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Post occupancy energy evaluation of Ronald Tutor Hall using eQUEST; computer based simulation of existing building and comparison of data
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Post occupancy energy evaluation of Ronald Tutor Hall using eQUEST; computer based simulation of existing building and comparison of data
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Post Occupancy energy evaluation of Ronald Tutor Hall using eQUEST; Computer based simulation of existing building and comparison of data by Duyum Dulom A Thesis Presented to the FACUL TY OF THE SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF BUILDING SCIENCE May 2013 Copyright 2013 Duyum Dulom ii Acknowledgements I would like to express heartfelt thanks to Prof. Schiler, my committee chair who has been very supportive right from the start of this project. He not only gave me his valuable guidance with my research work but also gave me moral support when I had difficulty focusing on my work. I feel privileged to have had him in my committee. I would also like to thank Ms Karen Mozes, my committee member. I was able to structure my thesis work because of her in-depth feedback. I learned a lot from her thorough comments on my chapters. Prof. Noble, my third committee member has also given me his invaluable help. Today I ’ v e fi ni s he d m y project because of his persistent push to finish and meet deadlines. He gave me the discipline I needed to finish this project a nd for t ha t I ’m v e r y t ha nkful t o him. I would also like to acknowledge Jose Delgado and Carol Fern from the USC facility management services (FMS) who provided with all the documents needed for this research work. Without their help this project would not have been possible. Lastly I want to thank my friends Andrea Martinez and Guang Yang who gave me their valuable time and helped me figure solutions to problems in my research work. iii Table of Contents Acknowledgements ………………………………………………………………………..i i Abstract ………………………………… ………………………………………………..v i i Chapter 1: Introduction ………………… ………………………… ………………………1 1.1 USC Ronald Tutor Hall (RTH) School of Engineering Post Occupancy Evaluation ……………………… ………………………… ………………… ……3 1.2 Tools and Methods ……………… ………………………………………………...4 1.2.1 Thermal Comfort … ………… ………………………………………………...7 1.2.1a Thermal Comfort Calculation …..................................................................8 1.2.2 Tools and Methods used in Ronald Tutor Hall …...........................................11 1.3 Benefits of Post Occupancy Evaluation (POE) ……………...… …….……… ….13 1.4 Drawbacks of Post Occupancy Evaluation (POE) ……………… ……...…….….14 1.5 Caltrans District 7 Headquarters Building: A Case Study on Post Occupancy Evaluation ……………………… ………………… ……………………………..15 1.5.1 Energy efficiency measures …….……………… ……………………………16 1.5.2 Post Occupancy Evaluation results ….……………………. …………………18 Chapter 2: USC Ronald Tutor Hall School of Engineering ……………………………...21 2.1 Project background ………………………………………………………………21 2.2 Building Site and Characteristics ………………………………………………...22 2.3 Weather & Climate ……………… ………………………………………………28 2.4 Design Strategies for California Climate Zone 9 ………………………………...32 2.5 Building Plans …………………… ………………………………… ……………35 iv 2.6 Occupancy zoning profile of Ronald Tutor Hall ……………… …………… …...39 2.7 Hours of operation and mechanical systems schedule ……………………… …...41 2.8 Internal heat gain profile of Ronald Tutor Hall ………………………………….43 2.9 Mechanical System ………………………………………………………………47 2.9.1 HVAC system of Ronald Tutor Hall ….……………………………………..48 2.9.2 Air Handling Unit (AHU) …… …….………………………………………...48 2.9.3 Fan Coil Unit (FCU) ………… ….…………………………………………...51 2.10 Ronald Tutor Hall Energy Consumption Profile …………………………… …53 2.10.1 Current Ronald Tutor Hall Energy Consumption Data ….…………… …...54 2.10.2 Benchmarking the Energy Consumption of Ronald Tutor Hall with Energy IQ ………………… ………………………………… ……………56 2.11 Ronald Tutor hall Building Envelope profile ……………………………… …..58 Chapter 3: Research Background, Procedure & Methodology ……………….……… ….69 3.1 Background Research …………………………………………………………....69 3.1.1 Groundwork Research ……… ………………………………………… …….70 3.1.2 Indoor Thermal Comfort Research ……………………………………… …..73 3.1.3 Energy modeling tools ……… ……………………………………………….74 3.1.4 Energy Consumption Baseline Research ………………………………… ….76 3.2 Research Methodology ………… ……………………………………………….76 Chapter 4: Indoor Thermal Comfort Research of Ronald Tutor Hall ……………………79 4.1 Introduction ………………………………………………………………………79 4.2 Data Acquisition System (DAS) Installation of Ronald Tutor Hall ………… …..80 v 4.2.1 DAS Equipment ….