool for comparative study. • Settings Table 11 Basic settings of office model in EQUEST Office: 6.1*4.57*3.05m=27.88m 2 =20'*15'*10'=300f 2 Lighting load =1.0w/f 2 =10.76w/m 2 (ASHRAE90.1-2007 LPD standard) Equipment load=8.07w/m 2 =0.8w/f 2 People=1/100sf Lighting control: dimming to 10% Light level: 500lux HVAC=Packaged single zone DX with furnace Exterior wall U=0.089, Roof U=0.008 Schedult:9am-5pm weekdays Efficiency: EER=9.5, AFUE=0.78 Figure 12 3D geometry of office Figure 13 Parametric runs in detail wizard for WWR 0%, 10%, 20%, 30%, 40%, 50%, 60% and 80% • Results of parametric runs 33 Table 12 Results of parametric runs in EQUEST • Chart Figure 14 Annual energy consumption results-EQUEST-South window • Conclusion The EQUEST results show the bigger the window is, the more energy of cooling and lighting is consumed. The lighting usage doesn’t change much from 10% to 40% window-to-wall ratio. The results shown for COMFEN and EQUEST are meant to introduce the program and evaluate their capability for this study. 1.09 1.65 2.33 2.98 3.59 2.51 2.11 2.10 2.09 2.09 3.60 3.76 4.43 5.07 5.68 0.00 1.00 2.00 3.00 4.00 5.00 6.00 0% 10% 20% 30% 40% Annual Energy Consumption (kwh/sf) Window-to-wall Ratio Annual Energy Consumption-eQUEST-South(kwh/sf) cooling lighting total Annual Energy Use and Demand Lighting HVAC Electric Electric kWh kWh 1 0+Run window0% 752 328 0 Base Design 10% 633 496 2 0+Run 20% 629 700 3 0+Run 30% 628 894 4 0+Run 40% 628 1,077 34 2.2.3 DIVA for Grasshopper (Viper Component) DIVA for Grasshopper is a relatively new simulation program by GSD-Squared (Graduate School of Design-Sustainable Design, Harvard University), an extension program for DIVA-for-Rhino with addition of the generative modeling program Grasshopper. There are two components-DIVA (for daylight performance analysis) and Viper (for energy consumption analysis). DIVA for Grasshopper is uses the EnergyPlus engine. It is more open to users in modeling and input variables than COMFEN and EQUEST. The limitation is some of the parameters, like lighting control system, occupancy schedule, and HVAC systems are not shown in the Grasshopper interface, but users can make change in them through the EnergyPlus basic settings. 35 Figure 15 3D geometry in Rhino and Grasshopper definition The Viper component is defined in Grasshopper. It runs thermal analysis based on EnergyPlus simulation engine. Locations of climate files and metrics of monthly and annual electric cooling and lighting use and heating use can be chosen for different simulation purposes. Conditions of scenarios including people per square foot, lighting load, equipment load, lighting control set point, zone geometry, window assembly and shading devices are inputs of the Viper component. There is a construction component, window unit component and fixed shade components. Construction component is to define construction assembly using default or custom layered material choices. Window 36 unit component provides a list of default options and two custom options, one of which is customized by material layers and another is defined by glazing properties of U-value, SHGC an VT. Fixed shade component consists of shade geometry, solar reflectance and visible reflectance. All of these components are defined in this study for different parameters included in this study. Figure 16 Viper component definitions Figure 17 Construction Assembly-default options and custom options 37 Figure 18 Window unit component-default and custom option of glass layers Figure 19 Window unit component-custom options of glazing properties, and fixed shade component 38 Figure 20 Excel exporter-export cooling and lighting use to Excel • Setting Table 13 Basic settings in DIVA for Grasshopper Office: 6.1*4.57*3.05m=27.88m 2 =20’*15’*10'=300f 2 Lighting load =1.0w/f 2 =10.76w/m 2 (ASHRAE90.1-2007 LPD standard) Equipment load=8.07w/m 2 =0.8w/f 2 People=1(0.039people/f 2 ) Lighting control: dimming to 10% Light level: 500lux HVAC-single packaged Exterior wall& Roof: Adiabatic Table 14 Monthly energy consumption from DIVA for Grasshopper Month 1 2 3 4 5 6 7 8 9 10 11 12 Tota l 0.10 % Coolin g 1.9 1.1 2.5 3.4 1.7 5.7 20. 2 22. 7 23. 0 8.6 2.8 0.7 94.4 Lighti ng 78. 7 71. 5 84. 8 76. 2 81. 8 81. 4 76. 6 84. 8 76. 2 78. 7 77. 4 76. 6 944. 7 10% Coolin g 5.0 3.9 5.2 6.6 4.7 12. 7 28. 1 34. 4 35. 6 22. 7 12. 6 4.4 175. 9 Lighti ng 71. 9 64. 9 76. 7 70. 5 77. 2 77. 3 72. 4 78. 5 69. 5 70. 8 69. 5 69. 3 868. 5 20% Coolin g 10. 2 7.9 9.2 11. 9 10. 9 18. 9 35. 6 45. 7 47. 7 34. 8 23. 9 12. 6 269. 4 39 Lighti ng 65. 8 58. 8 69. 3 65. 3 73. 0 73. 4 68. 5 72. 6 63. 2 63. 5 62. 4 62. 7 798. 4 30% Coolin g 15. 3 13. 0 15. 6 17. 4 15. 8 24. 0 43. 3 56. 4 59. 8 46. 2 34. 1 20. 7 361. 6 Lighti ng 60. 0 53. 2 62. 4 60. 3 69. 0 69. 8 64. 8 67. 2 57. 4 56. 7 55. 7 56. 5 733. 0 40% Coolin g 21. 5 18. 8 23. 4 23. 1 20. 6 29. 2 51. 2 66. 8 71. 3 57. 0 43. 9 28. 7 455. 4 Lighti ng 54. 7 47. 9 55. 9 55. 6 65. 1 66. 3 61. 3 62. 0 51. 9 50. 4 49. 4 50. 7 671. 3 •Bar chart Figure 21 Annual energy consumption results-DIVA-South window •Conclusion There is not much difference in the total energy demand of cooling and lighting for various window sizes. The tendency shows that a larger window consumes more energy than a smaller window. It is possible that the lowest energy usage is between 0% and 10%. The cooling usage differs a lot from the results of EQUEST, but it is similar to the results of COMFEN. It turned out the results are incorrect, because of the bug of DIVA for grasshopper 1.9, which misplaced lighting control point in Rhino with units of feet. 0.31 0.59 0.90 1.21 1.52 3.15 2.90 2.66 2.44 2.24 3.46 3.48 3.56 3.65 3.76 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Annual Energy Consumption (kwh/sf) Window-to-wall Ratio Annual Energy Consumption-DIVA-South(kwh/sf) cooling lighting total 40 After changing units from feet to meters, cooling usage stays the same, but lighting usage changes totally, and the total usage coincides with the total results of EQUEST. 2.2.4 Conclusion COMFEN is not an ideal simulation software for this study, because it is limited to a four-scenario comparison as a time. DIVA for grasshopper and EQUEST will be used for detailed simulations. 41 Chapter 3: Methodology 3.1 INTRODUCTION The purpose of the study is to investigate minimum energy cooling and lighting use by optimizing fenestration systems and geometry conditions for typical office buildings in California. It discusses several critical parameters and finds out their impact of energy load. This chapter compromises three parts. First, the general design parameters of a typical office model are considered. These are building geometry, dimensions, schedules of occupancy and equipment, power densities and daylight control system. Second, the specific simulation parameters, such as the parameters of illuminance level and room depth, parameters of fenestration systems including window-to-tall ratio (WWR), window height, window aspect ratio, glazing parameters and exterior overhangs are presented. 42 3.2 MODEL DESCRIPTION 3.2.1 Geometry Figure 22 Model of the office and parameters of this study 3.2.2 Main Parameters The main parameters set in the simulation program of EQUEST and DIVA for Grasshopper are coordinated with each other as much as possible. For the envelope construction, the walls without opening, floor, and ceiling are set for an adiabatic condition. The walls with windows are created according to ASHRAE 90.1-2007 wall requirement in each climate zone in California. The HVAC (heating, ventilation and air- conditioning is a packaged single zone DX with furnace. Operation and occupancy schedules are set according to ASHRAE 90.1-2007 and the default setting in EQUEST and DIVA. The designed heating and cooling temperature is 70F and 75F during the occupied hours. The equipment load and lighting load are set to 1.0w/sf based on the 43 ASHRAE standard value. The model assumes one person per 100 square feet. A daylight control photosensor is placed in the center of office space, and it is used to dim electrical lighting to a minimum of 10% light output (American Society of Heating, Refrigeration and Air-Conditioning Engineers, Inc., 2007) Table 15 Settings of main parameters Office: 6.1*4.57*3.05m=27.88m 2 =20'*15'*10'=300f 2 Lighting load =1.0w/f 2 =10.76w/m 2 (ASHRAE90.1-2007 LPD standard) Equipment load=8.07w/m 2 =0.8w/f 2 People=1(0.039peo ple/f 2 ) Lighting control: continuous dimming Lighting control point: 1 point in the middle Exterior wall& Roof: Adiabatic HVAC-Single packaged 3.3 ENERGY SIMULATION PARAMETERS 3.3.1 Climate Zones Energy performance of cooling and artificial lighting is influenced by the weather and the geographical location. Two typical climate zones in California, CZ06 (Los Angeles) and CZ15 (Blythe), were chosen in this study. Climate Zone 6 includes cities along the beaches of southern California. The temperature is relatively mild throughout summer and winter. The city of Los Angeles is the largest city in this climate zone, and it benefits from solar heating due to plentiful sunshine throughout the year. Besides the benefits of solar energy, over-illumination would cause excess cooling energy load for offices, so daylight harvesting would help lessen energy load. 44 Climate Zone 15 is chosen for this study due to its characteristic of extremely hot and dry summer and moderately cold winters. Saving cooling energy and taking use of daylight harvesting would be the key factor that attributes to energy reduction in the summer. The average temperature in CZ15 is much higher than other zones in California. Skies are clear in most days of year with annual sunshine of about 85% (Pacific Gas and Electric Company, 2012). 3.3.2 Lighting Design Level Lighting design load of 1.0w/sf was used in this study. Designed illuminance level of 500lux (50 foot-candles, IESNA, 2000) and 350lux (35 foot-candles) at the workplane height (2.5ft) are compared. According to criteria from IESNA handbook (IESNA, 2000), lighting levels can be selected based on the associated lighting power density. For offices with task lighting, a 500lux lighting level with lighting power density of 1.0w/sf is recommended, and a 350lux lighting level with lighting power density of 0.8w/sf should be matched. 3.3.3 Window parameters and shading devices Several critical parameters of window and exterior shadings are compared and analyzed in this study. These are window orientation, window-to-wall ratio, window height, window-aspect-ratio, glazing, and exterior overhangs. Orientations of south, north, east and west are the most influential factors in the decision of selecting window parameters. The studies were conducted for one wall and one orientation at a time in order to keep the inputs separate. 45 Window-to-wall ratio (WWR) is the ratio of glazing area and wall area. It is a key factor not only in the study of daylight performance but also in the prediction of energy conservation. Consideration of WWR is covered the most stages of this study. According to ASHRAE and Title24, the recommended WWR and the maximum WWR should be less than 40%. However, 10%-80% of WWRs are compared. Window height is known as the position of window on the wall. As it is tested in chapter1 using DFcalc calculation tool, the daylight performance of windows in the upper portion of walls tends to increase the daylight illumination level and provide a more even distribution of daylight across the whole office space. In this study, a window in the upper portion of walls (1ft from the top of walls) and a window in the middle of wall are compared under the condition of the same window area. Window-aspect-ratio (WAR), the ratio of window width and window height, determines the window shape. A WAR of 4:1 tends to be a very rectangular horizontal window, while a WAR of 1:2 is likely a typical vertical window. A series of WAR of 4:1, 2:1, 1:1 and 1:2 is simulated for various window areas and four orientations. A component named Galapagos in Grasshopper is used to optimize (minimize) energy load of cooling and lighting for the study of window-aspect-ratios. 46 Figure 23 Diagram of WWR, window height and window w/h ratio Decisions of glazing choices are made based on their performance using different combinations of U-factor, VT, and SHGC, and it is dependent on climate zones. For the city of Los Angeles (Climate zone 6), three types of glazing systems are selected according to the baseline from ASHRAE 90.1-2007, recommendations of base and better performance glazing from James Benya (Principal of Benya Lighting Design) based on experience and climate conditions. Table 16 Glazing properties Choices and sizes of exterior shading devices depend on climate and orientation. The simulation parameters of exterior overhangs, recommended by James Benya, are to project out 60% window height and equal to window-height projection. Overhang depths U-Factor VT SHGC LSG ASHRAE baseline 0.55 0.508 0.4 1.27 Base performance 0.55 0.5 0.375 1.33 Better performance 0.55 0.63 0.26 2.4 47 are calculated based on the peak demand time of year (eg, for Los Angeles, it is Sept. 22 nd from COMFEN peak demand simulation results) using the Solar Tool from Ecotect. Beside defining the geometry of fixed shades in DIVA for Grasshopper, solar reflectance and visible reflectance of 0.5 are selected based on default settings. Figure 24 Exterior overhang-South WWR 10%-60% projection, depth of shade=0.6m Figure 25 Exterior overhang-South WWR 10%-100% projection, depth=0.75m 48 Figure 26 Exterior overhang-South WWR 20%-60% projection, depth=0.65m Figure 27 Exterior overhang-South WWR 20%-100% projection, depth=0.85m 49 Figure 28 Exterior overhang-South WWR 30%-60% projection, depth=0.75m Figure 29 Exterior overhang-South WWR 30%-100% projection, depth=1m 50 Chapter 4: Simulation Results Simulations of different parameters were conducted in stages. In each stage, the simulation results were compared and analyzed. The study of window heights and lighting levels were simulated for window-to-wall ratio 0%, 10%, 20%, 30%, 40%, 60% and 80% of four orientations. The data shown in the charts are based on energy performance under various conditions. A better performance range of WWR was selected for each orientation to continue with study of window-aspect-ratio. Then best performance scenarios of WAR were chosen for comparison of base and better glazing systems. At last, exterior shadings were added to the optimized window system for the possibility of further energy reduction. The fixed parameters for all simulations are shown in the table below. Table 17 Fixed parameters used in all simulations Office: 6.1*4.57*3.05m=27.88m 2 =20'*15'*10'=300f 2 Lighting load =1.0w/f 2 =10.76w/m 2 (ASHRAE90.1-2007 LPD standard) Equipment load=8.07w/m 2 =0.8w/f 2 People=1(0.039people/f 2 ) Lighting control: fluorescent lighting, continuous dimming, one control point in the middle Exterior wall& Roof: Adiabatic HVAC-Single packaged 4.1. WINDOW HEIGHT (PLACEMENT) Three window heights were compared in this study. These are window on top of the wall, window between top and center of the wall, and window in the center of the wall. The scenarios were simulated under the assumption of wide window (width=19ft) for WWR 0% to 80%. The data shown in the charts were annual energy consumption of cooling, 51 electric lighting and total of the two uses, and it was recorded on an illuminance level on the working surface of 500lux in the study of window heights. Figure 30 Window variations of window height and window-to-wall ratios 4.1.1. 0.1m from top of the wall • South-facing windows Figure 31 Annual Energy Consumption-window on top-500 lux-South The most energy savings obtained for city of Los Angeles are likely to be achieved from WWR 10% to 30% for the south window. This can be explained that smaller windows are more energy-efficient in hot climate zones for south orientation. It is presented that as WWR increases, cooling load increases but lighting use reduced. The data of lighting use also shows fewer lighting use reduction after window size becomes larger than 40% for the reason that when WWR exceeds 40%, daylight is sufficient for the required lighting 0.49 0.73 1.15 1.57 1.96 2.74 3.51 3.15 1.59 1.11 0.99 0.95 0.93 0.92 3.65 2.32 2.25 2.56 2.92 3.67 4.44 0.00 1.00 2.00 3.00 4.00 5.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(500lux)(kwh/sf) cooling lighting total 52 level, and larger window area would only results in more cooling consumption. If a larger window is wanted in the south façade for better view, other parameters such as window placement, window shape, better glazing system, and shading devices are recommended. • East-facing windows Figure 32 Annual Energy Consumption-window on top-500 lux-East Unlike south-facing windows, the optimum WWR for minimum energy load of cooling and lighting is in the range of 30% to 60%. Total energy load is much less than windows facing south because of less cooling load. Lighting use decreases gradually with the increment of WWR. 0.50 0.60 0.75 0.91 1.06 1.37 1.69 3.15 2.33 1.81 1.51 1.30 1.13 1.11 3.65 2.92 2.56 2.41 2.36 2.50 2.81 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(500lux)(kwh) cooling lighting total 53 • West-facing windows Figure 33 Annual Energy Consumption-window on top-500 lux-West Similar to the east orientation, the optimum WWR range for minimum energy load is also from 30% to 60% and electric lighting is consumed only a little less than east windows but with the same tendency. However, due to more cooling consumption after WWR exceeds 20%, more total load is required for west-facing windows. • North-facing windows Figure 34 Annual Energy Consumption-window on top-500 lux-North Different from previous study of south, east and west windows, as predicted, even though WWR 30% to 60% is also the best performance window sizes for the north, more 0.46 0.60 0.82 1.01 1.19 1.59 2.01 3.15 2.29 1.77 1.45 1.24 1.07 1.06 3.61 2.89 2.58 2.46 2.43 2.66 3.06 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(500lux)(kwh) cooling lighting total 0.41 0.42 0.45 0.52 0.61 0.82 1.00 3.15 2.37 1.64 1.24 1.06 0.96 0.95 3.56 2.79 2.08 1.76 1.67 1.78 1.95 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(500lux)(kwh) cooling lighting total 54 significant energy reduction of cooling and total use is shown in the chart. This can be explained that daylight harvesting helps save cooling energy for north-facing façade in cooling-dominated climate, and it might also be beneficial for heating-dominated climates. The results and optimum WWR ranges within this section are obtained for window placed 0.1m from top of the wall. Windows placed 0.7m from top of the wall and in center of the wall are simulated and compared in the following sections. 4.1.2. 0.7m from top of the wall Moving windows downward to 0.7m from top of the wall, simulations are run for windows in the south and east. • South-facing windows Figure 35 Annual Energy Consumption-window 0.7m from top-500 lux-South For WWR larger than 30%, windows 0.13m and windows 0.7m from top are similar, to avoid repetitive data, simulations for south-facing windows at the height of 0.7m from top of the wall are run for WWR 0% to 30%. The optimum WWR ranges from 0% to 0.49 0.76 1.25 1.68 3.15 1.44 1.05 0.98 3.65 2.20 2.30 2.65 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% Annual Energy Consumption WWR Annual Energy Consumption-0.7m from top(500lux)(kwh/sf) cooling lighting total 55 20% for window height 0.7m from top, which differs from the results obtained for window 0.1m from top. This leads to a conclusion that optimum WWR range changes with different window placements. Compared to data shown in previous chart of 0.1m from top, the 0.7m condition consumes less total energy at WWR 10% assumption, while it consumes more total energy at other window sizes. • East-facing windows Figure 36 Annual Energy Consumption-window 0.7m from top-500 lux-East Theoretically, the higher the window is, the deeper the daylighting zone would be, and deeper daylighting zone would help reduce artificial lighting use. However, when placing window on the east façade at the height of 0.7m from top, the optimum WWR range for minimum energy and total energy load are almost the same with placing the window at 0.1m from top. 0.50 0.60 0.75 0.91 1.06 3.15 2.33 1.82 1.51 1.30 3.65 2.93 2.56 2.41 2.36 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Anunual Energy Consumption WWR Annual Energy Consumption-0.7m from top(500lux)(kwh/sf) cooling lighting total 56 • West-facing windows Figure 37 Annual Energy Consumption-window 0.7m from top-500 lux-West The best performance WWR range for windows placing 0.1m from top of wall was 30% to 60%, and for windows 0.7m from the top of wall the tendency of energy use variations turns out to be similar. For windows larger than 40%, there is not much difference for various window placements. • North-facing windows Figure 38 Annual Energy Consumption-window 0.7m from top-500 lux-North For windows placing 0.7m from top of wall on the North, the energy use of cooling and lighting decreases for 10% and 20%. However, the optimum energy performance for 0.46 0.60 0.81 1.00 1.17 3.15 2.29 1.77 1.45 1.24 3.61 2.89 2.58 2.45 2.41 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Anunual Energy Consumption WWR Annual Energy Consumption-0.7m from top(500lux)(kwh/sf) cooling lighting total 0.41 0.42 0.45 0.55 0.66 3.15 2.22 1.48 1.16 1.03 3.56 2.64 1.93 1.71 1.69 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Anunual Energy Consumption WWR Annual Energy Consumption-0.7m from top(500lux)(kwh/sf) cooling lighting heating 57 WWR is from 30% to 60% for window 0.1m from top of wall. Moving the window from 0.1m to 0.7m from top of wall doesn’t make a change of least energy use WWR range. 