…….…… … ……………… …………… …………………80 4.2.1a HOBOware Pro ….................. ........................................................................81 4.2.1b HOBO U12 Data Logger … …………………………………………… …...82 4.3 DAS Installation Procedure & Method …………………………………………..82 4.4 Location of Hobos/Data Loggers ………………………………………………...85 4.5 Analysis of the Data Logger Results …………………………………………….87 4.6 Summary ………………………… ………………………………………………98 Chapter 5: Building Energy Consumption Simulation model ……………………….....102 5.1 Weather Data …………………… ……………………………………………...102 5.2 Codes and Standards …………… ………………………………………………103 5.3 Creating the RTH Virtual Model ……………………………………………….103 5.3.1 Design Development Wizard ….……………………………………………104 5.3.2 Project/Site/Utility …………… …………….………………………………104 5.3.3 Bldg Shell Components ……… …………….………………………………105 5.3.4 Air-side System Types ……… …………….………………………………..107 5.3.5 CHW plant equipment ……… …………….………………………………..109 5.3.6 HW plant equipment ………… ……… …. ………………………………….109 5.4 Thermal Zones ………………………………………………………………….109 5.5 Geometric Model ……………… ……………………………………………….111 5.6 Simulation Result ……………… ……………………….………………………113 5.7 Calibration ……………………… ……………………..………………………..115 5.7.1 Analyzing Simulation Results …….……………….….…………………….116 vi 5.7.2 Calibration of RTH Model …………….……………………………………117 5.7.3 F i na l Ca l i bra t e d RT H m ode l … …….….…………...……………………….119 5.8 Measures to improve RTH Energy Consumption ………...…………………. …124 Chapter 6: Conclusion and Future Work ……………………………………………….130 6.1 Conclusion ……………………… ………………………………………… …...130 6.2 Future Work …………………… ……………………………………………….132 Bibliography …………………………… ………………………………………………135 vii Abstract Buildings account for about 40 percent of total U.S. energy consumption. It is therefore important to shift our focus on important measures that can be taken to make buildings more energy efficient. With the rise in number of buildings day by day and the dwindling resources, retrofitting buildings is the key to an energy efficiency future. Post occupancy evaluation (POE) is an important tool and is ideal for the retrofitting process. POE would help to identify the problem areas in the building and enable researchers and designers to come up with solutions addressing the inefficient energy usage as well as the overall wellbeing of the users of the building. The post occupancy energy evaluation of Ronald Tutor Hall (RTH) located at the University of Southern California is one small step in that direction. RTH was chosen to study because; (a) relatively easy access to the building data (b) it was built in compliance with Title 24 2001 and (c) it was old enough to have post occupancy data. The energy modeling tool eQuest was used to simulate the RTH building using the background information of the building such as internal thermal comfort profile, occupancy profile, building envelope profile, internal heat gain profile, etc. The simulation results from eQuest were then compared with the actual building recorded data to verify that our simulated model was behaving similar to the actual building. Once we were able to make the simulated model behave like the actual building, changes were made to the model such as installation of occupancy sensor in the classroom & laboratories, changing the thermostat set points and introducing solar shade on northwest and southwest façade. The combined savings of the proposed interventions resulted in a 6% savings in the overall usage of energy. 1 Chapter 1: Introduction The t e r m “ P os t O c c upa n c y E v a l ua t i on” according to Preiser and colleagues started to be used around the 1960 ’ s a nd i s s a i d t o ha v e i t s ori g i n i n the USA. (Preiser et al. 1988) (Federal Facilities Council, 2001) Post Occupancy Evaluation (POE) is believed to have started on the notion that better living spaces can be designed by interacting with the users of the building about their needs. Most of the early POE efforts as seen in Britain, France, Canada and the United States between the pe ri od 1960’ s – 1970 ’ s w e re fo c us e d on individual case studies such as public housing and college dormitories as these buildings were easily accessible to academic researchers. The POE effort focus was primarily on government and other public buildings because of the issue of permission to inspect the buildings with private ownership. The information was gathered from occupants of the building about their response to the building by means of questionnaires, interviews, site visits and observation. By doing so