4.1.3. Middle of the wall (1.5 m from top) • South-facing windows Figure 39 Annual Energy Consumption-window in the middle-500 lux-South Moving windows from 0.1m from top of the wall to 1.5m from top of the wall, both of cooling load and lighting load increased from WWR 0.1% to 80%. The result implies that he increment of cooling energy consumption could be affected by window placement, when glazing areas are the same. For windows placed in the center of the wall, similar to the condition of windows on top, total energy use tends to be less from WWR 10% to 30%. 0.49 0.79 1.25 1.68 2.09 2.89 3.65 3.15 1.70 1.13 1.01 0.98 0.94 0.92 3.65 2.49 2.38 2.69 3.07 3.84 4.58 0.00 1.00 2.00 3.00 4.00 5.00 0.10% 10.00% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window in the middle (kwh/sf) cooling lighting total 58 • East-facing windows Figure 40 Annual Energy Consumption-window in the middle-500 lux-East The annual energy consumption of cooling and lighting indicates a major increment in artificial lighting use and only a slightly higher cooling use if compared with windows placed on the upper portion of the wall. Different from the south orientation where lighting uses are almost the same with windows on top if WWR exceeds 30%, window head height at the center of the wall would cause much more lighting use for all window sizes than windows on top. However, change of lighting use would not influence the optimum WWR range. The optimum range is 30%to 60% for east-facing windows. 0.50 0.63 0.77 0.93 1.07 1.37 1.67 3.15 2.55 2.04 1.72 1.50 1.28 1.12 3.65 3.17 2.81 2.65 2.57 2.64 2.79 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window in the middle (500lux)(kwh/sf) cooling lighting total 59 • West-facing windows Figure 41 Annual Energy Consumption-window in the middle-500 lux-West For the west-facing windows, tendency of total energy use turns to be flatter for different window sizes than other conditions and orientations. Cooling uses presented equal with the uses of top window condition from WWR 0.1% to 40%. Instead of increasing cooling use for larger window area, the cooling load drops slightly for WWR 60% and 80%. Even though, as expected, lighting use is growing all the way from 10% to window 80%, the fluctuation is insufficient in influencing the optimum WWR range for less energy use. It ranges from 30% to 60%, but apparently there is not much difference of total energy consumption from WWR 20% to 60% as shown in the chart. 0.46 0.62 0.83 1.01 1.19 1.56 1.95 3.15 2.47 1.96 1.66 1.45 1.22 1.07 3.61 3.09 2.79 2.67 2.63 2.79 3.02 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window in the center (500lux)(kwh/sf) lighting cooling total 60 • North-facing windows Figure 42 Annual Energy Consumption-window in the middle-500 lux-North North-facing windows consumes much less total energy compared with the other three orientations for all window sizes. The reason is that north orientation would only receive minor direct solar penetration in the early morning and late afternoon in the summer. It saves energy, even though not as much as other orientations, when window head height is higher. The lower energy consumption and less solar radiation does not necessary mean the bigger the window is, the less the energy load would be. As it is drafted in the chart, the lowest energy consumption WWR are presented between 30% and 60%. In summary, the optimum window-to-wall ratio tends to be smaller on the south orientation, and it has a tendency to be larger on the east, west, and north orientations. For each orientation and each condition of window height, the top ones (window head height is 0.1m from the top of wall) are always the best performance scenarios for energy reduction, except for one WWR 10% scenario on south for which the 0.7m condition 0.41 0.43 0.46 0.54 0.65 0.87 1.07 3.15 2.37 1.65 1.24 1.10 0.99 0.95 3.56 2.80 2.11 1.78 1.75 1.86 2.02 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window in the center (500lux)(kwh/sf) cooling lighting total 61 saves more energy. Windows placed in the center tends to consume more cooling and lighting energy for all conditions and all WWRs than the other two case studies. 4.2. ILLUMINANCE LEVEL In the study of tradeoff between daylight harvesting and energy load, two outputs of cooling energy use and artificial lighting use were analyzed. Conditions of window systems were compared in order to have influence on energy uses. Illuminance level measured on the workplane is not only a factor affecting daylight performance of the interior; it would also affect artificial lighting use. The lower the illuminance level is, the less artificial lighting use is needed. Traditionally, the higher standard of lighting level of an open office is 500lux according to ASHRAE 90.1-2007, while a lower standard of illuminance level 350lux was compared to examine the correlation of lighting use reduction and alteration of WWR best performance range. Lower levels could be considered only if task lighting were included, adding a plug load in lieu of the lighting power density for ambient lighting. 4.2.1 500 lux vs 350 lux 62 • South-facing windows Figure 43 Annual Energy Consumption-window on top-350 lux-South Figure 44 Annual Energy Consumption-window 0.7m from top-350 lux-South A lower illuminance level of 350lux requires less artificial lighting use, and it also helps save cooling energy for WWR 10%, 20% and 30% compared to the higher illuminance level of 500lux. It can be explained that lighting fixtures generate less heat for lower standard of lighting level, thus less cooling load would be needed. For WWRs other than 10%, the conditions of top window and 350lux generate the least energy consumption for south orientation. For WWR equals 10%, the condition of 0.7m from top and 350lux is 0.49 0.69 1.14 1.56 1.96 2.74 3.51 3.15 1.30 1.01 0.95 0.92 0.90 0.90 3.65 1.99 2.15 2.51 2.88 3.65 4.41 0.00 1.00 2.00 3.00 4.00 5.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) cooling lighting total 0.49 0.73 1.24 1.67 1.96 3.15 1.19 0.98 0.94 0.92 3.65 1.92 2.22 2.61 2.88 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Annual ENergy Consumption WWR Annual Energy Consumption-0.7m from top(350lux)(kwh/sf) cooling lighting total 63 the best choice for the following study. Changing lighting level does not change the optimum range of 0%- 30% for south. • East-facing windows Figure 45 Annual Energy Consumption-window on top-350 lux-East Similarly, illuminance level of 350lux reduces much total energy load without changing the tendency of WWRs and the slight decrease of cooling load for east façade is shown from WWR 0.1% to 40% when large amount of lighting heat is generated. The best WWR altered from the range of 30%-60% to 20%-60% for the reason that WWR 30% and 40% have a tendency to consume the same amount of total energy. 0.50 0.57 0.72 0.88 1.04 1.37 1.69 3.15 2.08 1.54 1.25 1.10 1.00 1.00 3.65 2.66 2.26 2.13 2.13 2.37 2.68 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) cooling lighting total 64 • West-facing windows Figure 46 Annual Energy Consumption-window on top-350 lux-West Comparing with the 500 lux illumination level, lighting use under all WWRs decreased. Therefore, the total energy use of cooling and lighting decreased. However, the WWR range (20% - 60%) that used the least amount of energy did not change. • North-facing windows Figure 47 Annual Energy Consumption-window on top-350 lux-North After changing the illuminance level to 350 lux, the WWR range of that used the least amount of energy expanded from 30% - 60% to 20% - 60%. Most of the reduction of lighting energy occurs in the range of 20% to 40%. However, when WWR level goes 0.46 0.57 0.79 0.99 1.18 1.59 2.00 3.15 2.04 1.48 1.19 1.05 0.96 0.95 3.61 2.61 2.26 2.17 2.22 2.55 2.96 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) cooling lighting total 0.41 0.39 0.42 0.51 0.61 0.82 1.00 3.15 2.04 1.31 1.04 0.95 0.92 0.91 3.56 2.43 1.72 1.55 1.57 1.74 1.91 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) cooling lighting total 65 beyond 60%, the total amount of energy does not decrease much because there is enough daylight reaching 350lux illuminance level. In order to avoid over-illumination, windows that are over WWR 60% are not recommended for the north elevation. 4.3. WINDOW ASPECT RATIO When it comes to window aspect ratio, daylight penetration and distribution are the key issues. In the 18 th and 19 th century tall windows were commonly used for their good daylight distribution; however, during the 20 th century windows, office building windows tend to be continuous ribbon glazing with a lower head height. In this study, window aspect ratios of 4:1, 2:1, 1:1 and 1:2 are compared in consideration of cooling and lighting load for different sizes of windows and for all orientations. The simulation results presented below would be affected by several parameters, and these optimum window-aspect-ratios can only be true to certain conditions (continuous dimming to 10% and required illuminance level of 350lux and single packaged HVAC). For instance, choosing different daylight control systems or changing required illuminance level the electric lighting energy would be reduced or increased; therefore total energy would alter use and optimum window-aspect-ratio. An optimized study of window-aspect ratio using the Galapagos component for Grasshopper (See Appendix A) with Rhino is conducted for best-performed window-to wall ratios in each orientation. The requirement of optimization is the minimum energy load of cooling and lighting. The conditions of window perimeters are set to run from 66 very horizontal rectangular windows (nearly full width of the wall) to very vertical windows (nearly full height of the wall) Figure 48 Window variations for w/h ratios 4.3.1. South facing window • WWR 10% Figure 49 Annual Energy Consumption-WWR 10%-window aspect ratio-South In regards to WWR 10% windows, window aspect ratio 2:1 is the most efficient scenario in terms of total energy use of cooling and lighting. We can see clearly from that chart that cooling energy consumption is rather stable in all WAR, but when the WAR is a vertical rectangular, the cooling energy consumption increased, and there is an obvious increase of lighting use. Therefore, in all south WWR 10% windows, vertical rectangular windows are not recommended. 0.70 0.70 0.71 0.74 1.36 1.35 1.42 1.69 2.06 2.05 2.13 2.43 0.00 0.50 1.00 1.50 2.00 2.50 3.00 4 2 1 1/2 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR10%-Window Aspect Ratio (kwh/sf) cooling lighting total 67 • WWR 20% Figure 50 Annual Energy Consumption-WWR 20%-window aspect ratio-South The annual energy consumption chart for WWR 20% indicates a total energy increase for the window with 1/2 width to height ratio for south-facing windows. • WWR 30% Figure 51 Annual Energy Consumption-WWR 30%-window aspect ratio-South Different from window-aspect ratio charts of WWR 10% and 20%, which show an obvious increment in WAR ½, it is impossible to make a width to height ratio of ½ for WWR 30%. Even though the window with WAR 2/1 consumes the least cooling and lighting energy, there is not a significant difference of different window shapes when 1.13 1.13 1.13 1.14 1.06 1.04 1.05 1.15 2.19 2.17 2.18 2.29 0.00 0.50 1.00 1.50 2.00 2.50 4 2 1 1/2 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR20%-Window Aspect Ratio (kwh/sf) cooling lighting total 1.55 1.55 1.55 0.98 0.97 1.00 2.53 2.52 2.55 0.00 1.00 2.00 3.00 4 2 1 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR30%-Window Aspect Ratio (kwh/sf) cooling lighting total 68 WWR is as large as 30% percent. Compared with WWR 10% with WAR ½, it is general better to have a larger window rather than a vertical small window in term of energy use and good view. • Optimal window-aspect ratio Figure 52 Annual Energy Consumption-Optimal window aspect ratio-South For south-facing windows, the least energy consumption appears at WWR 10% with width to wall height ratio of 0.97 according to optimization from Galapagos. When WWR is as large as 20%, the optimal energy performance is shown at window-aspect ratio of 1.6; when WWR is 30%, the optimal energy use is 2.52kwh/sf with window- aspect ratio of 1.9. The optimization simulations correlate with the results of WAR 4/1, 2/1, 1/1 and ½, but different window perimeters, even the optimal window perimeter, fail to save much energy in comparison with different window placements, window-to-wall ratios, and illuminance levels. 0.69 1.13 1.55 1.34 1.03 0.97 2.03 2.16 2.52 0.00 1.00 2.00 3.00 10% 20% 30% Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-South-Optimal WAR(kwh/sf) cooling lighting total 69 4.3.2. East facing window • WWR 20% Figure 53 Annual Energy Consumption-WWR 20%-window aspect ratio-East The window-to-wall ratio of 20% to 40% was simulated for the study of window-aspect ratio for the east, which differs from south facing window (WWR10%-30%), based on the results of optimal energy performance range. The tendency of annual energy use for different window shapes are similar to that of the south facing windows, however, much more lighting load is taken utilized for the east, which makes the total energy use for the east much higher than that for the south. The cooling load, as expected, keeps nearly constant for window-aspect ratios. 0.74 0.74 0.74 0.76 1.78 1.75 1.78 1.98 2.52 2.50 2.53 2.74 0.00 1.00 2.00 3.00 4 2 1 1/2 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR20%-Window Aspect Ratio (kwh/sf) cooling lighting total 70 • WWR 30% Figure 54 Annual Energy Consumption-WWR 30%-window aspect ratio-East With windows approaching 30% of the wall area, the lighting load decreases compared to WWR 20%, and so does the total energy consumption. So it can be predicted that a WWR 20% window cannot provide enough daylight for east-facing windows. Since vertical window of width to height ratio of ½ could be simulated for WWR equals or larger than 30%, the best choice is WAR ½ and WAR 1/1 produces not much more energy than horizontal window of ratio 4/1. • WWR 40% Figure 55 Annual Energy Consumption-WWR 40%-window aspect ratio-East 0.90 0.90 0.91 1.50 1.46 1.54 2.40 2.36 2.44 0.00 1.00 2.00 3.00 4 2 1 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR30%-Window Aspect Ratio (kwh/sf) cooling lighting total 1.06 1.07 1.29 1.44 2.35 2.51 0.00 1.00 2.00 3.00 2 1 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR40%-Window Aspect Ratio (kwh/sf) cooling lighting total 71 After a window is as large as 40% of the wall area, it cannot be built that rectangular neither for horizontal nor for vertical, as a result, only window-aspect ratio of 2/1 and 1/1 are compared. The square window shows an increasing energy use in both lighting and cooling. It is not a subtle difference, so that for WWR 40% window facing east, a rectangular window of 2/1 width to height ratio is recommended, and it even has a better energy performance than all window shapes in the outputs of WWR 30%. • Optimal window-aspect ratio Figure 56 Annual Energy Consumption-Optimal window aspect ratio-East The optimal window-aspect ratio for WWR 20%, 30% and 40% windows are 1.89, 1.95 and 2.37 with total energy reduction equal to or slightly less than the energy load of best performed window perimeters discussed above. 0.74 0.90 1.06 1.75 1.46 1.29 2.49 2.36 2.34 0.00 1.00 2.00 3.00 20% 30% 40% Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-East-Optimal WAR(kwh/sf) cooling lighting total 72 4.3.3. West facing window  WWR 20% Figure 57 Annual Energy Consumption-WWR 20%-window aspect ratio-West The energy consumption of WWR 20% for west facing windows shows a similar result with east facing windows. The best-performed window-aspect ratio is 2/1 and the worst one is 1/2.  WWR 30% Figure 58 Annual Energy Consumption-WWR 30%-window aspect ratio-West For the condition of WWR 30%, the lowest energy load is also shown at window-aspect ratio 2/1; this is recommended for the west elevation. 0.81 0.81 0.81 0.83 1.73 1.70 1.73 1.92 2.54 2.51 2.54 2.76 0.00 1.00 2.00 3.00 4 2 1 1/2 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR20%-Window Aspect Ratio (kwh/sf) cooling lighting total 1.01 1.01 1.01 1.44 1.41 1.48 2.45 2.41 2.49 0.00 1.00 2.00 3.00 4 2 1 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR30%-Window Aspect Ratio (kwh/sf) cooling lighting total 73  WWR 40% Figure 59 Annual Energy Consumption-WWR 40%-window aspect ratio-West The window-aspect ratio of 2/1 for WWR 40% on the west performs much better than that of 1/1. Furthermore, the energy use of WAR 2/1 is equal to or less than the best performance scenarios of WWR 20% and 30%. A window with width to height ratio of 2/1 and WWR 40% is recommended for the west side because of lower energy use and better views. • Optimal window-aspect ratio Figure 60 Annual Energy Consumption-Optimal window aspect ratio-West 1.19 1.20 1.23 1.38 2.42 2.58 0.00 1.00 2.00 3.00 2 1 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR40%-Window Aspect Ratio (kwh/sf) cooling lighting total 0.81 1.00 1.19 1.70 1.40 1.23 2.51 2.41 2.42 0.00 1.00 2.00 3.00 20% 30% 40% Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-West-Optimal WAR(kwh/sf) cooling lighting total 74 The best-performed window-aspect ratios for WWR 20%, 30% and 40% on the west are 1.87, 1.55 and 2.37. The lowest output of energy consumption appears when window is 30% of the wall area with width to height ratio of 1.55. 4.3.4. North facing window The best performance range of WWR for north facing windows is from 20% to 40%. According to the characteristic of the north orientation, much less cooling load would be wanted but heating load would be introduced. One purpose of this study was to balance the cooling load and lighting load trade-offs, so that heating load is not included in the final result. Heating load was tested and simulated for certain scenarios and it turns out to be not much, so it would not affect much of the conclusion. • WWR 20% Figure 61 Annual Energy Consumption-WWR 20%-window aspect ratio-North When window area is 20% of the wall, the square shape of the window saves the most energy use; besides, windows with width to height of 2/1 also have a good energy performance. However, window-aspect ratio of ½ would definitely not be recommended for WWR 20% on the north side of the building. 0.43 0.42 0.41 0.43 1.45 1.35 1.35 1.65 1.88 1.77 1.76 2.08 0.00 0.50 1.00 1.50 2.00 2.50 4 2 1 1/2 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR20%-Window Aspect Ratio (kwh/sf) cooling lighting total 75 • WWR 30% Figure 62 Annual Energy Consumption-WWR 30%-window aspect ratio-North Apparently, window with width to height of 2/1 consumes the least cooling and lighting energy. It is also the best scenario for energy saving of the north façade compared to WWR 20% and 30%. • WWR 40% Figure 63 Annual Energy Consumption-WWR 40%-window aspect ratio-North The energy performance of all window-aspect ratios for WWR 30% and 40% turns out to be similar. Window-aspect ratio of 2/1 would be the best choice in terms of energy conservation. 0.51 0.51 0.50 1.18 1.10 1.20 1.69 1.61 1.71 0.00 0.50 1.00 1.50 2.00 4 2 1 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR30%-Window Aspect Ratio (kwh/sf) cooling lighting total 0.61 0.60 0.59 1.05 1.01 1.10 1.66 1.62 1.69 0.00 0.50 1.00 1.50 2.00 4 2 1 Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-WWR40%-Window Aspect Ratio (kwh/sf) cooling lighting total 76 • Optimal window-aspect ratio Figure 64 Annual Energy Consumption-Optimal window aspect ratio-North The optimized window-aspect ratios for north facing windows are 1.27, 1.86 and 2.08. 4.4. GLAZING A choice of glazing was simulated for optimal energy performance ranges and best performance window shape based on Galapagos’ optimization. These are WWR 10%- 30% for the south, WWR 20%-40% for the east, west, and north. The U-factor of glazing properties stays constant as the base performance glazing (ASHRAE-90.1 2007 baseline), while the visible transmittance of window increases from 0.5 to 0.63 and the solar heat gain coefficient decreases from 0.375 to 0.26. As a result, the light to solar gain ratio (LSG) goes up from 1.33 to 2.4. The simulations for better glazing (high-performance low-e glazing) are trying to find out whether glazing (LSG) would be beneficial to energy trade-off of cooling and lighting and how much it would affect energy output. 