the researchers intended to learn what design elements work well, design that works best and design elements which should not be repeated in future buildings because of their observed issues. The private sector organization in the United States was said to be detached from POE process until the release of book “ Using Office Design to Increase Productivity ” (Brill et al., 1985) (Federal Facilities Council, 2001) which brought some awareness and made clients and designers pay attention to POE. The book summarizes the importance of having good office environment for increased workers productivity. Soon after the release of the book, buildings began to be seen as ways to achieve strategic goals such as “customer satisfaction, increased innovation, attraction and retention of high quality workers and 2 enhanced productivity of work groups ” (Federal Facilities Council, 2001) which led to more organizations getting involved with the POE process. One of the early definitions of Post Occupancy Evaluation was given by Preiser et al. (1988): “Post-occupancy evaluation (POE) is the process of evaluating buildings in a systematic and rigorous manner after they have been built and occupied for some time.” (Preiser et al. 1988) (Federal Facilities Council, 2001) A more recent definition was from the website on Post Occupation Evaluation: “Post Occupancy Evaluation involves systematic evaluation of opinion about buildings in use, from the perspective of the people who use them. It assesses how well buildings match users' needs, and identifies ways to improve building design, performance and fitness for purpose.” (Post Occupancy Evaluation, 2011) The two quotes seem to indicate that the notion of POE might have changed over time. The first quote talks about studying the building without mentioning the occupants of the building whereas the second quote talks of involving the occupants of the building to improve the performance of the building. Perhaps it initially made sense to do post evaluation study of the building alone and dismiss the involvement of users of the building because of the assumption that no fruitful input can come from regular building users who are layman when it comes to knowledge about buildings. Such post evaluation studies might actually work for buildings with few to no occupants such as storage house, warehouse etc. where users comfort can be easily dismissed. However conducting post evaluation studies without users input, of residences, commercial buildings, office buildings etc where users comfort is very important would be defeating the purpose. The 3 whole idea of post evaluation studies is to make building more efficient, however this efficiency should not be at the cost of the occupants comfort as buildings afterall are built for the people. If the occupants of the building are not comfortable, the high performance of the building itself would not be as valuable. The high performance of the building has to come with users comfort and to assure users comfort, it is very important to have feedbacks from them. Same goes for the systems of the building. Building systems are responsible for controlling the environment inside the building. The occupants of the building need to feel comfortable in the environment created inside. Therefore the efficiency of the system has to be designed around the comfort of the occupants. 1.1 USC Ronald Tutor Hall (RTH) School of Engineering Post Occupancy Evaluation Ronald Tutor Hall (RTH) is a 6 storied state of the art instructional and research complex at the University of Southern California (USC) campus. The building is part of the USC Viterbi School of Engineering. The project cost about 50 million US Dollars. The building opened to faculty, staff and students on Feb 2 nd , 2005.The building was designed by the architectural firm A.C.Martin Partners Inc. and the mechanical system was designed by IBE consulting engineers. The total area of the building is 102,503 square feet. It is not a very common practice for architects and engineers to go back to the project t he y ’ v e c om pl e t e d a nd c h e c k i f t he bui l di ng ’ s e ne r gy pe rform a nc e is as expected. The reasons can vary from not knowing how to do it, to not having time or simply that there 4 was no money set aside in the contract to do the post evaluation. POE is usually not in contract. This attitude, however, needs to change as there is lot to learn from the process of post evaluation. Without knowing how much energy the actual building is consuming, it is not possible to figure if all the principles applied