0.41 0.50 0.60 1.32 1.10 1.01 1.74 1.60 1.62 0.00 0.50 1.00 1.50 2.00 20% 30% 40% Energy Consumption WIndow Aspect Ratio Annual Energy Consumption-North-Optimal WAR(kwh/sf) cooling lighting total 77 4.4.1. South Figure 65 Annual Energy Consumption-Optimal WAR-better glazing-South In comparison with the energy performance of base glazing simulations for optimal window-aspect ratios, the use of better glazing saves a great deal of energy, especially for WWR greater than 30%. The major energy savings benefit is from cooling load reduction in light of the increased LSG. The energy load of better glazing decreases 7%, 24% and 29% for WWR 10%, 20%, and 30% from the results of base glazing. The tendency shown on the energy consumption chart indicates that a better glazing would promise a bigger window-to-wall ratio with less energy use since WWR of the minimum cooling and lighting use alters from 10% to 20%. 0.49 0.64 0.84 1.38 1.01 0.95 1.88 1.64 1.79 0.00 0.50 1.00 1.50 2.00 10% 20% 30% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-South window-Better glazing(kwh/sf) cooling lighting total 78 4.4.2. East Figure 66 Annual Energy Consumption-Optimal WAR-better glazing-East When better glazing is utilized for east facing windows, a noticeable decrement is depicted for window-to-wall ratios of 20%, 30%, and 40%. The most energy is conserved for WWR 40% by the 20% reduction. As a result, WWR 40% with better glazing in the optimal window-aspect ratio would be recommended. It is likely that an even bigger WWR would perform better, but it is not included in this study. 4.4.3. West Figure 67 Annual Energy Consumption-Optimal WAR-better glazing-West 0.53 0.61 0.69 1.63 1.35 1.19 2.16 1.95 1.88 0.00 0.50 1.00 1.50 2.00 2.50 20% 30% 40% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-East window-Better glazing(kwh/sf) cooling lighting total 0.55 0.66 0.79 1.58 1.29 1.13 2.12 1.94 1.92 0.00 0.50 1.00 1.50 2.00 2.50 20% 30% 40% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-West window-Better glazing(kwh/sf) cooling lighting total 79 The lowest energy load altered from the condition of window-to-wall ratio 30% to 40% after the installment of better glazing with 20% energy difference. 4.4.4. North Figure 68 Annual Energy Consumption-Optimal WAR-better glazing-North The better glazing of higher LSG would also save energy for the North façade, however, not as much as energy for other orientations. The WWR 40% or bigger would be recommended for windows with better glazing. 4.5. EXTERIOR SHADING The exterior overhangs are simulated for the south façade with a 30 degree projection (projection distance equal to 60% of window height) and 45 degree projection (projection equal to window height). Windows of the best-performing window aspect ratio and window-to-wall ratio at the sill height of 0.1m from top of the wall are simulated with either base glazing or better glazing at 30” workplane level of illuminance level of 350 lux. The purpose of this shading device study is trying to find out if exterior overhang could save much cooling and lighting energy, and how much the difference could be for base and better window glazing types and for 60% and 100% projections. All these 0.33 0.38 0.44 1.21 1.04 0.98 1.54 1.42 1.42 0.00 0.50 1.00 1.50 2.00 20% 30% 40% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-North window-Better glazing(kwh/sf) cooling lighting total 80 overhangs are flush with the top of the window and are simulated to save annual energy load. These overhangs are not as energy effective compared to offset overhangs, but consider the limit of this study, those studies of exterior and interior shading devices can be put into future work. 4.5.1. Exterior overhang-60% projection • Base glazing Figure 69 Annual Energy Consumption-60% overhang-base glazing-South Adding exterior shading devices of 60% projection of window height on Sep. 22 nd fails to make any energy reduction for the south facing windows. On the contrary, due to the significant decrease on the amount of daylighting, the lighting use increases dramatically. Thus the total energy use increases for conditions of WWR 10% to 30% with 60% projection. 0.72 1.11 1.52 1.63 1.16 1.04 2.35 2.28 2.57 0.00 1.00 2.00 3.00 10% 20% 30% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-Base glazing-Exterior overhang 60% projection(kwh/sf) cooling lighting total 81 Figure 70 Annual Energy Consumption-exterior overhang-base glazing-WWR 20%-South Because of the energy increase for all WWR with installment of a 0.65m exterior overhang, smaller shading depths are simulated for WWR 20% in order to find out whether the overhang depth for 60% window projection is too deep and whether it would block the majority of daylight. However, the chart of energy use for different overhang depths indicates only little decrease of total energy for 0.2m overhangs, and for other depths (0.4m and 0.65m), the total energy uses of both lighting and cooling increase a lot. As a result, adding exterior overhang does not make less energy use for WWR 10% to 30% placed on the south under conditions for this case study. 1.13 1.12 1.12 1.12 1.11 1.03 1.03 1.03 1.16 1.16 2.16 2.16 2.15 2.28 2.28 0.00 1.00 2.00 3.00 0m 0.1m 0.2m 0.4m 0.65m Annual Energy Consumption (kwh/sf) Depth of Shade Annual Energy Consumption-Base glazing-Exterior overhang-WWR 20%(kwh/sf) cooling lighting total 82 • Better glazing Figure 71 Annual Energy Consumption-60% overhang-better glazing-South Similar with base glazing conditions, an increment of energy use for every WWR (10% - 30%) is shown in the chart for 60% projection overhangs with better glazing windows. 4.5.2. Exterior overhang-100% projection • Base glazing Figure 72 Annual Energy Consumption-100% overhang-base glazing-South 0.48 0.62 0.81 1.51 1.10 1.01 1.98 1.72 1.82 0.00 0.50 1.00 1.50 2.00 2.50 10% 20% 30% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-Better glazing-Exterior overhang 60%projection(kwh/sf) cooling lighting total 0.72 1.11 1.52 1.64 1.16 1.05 2.36 2.27 2.56 0.00 1.00 2.00 3.00 10% 20% 30% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-Base glazing-Exterior overhang 100%projection(kwh/sf) cooling lighting total 83 When installing an exterior overhang to block 100% sun projection of the window height on Sept. 22 nd 12pm, as expected, there is an even more energy consumption than that of 60% projection overhangs. • Better glazing Figure 73 Annual Energy Consumption-100% overhang-better glazing-South For 100% projection overhang with better glazing, the same amount of annual energy use intensity is shown as that of 60% projection overhang generates. In the case studies of exterior overhangs, no energy reduction is shown compared to no- shade conditions. The possible explanation would be that because of much daylight is shielded by the overhang, more electric lighting is wanted. Even though the overhang also blocks solar heat gain, the cooling load does not decrease much due to excessive need for cooling lighting fixtures. We are not convinced of these results. It is intended that this part of the study (exterior overhangs) be re-visited in the future as the results seem counter-intuitive and go against other studies. 0.48 0.62 0.81 1.51 1.10 1.01 1.98 1.72 1.82 0.00 1.00 2.00 3.00 10% 20% 30% Annual Energy Consumption (kwh/sf) WIndow Aspect Ratio Annual Energy Consumption-Better glazing-Exterior overhang 100%projection(kwh/sf) cooling lighting total 84 4.6. SUMMARY The charts presented in this chapter are conducted for Climate Zone 06 (Los Angeles). The simulation data for another location of Climate Zone 15 (Blythe) are collected in Appendix B, and the analyses for both Climate Zones are included in Chapter 5. According to the energy consumption data for both Climate Zones, north-facing windows tend to be larger (30%-60%) and south-facing windows are smaller (10%-30%). But the best performance range for east and west are climate-dependent. For CZ06, windows on the east and west have a tendency to be larger (20%-60%), while for CZ15, east and west windows should be as small as 10%-30% of the wall area. By changing window placement (window height), illuminance levels, and glazings, the best performance range of window-to-wall ratios may vary. Exterior overhangs flush with the head of the window and with 60% projection and 100% projection do not make much difference in the final energy load results. Exterior overhangs are not recommended for balancing cooling and lighting load under the conditions of this study. As mentioned earlier, the results about shading are not convincing and need to be re-analyzed. 85 Chapter 5: Analysis 5.1. IMPACT OF VARIABLES 5.1.1. Window placement and illuminance level Figure 74 Analysis of window placement and illuminance level The window placements shown in the table are top (0.1m from top of the wall), 0.7 (0.7m from top of the wall) and middle (1.5m from top of the wall). From the summarized chart, the best performance window-to-wall ratios for south, north, east and west are 10%-30%, 30%-60%, 30%-60% and 30%-60% for almost every window height. The window placements of 0.1m from top of the wall and 0.7m from top of the wall result in similar energy consumption, while a window placed in the middle height always consumes much more energy. In order to make a comparison of conditions, windows on top are selected for the following studies of variables. The window-to-wall ratios have a tendency to be smaller when changing the illuminance level from 500 lux to 350 lux. The 86 simulation results are based on certain conditions, so they are used for giving guidance in decisions for specific window parameters, however, the best performance range would change under different conditions. Furthermore, by decreasing the designed illuminance level, the total energy use is reduced. So changing the required illuminance level can be used for energy reduction, but task lighting might be needed depending on activities in the office. 