in the design process have actually worked. Measurement and verification of the building systems can help to determine best capital improvement projects to help the existing facility reduce on energy use and costs. Post occupancy energy evaluation of Ronald Tutor Hall (RTH) is done for the very same reason. There has been no post evaluation study of R T H ’ s e ne r gy pe rform a nc e s i nc e i t was occupied. The post evaluation process of RTH for this thesis is intended to find if the bui l di ng ’ s e ne r gy pe rform a nc e i s e f fi c i e n t w he n c o m pa re d t o ot he r s i m i l a r bui l d i ng s (s e e benchmarking in Chapter 2, section 2.10.2) and what can be done to improve on present energy performance of the building. The ultimate goal is to propose strategies which w oul d i m prov e t he bui l di ng ’ s pe rform a n c e i n re g a rds t o i t s e ne r gy consumption. The procedure to proceed with the POE of RTH is explained in Chapter 3. 1.2 Tools and Methods M e i r e t a l . (2009) i n t h e i r j ourna l “ P os t -Occupancy Evaluation: An Inevitable Step Toward Sustainability ” c l a s s i fi e d P O E i n t hre e c a t e g ori e s ba s e d on t h e t ool s a nd m e t hods used. The three categories are; a) Measurements, monitoring, sampling b) Surveys, questionnaires, cohort studies, observations, task performance tests c) Document analysis, on-site observations 5 The first category is meant to help in understanding the existing condition by measurements, monitoring, and sampling various data including temperature, relative humidity, light intensity, noise levels, air movement, occupancy, pollutants, allergens, pathogens, electromagnetic fields, and solar radiation depending on the scope of the project. POE here is intended to bridge the gap between pre and post occupation phases and also provide link between various responses by the occupants to the building and between all the knowledge gained in the process that helps in establishing overall satisfaction. The second category attempts to find the intricate interrelations between the building, its users and the various building systems that are part of the operation which will help in clearly assessing the performance of the building. This is achieved by Surveys, questionnaires, cohort studies, observations, task performance tests. These tests primarily include asking questions to user of the building about their experiences in using the building facilities which may be in the form of online survey or in hard copy. The question can be asking users to rate on scale of 1 to 10 the adequacy of available light levels, noise level, temperature, ventilation, air quality. These questions are basically about overall comfort in the usage of the building. Also the occupants of the building are asked to perform series of different repetitive task like simple or complex mathematical calculation, typing, form matching, and word ide nt i f i c a t i on or t a s k t ha t t h e y ’re us ua l l y expected to perform. Finally the last category involves critical analysis of all documents at preconstruction stage such as drawings, details, briefs, specifications, etc. with the hope of tracking as many critical mistakes as possible so that it can be taken care of before the execution of the project. This observation may range from spotting an 6 awkwardly shaped wall to a structural element that not only causes wastage of space but also causes behavioral problem within the space. The method also includes surveys and walk through of the building at post construction stage to notice anything irregular such as mould and stains at HVAC outlet, or a window which is kept open at a conditioned space which is indicating that space inside is not comfortable or anything in the building that poses a possible health hazards. (Meir et al., 2009) Buildings are complex systems in regards to how every aspect of it, from its architectural design to materials used for construction to type of system installed to plumbing, electrical, etc. is interconnected, which contributes to making the building fit for use. When we add occupants to it, the whole interaction between the user and the building further adds to the complexity, as we now have to consider users comfort, their safety, convenience, etc. This is why it is necessary that tools and methods used in the study of POE are able to take into account all possible variables such as climatic condition of the site, architectural design, mechanical systems, internal heat gain, indoor air quality etc. to correctly analyze and assess the building. Tools