5.1.2. Window aspect ratio Figure 75 Analysis of window aspect ratio Studies of window aspect ratios are conducted for best performance window-to-wall ratio range and at the illuminance level of 500 lux. Windows with an aspect ratio of 2/1 indicate better energy performance. For south facing windows, window aspect ratios of 4/1 and 2/1 are recommended. For north facing windows, width to height ratios of 2/1 and 1/1 would be recommended. For the east and west, window aspect ratio of 2/1 would have the best energy performance, however other aspect ratios of 4/1 and 1/1 tend to have similar energy performance. For all four orientations, vertical windows of ½ aspect ratio 87 are not recommended. The optimal performance ratio from Galapagos optimization shows a slightly less or an equal energy use compared with the best-performing window aspect ratio from manual simulations. In a word, horizontal windows are recommended for energy conservation that helps prove the theory of “five point architecture” from Le Corbuiser, and different window aspect ratios can affect energy performance. However, compared to the influence of window placement and illuminance level, the energy reduction is much less. 5.1.3. Window glazing Figure 76 Analysis of window glazing Base and better glazing properties are simulated for four orientations. The better glazing shows the most energy savings, as much as 0.52 kwh/sf for WWR 20% and 0.73kwh/sf for WWR 30%, for south facing windows. It is proved in the results that better glazing tends to save more energy for bigger windows rather than smaller window sizes for the south. In contrast, for east and west facing windows, the energy savings for WWR 30% and 40% are similar. Better glazing fails to save as much energy for the north as it does for the south, but the energy reduction is more than that from the analysis of window 88 aspect ratios. Moreover, better glazing predicts a bigger window-to-wall ratio for east, west, and north in light of energy savings. 5.1.4. Exterior overhang Figure 77 Analysis of exterior overhang Compared to the energy performance results without any shading devices, adding an exterior overhang makes the modeled office consume more total energy. It is shown in the table that 60% projection overhang and 100% projection overhang don’t make much difference in terms of energy use under the condition of windows with best-performed window-aspect ratio placed on 0.1m from top of the wall. As mentioned previously, although current results lead to this conclusion, we would like to revist this part of the study at a later date. 89 5.2. FENESTRATION GUIDELINES Figure 78 Fenestration guidelines for Climate Zone 6 (Los Angeles) and for Climate Zone 15 (Blythe) The table presents guidelines for fenestration choices for balancing energy tradeoffs between cooling and lighting load. The guidelines include window placement, window- to-wall ratio, window-aspect ratio and glazing. For Climate Zone 06, the best choice of window height for south and east windows is 0.1m from the top of the wall, and for north and west, it is 0.7m from the top of the wall. These best performance scenarios of window height are chosen based on the results from all window-to-wall ratios of 0%-80%, except for WWR 10% facing south, which shows less energy load for window height of 0.7m from top. The best performance range of window-to-wall ratios for an illuminance level of 500 lux is 10%-30% for the south, and 30%-60% for the north, east and west. However, if under the condition of a lower illuminance level of 350 lux, the best choices for window sizes are generally becoming 90 smaller for all the orientations. For the south, it turns to be from 0%-20%, and for other orientations, the best performance ranges are either wider or smaller-20% to 60% for north and east, 20% to 40% for west. From the simulation results of window-aspect ratio of 4/1, 2/1, 1/1 and ½, the best performance width to height ratio is 2/1 in general and it is true to all orientations and their best performance WWR range, except that for WWR 20% on the north, w/h ratio of 1/1 would be the best choice. The optimal choices of window-aspect ratio from Galapagos optimization are different for every orientation. It has a tendency to be a small square size window for south, and as large as 40% window area rectangular window for east, west, and north. Choices for glazing are, as expected, to be high performance low-e glazing with light to solar gain ratio of 2.44. For Climate Zone 15, windows on the south tend to consume less energy for cooling and lighting when placed 0.1m from the top of the wall, but for windows on north, east and west, lower windows at 0.7m from the top of the wall show a reduced energy load compared to 0.1m and mid-height conditions. Different from Climate Zone 06, the best- performing window-to-wall ratio for east and west orientations are 10%-30% for Blythe with the required illuminance level of 500 lux. However, changing the requirement for lighting level to 350 lux does not show a difference in the result of optimum WWR ranges for south, east and west. For the north facade, a lower lighting level of 350 lux shifts the optimum WWR from 20%-60% to 20%-40%. The recommended window- aspect-ratios and glazing properties for Climate Zone 15 are almost the same with the 91 results from Climate Zone 06, which are width to height ratio of 2/1 and high-performed low-e glazing with LSG 2.44. 5.3. BUILDING CODE COMPLIANCE Figure 79 Energy savings based on different conditions ASHRAE 90.1 2007 has no baseline or requirement for window placement or window- aspect ratio. However, as it is shown in the table, moving windows from middle to top would help energy saving of as much as 12% for windows placed on one orientation. Moreover, a window with best performance window-aspect ratio for south and north facades can save up to 16% energy use of cooling and lighting but it fails to save as much for the east and west. When it comes to better performance glazing, it would helped save about 20%-40% energy load compared to the baseline glazing from ASHRAE 90.1 2007 92 Figure 80 Summary of credits and prerequisites that this study would help achieve The table shows the possible credits and points that would be achieved by this study. The major credits are most likely to be achieved by energy savings. Other credits such as lighting control systems; daylight and view could be achieved by installing continuous dimming light sensors, daylight harvesting, and the placement of the window. 93 Chapter 6: Conclusion and Future Work 6.1. CONCLUSION The hypothesis was to prove or disprove whether there is an optimal window-to-wall ratio, window height, window-aspect ratio, glazing, and exterior shading devices for office buildings for specific climate zones in California in terms of less energy use of electric lighting and cooling. According to the simulation results, it turns out that it is possible to find an optimal range for window-to-wall ratio that saves the most cooling and lighting load from trade-offs for each orientation. It is also true to window height, window-aspect ratio, glazing, and exterior shading. These all vary based on climate, internal load and glazing type. The simulations of window configurations were conducted for a typical-size office. The output of annual energy load of cooling and lighting was compared and analyzed for each configuration. DIVA for grasshopper was the major simulation software used for the parametric study for the impacts of different window configurations. EQUEST was also used as a simulation tool for the validation of accuracy and reliability (see Appendix C). For most simulations and parameters, the results from EQUEST showed positive correlation of the tendency and optimal window configurations with those from DIVA for Grasshopper. Generally, according to the simulation results, the optimal window-to-wall ratio is 10%- 30% for the south, however, it tends to be larger (20%-60%) for the north based on the 94 results conducted for illuminance level of 500 lux with windows placed 0.1m from top of the wall. For east and west orientations, it depends on different climate conditions. On one hand, the windows have a tendency to be smaller, which is 10% to 30% window-to- wall ratios for Climate Zone 15; on the other hand, the optimum window-to-wall ratios for Climate Zone 06 are from 20%-40%. The results were conducted under certain conditions and would get changed if any of the parameters altered. Since the purpose of this study was to find out whether having a window is better than not having a window (and having energy efficient electrical lighting) and whether there is an optimal window configuration, the results simulated for a certain conditions show either a tendency or an optimal configuration and thus are acceptable. For the parameter of window height, for most of configurations, a higher window placement is better at energy reduction of cooling and electric lighting. For window-aspect ratios, width to height ratio of 4/1, 2/1, 1/1 and 1/2 were compared and for all orientation and WWR from 10% to 40%, it was found that a lower energy load resulted in the condition of 2/1. Galapagos was taken used of to get minimal energy load in terms of window parameters. To obtain further energy reduction, using better glazing system of LSG~2.4 had a great effect regardless of orientations. Exterior overhang fixed on south-facing windows, as expected, could also save cooling and lighting use because of daylight trade-offs. 6.2. LIMITATION The fenestration study of balancing trade-offs between daylight harvesting and energy load includes many variables beyond the parameters used in this study. Illuminance level and room depth were two other parameters simulated in order to find the impact of 95 window choices. However, several other parameters, such as lighting power density, equipment power density, lighting control strategies, thermostat set-points for heating and cooling, occupancy schedule, internal blinds, etc. may affect the simulation results, and thus change the fenestration choices in the guidelines. For example, for lighting power density, 1.0 w/sf was used in this study for all conditions but when the desired illuminance level is 350 lux, a lighting power density of 0.8 w/sf is preferred for lower lighting load. For the setting of equipment power density, 0.8w/sf was used according to ASHRAE 90.1-207 minimum requirement, however, in real office conditions, 1.5 w/sf is commonly used. For the lighting control system, 10% continuous dimming is chosen for all conditions, but stepped dimming may get more energy reduction for specific conditions, and the final choice of window would be changed accordingly. For heating and cooling set-points, a wider range of 65F to -78F would save more cooling load compared to the range of 70F-75F. There are also limitation and inaccuracy of simulation software programs that make it difficult to directly study the trade-offs. 6.3. FUTURE WORK The fenestration guidelines are summarized based on the total use of cooling and lighting energy, however, other factors such as daylight availability, occupant behaviors, internal blinds and visual comforts are not taken into consideration. In addition, revisiting the exterior shading simulations should be part of the future work. 6.3.1. Study of daylight autonomy and over-illumination The daylight autonomy is the annual daylight metrics that is used to present a percentage of annual daytime hours that a given point in the space would be above a certain 96 illuminance level. Different from the commonly simulated metric of daylight factor, which is determined for specific time of day, daylight autonomy calculates all sky conditions throughout the year. The daylight autonomy is an essential factor that would help with fenestration design and glazing choices. It is dependent on the illuminance requirement of users, the occupant schedule and blind schedules. The study of daylight autonomy is to find out how many hours could be shut off for the electric lighting, thus it saves energy. Another issue related to trade-offs between daylight and energy use is called over-illumination. It represents lighting illuminance levels beyond the requirement for a certain space. Daylight autonomy max is an indicator for too much light beyond a maximum level in a space. Analysis of daylight autonomy max on fenestration design, shading devices, task lighting, lighting zones and etc. would contribute to a further reduction in energy load and better visual comfort. 6.3.2. Study of occupant behavior This study does not take occupant behavior into consideration. The occupant behavior means differences of comfort for occupants, which includes thermostat heating and cooling set points, various levels of illumination, work location and work schedule, and preferred blind position over the course of the day and year. In this study, the occupant behaviors are simplified to a certain condition. Varying occupant behaviors would result in different results for energy consumption of cooling and lighting, and grouping occupant preference would show more comprehensive results for fenestration recommendations. In other words, occupant behavior can be an additional parameter to continue with the current study. 97 6.3.3. Study of interior blinds and schedule Besides exterior shading devices, interior blinds are another option to block direct sunshine. There are many kinds of blinds, such as roller blinds, venetian blinds, internal blinds etc. Even though interior shadings are less effective in preventing solar gains compared to exterior shading systems, highly reflective internal blinds are likely to reduce much heat gain in the summer while providing adequate illumination in the interior. Exterior shades tend to block views from the outer sky; however, interior blinds are flexible and controllable by occupants. The schedule of interior blinds is dependent on human behavior, and it would make a great change of energy load in the space. Studies of blinds and schedules can be conducted to complement studies of cooling and lighting energy trade-offs. 6.3.4. Study of glare and visual comfort A good visual comfort makes occupants more productive. Glare, which leads to discomfort to human eyes, is caused by high or non-uniform distribution of direct light. Although the glare issue is not directly related to energy use of lighting and cooling, it can be an independent further study of visual comfort in office buildings. For office spaces, glare is mostly caused by direct sunshine hitting on the computer or on the desk. Large area windows without any shading devices would likely cause significant glare problems. The Daylighting Glare Index (DGI) is the commonly used indicator to calculate glare performance, and it can be simulated using DIVA for Grasshopper. 98 Bibliography American Society of Heating, Refrigeration and Air-Conditioning Engineers, Inc. ASHRAE/IESNA Standard 90.1-2007 Antony D., Radford. "Optimization, Simulation and Multiple Criteria in Window Design." ., 2007. Computer-Aided Design Architecture 2030. "Problem: the building sector-energy consumption by sector." 2011. U.S. Energy Information Administration. < 13.6 (1981): 345-50. . http://architecture2030.org/the_problem/buildings_problem_why>. Architecture 2030. "Solution: the building sector-2030 challenge." 2010. <http://architecture2030.org/the_solution/solution_energy>. California Energy Commission. 2008 Building and Energy Efficiency Standards/Regulations for Residential and Nonresidential Buildings (Title 24) Cantin, F., and M-C Dubois. 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"Image of VillaSovoye." 2008. < ., 2009. http://en.wikipedia.org/wiki/File:VillaSavoye.jpg>. 101 Appendix A-Parametric and Simulation Tool Description Rhino (http://www.rhino3d.com/) is a 3d NURB-based surface-modeling program. It is widely used as a 3d modeling programming, but is also used with Grasshopper and specially developed components for Grasshopper like DIVA and Viper. Grasshopper (http://www.grasshopper3d.com/) is a free, graphical algorithm editor tightly integrated with Rhino's 3d modeling tools. It is also referred to as an associative modeling system. One feature it has allows for easier studying of parametric variations. Galapagos (http://www.grasshopper3d.com/group/galapagos) is a problem-solving component using evolutionary system and it is built in Grasshopper. It can be used as a program to find out fit individuals (minimum or maximum fitness functions) out of many generations. Galapagos provides optimum solution to a certain problem, but the accuracy of the solutions is dependent on how good the values (generation, population, mutation, fitness, etc) are defined. 102 Figure 81 Settings in Galapagos Figure 82 Galapagos Editor-Evolutionary Solver 103 DIVA for Rhino (http://wiki.diva-for-rhino.com/HomePage) “is a sustainable design plug-in for the Rhinoceros - NURBS modeling for Windows application. The plug-in has been developed by Christoph Reinhart, Alstan Jakubiec, Kera Lagios, Jeff Niemasz and Jon Sargent at the GSD-Squared research initiative at Harvard University and allows users to carry out a series of performance evaluations of individual buildings and urban landscapes including radiance maps, visualizations, climate-based metrics, glare analysis and LEED NC IEQ8.1 compliance.” DIVA for Grasshopper (http://wiki.diva-for-rhino.com/Grasshopper_Install) is an extension for DIVA for Rhino, which is capable of generative modeling under Grasshopper environment. There are two parts, one is for daylight performance simulation, the other one is for thermal simulations (Viper). The viper component is used in this study. Viper (http://wiki.diva-for-rhino.com/Grasshopper_Thermal) is the thermal component in DIVA for Grasshopper. “It runs thermal analyses from Grasshopper using Energy Plus, a simulation engine developed by the U.S. Department of Energy. As of DIVA version 1.901, Viper can be used to run single-zone thermal models composed of planar faces. Unlike the daylighting components, the thermal components operate independently of the DIVA Rhino toolbar (thermal analysis will be added to the Rhino toolbar in DIVA 2.0). So, you can use Viper without having first run an analysis in Rhino.” 104 Figure 83 Viper component definitions 105 Figure 84 Construction Assembly-default options and custom options Figure 85 Window unit component-default and custom option of glass layers Figure 86 Window unit component-custom options of glazing properties, and fixed shade component 106 Appendix B-Energy performance results from EQUEST All simulation results from EQUEST are shown in Appendix B. Five different scenarios are simulated and it turns out the tendency presented in the charts are consistent with the results from DIVA for Grasshopper. These scenarios include windows placed 0.1m from top of the wall with lighting level of 500lux, window placed 1.5m from top of the wall with lighting level of 500lux, windows placed 0.1m from top of the wall with illuminance level of 350lux, windows placed 0.1m from top of the wall using base glazing (the same base glazing with choices in DIVA) under 500lux and windows placed 0.1m from top of the wall using better glazing (the same better performance glazing with choices in DIVA) under 500lux. Other settings are consistent with those conditions in DIVA for Grasshopper. Simulations are conducted for four orientations and for Climate Zone 06 (Los Angeles). • South 0.91 1.00 1.26 1.52 1.78 2.27 2.73 2.15 0.92 0.57 0.55 0.54 0.54 0.53 3.07 1.92 1.83 2.07 2.32 2.81 3.27 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)(kwh/sf) cooling lighting total 107 0.91 1.03 1.26 1.52 1.78 2.27 2.73 2.15 1.13 0.60 0.57 0.55 0.54 0.54 3.07 2.15 1.86 2.09 2.33 2.81 3.27 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window in the middle(500lux)(kwh/sf) cooling lighting total 0.91 0.96 1.26 1.52 1.78 2.27 2.73 2.14 0.70 0.55 0.54 0.53 0.53 0.52 3.06 1.67 1.81 2.06 2.31 2.80 3.26 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) cooling lighting total 0.91 0.86 1.01 1.19 1.36 2.14 0.58 0.55 0.54 0.53 3.06 1.44 1.56 1.73 1.89 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-better glazing(kwh/sf) cooling lighting total 108 • East 0.91 0.94 1.19 1.45 1.70 2.14 0.61 0.56 0.55 0.54 3.06 1.55 1.75 2.00 2.24 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-base glazing(kwh/sf) cooling lighting total 0.91 0.95 1.00 1.08 1.24 1.53 1.84 2.15 1.36 0.95 0.76 0.66 0.59 0.56 3.06 2.31 1.95 1.85 1.89 2.11 2.40 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)(kwh/sf) cooling lighting total 0.91 0.96 1.01 1.09 1.24 1.53 1.84 2.15 1.51 1.05 0.82 0.70 0.60 0.57 3.07 2.47 2.07 1.91 1.94 2.13 2.40 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window in the middle(500lux)(kwh/sf) cooling lighting total 109 • West 0.91 0.92 0.98 1.07 1.23 1.53 1.84 2.15 1.12 0.78 0.63 0.58 0.55 0.55 3.06 2.05 1.76 1.70 1.81 2.08 2.38 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) cooling lighting total 0.91 0.92 0.97 1.04 1.19 1.47 2.15 1.13 0.79 0.63 0.58 0.56 3.06 2.05 1.75 1.68 1.77 2.03 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-base glaizng(kwh/sf) cooling lighting total 0.91 0.87 0.89 0.92 0.98 1.16 2.15 1.00 0.69 0.58 0.56 0.55 3.06 1.87 1.58 1.51 1.53 1.71 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-better glazing (kwh/sf) cooling lighting total 110 0.92 1.00 1.13 1.29 1.46 1.79 2.12 2.15 1.26 0.83 0.67 0.60 0.55 0.54 3.07 2.25 1.97 1.97 2.06 2.34 2.66 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)(kwh/sf) cooling lighting total 0.92 1.01 1.14 1.30 1.47 1.79 2.12 2.15 1.41 0.93 0.73 0.63 0.56 0.54 3.07 2.42 2.07 2.03 2.10 2.35 2.66 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window in the middle(500lux)(kwh/sf) cooling lighting total 0.92 0.97 1.12 1.29 1.46 1.79 2.12 2.15 1.01 0.69 0.58 0.54 0.53 0.52 3.07 1.97 1.80 1.87 2.00 2.31 2.64 0.00 1.00 2.00 3.00 4.00 100.00% 200.00% 300.00% 400.00% 500.00% 600.00% 700.00% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) cooling lighting total 111 • North 0.92 0.95 1.10 1.25 1.42 1.72 2.15 1.02 0.69 0.58 0.55 0.53 3.07 1.97 1.79 1.84 1.96 2.26 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-base glaizng (kwh/sf) cooling lighting total 0.92 0.88 0.97 1.08 1.19 1.39 2.15 0.89 0.62 0.55 0.54 0.53 3.07 1.77 1.59 1.63 1.73 1.92 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-better glazing(kwh/sf) cooling lighting total 0.91 0.89 0.88 0.91 0.95 1.08 1.19 2.16 1.28 0.80 0.63 0.57 0.55 0.54 3.07 2.17 1.68 1.53 1.52 1.63 1.74 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)(kwh/sf) cooling lighting total 112 0.91 0.90 0.88 0.91 0.95 1.08 2.16 1.54 0.83 0.64 0.58 0.55 3.07 2.43 1.71 1.54 1.53 1.63 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)(kwh/sf) cooling lighting total 0.91 0.86 0.86 0.89 0.95 1.07 1.19 2.14 1.19 0.65 0.56 0.55 0.54 0.53 3.06 2.06 1.50 1.45 1.50 1.61 1.72 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% 60% 80% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(350lux)(kwh/sf) lighting cooling total 0.91 0.94 0.62 0.56 0.55 2.14 0.83 0.84 0.88 0.93 3.06 1.77 1.46 1.44 1.48 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-base glaizng (kwh/sf) cooling lighting total 113 0.91 0.78 0.80 0.82 0.84 2.14 0.78 0.57 0.55 0.54 3.06 1.56 1.37 1.37 1.39 0.00 1.00 2.00 3.00 4.00 0.10% 10% 20% 30% 40% Annual Energy Consumption (kwh/sf) WWR Annual Energy Consumption-window on top(500lux)-better glazing (kwh/sf) cooling lighting total 114 Appendix C-Energy performance results of CZ 15 from DIVA All energy performance results of Climate Zone 15 (Blythe) are exported from DIVA for Grasshopper. All settings are consistent with those used for Climate Zone 06 (Los Angeles). • South-Window placement 2.55 2.95 3.46 3.99 4.72 6.16 7.53 3.24 1.76 1.24 1.06 1.00 0.97 0.97 5.79 4.71 4.70 5.04 5.73 7.13 8.50 0.00 5.00 10.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-South (kwh/sf) cooling lighting total 2.55 3.01 3.55 4.10 4.96 6.45 7.86 3.24 1.84 1.24 1.07 1.02 0.98 0.97 5.79 4.85 4.80 5.17 5.98 7.43 8.82 0.00 5.00 10.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window midheight-full width-South (kwh/sf) cooling lighting total 115 • South-Window aspect ratio 2.55 2.98 3.54 4.10 3.24 1.62 1.16 1.03 5.79 4.59 4.71 5.13 0.00 2.00 4.00 6.00 8.00 0% 10% 20% 30% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window 0.7m from top-full width- South (kwh/sf) cooling lighting total 2.55 2.89 3.42 3.96 4.72 6.16 7.53 3.24 1.47 1.08 0.99 0.97 0.95 0.95 5.79 4.36 4.51 4.96 5.69 7.10 8.47 0.00 5.00 10.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-South- 350lux (kwh/sf) cooling lighting total 2.89 2.89 2.90 2.95 1.53 1.52 1.59 1.85 4.42 4.41 4.49 4.80 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR10%-South (kwh/sf) cooling lighting total 116 • South-Better performance glazing • North-Window placement 3.41 3.41 3.41 3.44 1.17 1.13 1.14 1.29 4.58 4.54 4.55 4.73 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR20%-South (kwh/sf) cooling lighting total 3.93 3.93 3.94 1.04 1.02 1.07 4.97 4.95 5.01 0.00 2.00 4.00 6.00 4 2 1 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR30%-South (kwh/sf) cooling lighting total 2.52 2.72 2.96 1.47 1.09 1.00 3.99 3.80 3.96 0.00 2.00 4.00 6.00 10% 20% 30% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-WAR2/1-South-better glazing (kwh/sf) cooling lighting total 117 2.36 2.47 2.57 2.70 2.87 3.25 3.82 3.24 2.56 1.88 1.39 1.13 1.00 0.99 5.60 5.03 4.45 4.09 4.00 4.25 4.81 0.00 2.00 4.00 6.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-North (kwh/sf) cooling lighting total 2.36 2.46 2.57 2.71 2.91 3.36 3.99 3.24 2.50 1.81 1.33 1.15 1.03 0.99 5.60 4.97 4.38 4.05 4.06 4.40 4.98 0.00 2.00 4.00 6.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window midheight-full width-North (kwh/sf) cooling lighting total 2.36 2.46 2.57 2.73 3.24 2.42 1.70 1.27 5.60 4.88 4.27 4.00 0.00 2.00 4.00 6.00 0% 10% 20% 30% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window 0.7m from top-full width- North (kwh/sf) cooling lighting total 118 • North-Window aspect ratio 2.36 2.42 2.50 2.65 2.84 3.24 3.82 3.24 2.27 1.48 1.11 1.00 0.96 0.96 5.60 4.69 3.98 3.76 3.84 4.20 4.77 0.00 2.00 4.00 6.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-North- 350lux (kwh/sf) cooling lighting total 2.68 2.65 2.66 1.29 1.18 1.33 3.96 3.83 3.99 0.00 2.00 4.00 6.00 4 2 1 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR30%-North (kwh/sf) cooling lighting total 2.53 2.50 2.49 2.53 1.68 1.55 1.53 1.86 4.21 4.06 4.03 4.40 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR20%-North (kwh/sf) cooling lighting total 119 • North-Better performance glazing • East-Window placement 2.89 2.89 2.90 2.95 1.53 1.52 1.59 1.85 4.42 4.41 4.49 4.80 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR40%-North (kwh/sf) cooling lighting total 2.21 2.26 2.33 1.36 1.10 1.02 3.57 3.35 3.35 0.00 1.00 2.00 3.00 4.00 20% 30% 40% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-WAR2/1-North-better glazing (kwh/sf) cooling lighting total 2.48 2.81 3.16 3.55 3.94 5.02 6.09 3.24 2.46 1.95 1.64 1.43 1.21 1.19 5.71 5.27 5.11 5.19 5.37 6.23 7.28 0.00 2.00 4.00 6.00 8.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-East (kwh/sf) cooling lighting total 120 • East-Window aspect ratio 2.48 2.79 3.15 3.53 3.92 4.94 5.93 3.24 2.63 2.14 1.82 1.61 1.39 1.21 5.71 5.43 5.29 5.35 5.52 6.33 7.14 0.00 2.00 4.00 6.00 8.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window midheight-full width-East (kwh/sf) cooling lighting total 2.48 2.78 3.14 3.51 3.90 3.24 2.46 1.95 1.64 1.43 5.71 5.25 5.08 5.15 5.33 0.00 2.00 4.00 6.00 0% 10% 20% 30% 40% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window 0.7m from top-full width-East (kwh/sf) cooling lighting total 2.48 2.76 3.11 3.50 3.90 4.99 6.06 3.24 2.21 1.68 1.38 1.19 1.05 1.04 5.71 4.97 4.79 4.88 5.09 6.04 7.11 0.00 2.00 4.00 6.00 8.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-East-350lux (kwh/sf) cooling lighting total 121 • East-Better performance glazing 2.78 2.77 2.77 2.77 2.39 2.38 2.38 2.38 5.17 5.14 5.14 5.15 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR10%-East (kwh/sf) cooling lighting total 3.13 3.13 3.13 3.16 1.91 1.89 1.91 2.09 5.05 5.01 5.04 5.25 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR20%-East (kwh/sf) cooling lighting total 3.51 3.50 3.51 1.63 1.59 1.66 5.14 5.09 5.17 0.00 2.00 4.00 6.00 4 2 1 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR30%-East (kwh/sf) cooling lighting total 122 • West-Window placement 2.53 2.68 2.85 2.29 1.79 1.49 4.82 4.46 4.34 0.00 2.00 4.00 6.00 10% 20% 30% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-WAR2/1-East-better glazing (kwh/sf) cooling lighting total 2.42 2.66 2.94 3.45 4.02 5.20 6.37 3.24 2.42 1.90 1.58 1.37 1.14 1.12 5.65 5.08 4.84 5.03 5.39 6.34 7.49 0.00 2.00 4.00 6.00 8.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-West (kwh/sf) cooling lighting total 2.42 2.67 2.93 3.43 3.98 5.11 6.22 3.24 2.57 2.03 1.73 1.52 1.31 1.14 5.65 5.24 4.96 5.16 5.50 6.42 7.36 0.00 2.00 4.00 6.00 8.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window midheight-full width-West (kwh/sf) cooling lighting total 123 • West-Window aspect ratio 2.42 2.64 2.92 3.42 3.97 3.24 2.40 1.89 1.58 1.37 5.65 5.05 4.81 5.00 5.34 0.00 2.00 4.00 6.00 0% 10% 20% 30% 40% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window 0.7m from top-full width- West (kwh/sf) cooling lighting total 2.42 2.61 2.89 3.41 3.99 5.18 6.36 3.24 2.17 1.63 1.32 1.13 0.98 0.97 5.65 4.79 4.52 4.73 5.12 6.16 7.33 0.00 2.00 4.00 6.00 8.00 0% 10% 20% 30% 40% 60% 80% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-full width-West-350lux (kwh/sf) cooling lighting total 2.64 2.64 2.63 2.63 2.35 2.33 2.32 2.32 4.99 4.96 4.95 4.96 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR10%-West (kwh/sf) cooling lighting total 124 • West-Better performance glazing 2.93 2.92 2.92 2.94 1.86 1.83 1.84 2.03 4.79 4.75 4.76 4.97 0.00 2.00 4.00 6.00 4 2 1 1/2 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR20%-West (kwh/sf) cooling lighting total 3.45 3.44 3.44 1.57 1.53 1.59 5.02 4.97 5.03 0.00 2.00 4.00 6.00 4 2 1 Energy Consumption (kwh/sf) Window-aspect-ratio Annual Energy Consumption-window on top-WWR30%-West (kwh/sf) cooling lighting total 2.42 2.52 2.65 2.24 1.73 1.43 4.66 4.25 4.08 0.00 2.00 4.00 6.00 10% 20% 30% Energy Consumption (kwh/sf) Window-to-wall ratio Annual Energy Consumption-window on top-WAR2/1-West-better glazing (kwh/sf) cooling lighting total

Abstract (if available)

Abstract The early decisions made during the design phase of a building regarding the choice of windows have a large impact on future energy consumption. Although the final selection depends on many issues not directly related to energy concerns including aesthetics, cost, material, views, and client preferences, energy consumption is a major factor for several reasons. These include environmental concerns, financial aspects, code compliance, operations and maintenance over the lifetime of the building, and occupant comfort. One technique for saving energy is to harvest daylight

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Wu, Geman (author)

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

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Publication Date 05/09/2012

Defense Date 05/09/2012

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

Tag daylight harvesting,Diva for Grasshopper,energy trade-off,fenestration guideline,OAI-PMH Harvest

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Kensek, Karen M. (committee chair), Schiler, Marc (committee member), Simmonds, Peter (committee member)

Creator Email gemanwu@usc.edu,wugeman@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-38955

Unique identifier UC11289524

Identifier usctheses-c3-38955 (legacy record id)

Legacy Identifier etd-WuGeman-838.pdf

Dmrecord 38955

Document Type Thesis

Rights Wu, Geman

Type texts

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

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

Repository Name University of Southern California Digital Library

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