and methods used in POE should be multifaceted in its checks and tests. The study should include all the aspects of the building that concerns user comfort both physiologically and psychologically which means it should include thermal comfort alongside heating ventilation & air-conditioning, illumination and visual comfort, oc c upa nt ’ s satisfaction, etc. 7 1.2.1 Thermal Comfort The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) is “an international building technology society with more than 50,000 members worldwide. ” ( ASHRAE, 2012) ASHRAE defines thermal comfort as the state of mind in humans that expresses satisfaction with the surrounding environment. So ‘t he rm a l c o m fort ’ de s c ri b e s a pe rs on’ s ps y c hol og i c a l s t a t e of m i nd, w hi c h oft e n i s a bout whether a person is feeling too hot or too cold. Thermal comfort is an important factor to gauge the performance of a building because several studies have shown that there is a direct relation between thermal comfort and produc t i v i t y . W he t he r i t ’ s a s t ude n t or a n of fi c e w orke r , t h e i r p e rform a n c e w a s obs e rv e d to improve considerably when their indoor environment was made better as shown in the re s e a rc h w ork “ E f fe c t s O f H V A C on S t ude nt P e rform a nc e ” done by Dr. Pawel Wargocki, & Dr. David Wyon and “ E f fe c t of T e m pe ra t ure on T a s k P e rform a nc e i n O f fi c e E nv i ronm e nt .” by Helsinki University of Technology. I t ’ s not e a s y to decide what will make people comfortable because various environmental factors such as air temperature, radiant temperature, air velocity, humidity and personal factors such as clothing insulation & metabolic heat has to be taken into account which means air temperature alone is not the measure of thermal comfort. (HSE, 2012) Health and Safety Executive (HSE), an independent watchdog for work-related health, safety and illness for Great Britain considers 80% of occupants as a reasonable limit for the minimum number of people who should be thermally comfortable in an environment, so thermal comfort is best assured by trying to achieve thermal environment that satisfies 8 the majority of people in the workplace. 1.2.1a Thermal Comfort Calculation The ‘T he r m a l Com for t ’ e qu a t i on derived by P.O.Fanger is too complicated for manual arithmetic and is normally solved using a computer. The Center for the Built Environment (CBE) at the University of California, Berkeley ha s de v e l ope d a ‘T h e rm a l Com fort T oo l ’ f or ASHRAE Standard 55 w hi c h he l ps i n c a l c ul a t i ng ‘T he rm a l Com fort ’. The tool is based on the PMV/PPD model that uses the Predicted Mean V ote formula by P. O. Fanger. The predicted mean vote (PMV) is the average comfort vote of a large number of people exposed to a certain environment. This vote is based on the seven-point ASHRAE thermal sensation scale as seen in Table 1.1 below. (Brandemuehl, 2005) Table 1.1 ASHRAE Thermal Sensation Scale (Brandemuehl, 2005) Zero is the ideal value, representing thermal neutrality. PPD is the predicted percentage of dissatisfied people exposed to a certain environment at each PMV . Fig. 1.1 shows an empirical relationship between the predicted percentage of dissatisfied (PPD) people with a thermal environment at each PMV . As PMV changes away from zero in either the positive or negative direction, PPD increases. (Brandemuehl, 2005) 9 Fig. 1.1 Percentage of People Dissatisfied (Brandemuehl, 2005) T he ‘ T he rm a l Co m fort T oo l ’ us e s the combinations of the six key factors, namely air temperature, mean radiant temperature (MRT), metabolic rate, clothing insulation, air speed and humidity to define thermal comfort for which the PMV is within the recommended limits (-0.5<PMV<+0.5). The MRT here is basically a measure of the average temperature of all the objects in a space, including the windows, walls, flooring, ceiling, furniture, people etc. It, along with the ambient dry air temperature, clothing insulation, air speed and humidity determines how thermally comfortable a space is. Fig. 1.2 shows t he s c re e ns hot of t he ‘T he r m a l Com fort T ool ’ de v e l op e d b y t he C B E for ASHRAE 55. After putting the values for each field, the tool does the arithmetic to determine thermal comfort based on the PMV/PPD model. 10 Fig. 1.2 Thermal Comfort Tool for ASHRAE-55 11 1.2.2 Tools and Methods used in Ronald Tutor Hall a) Site study, document analysis: Site study was conducted to see what kind of climate the site has, the orientation of the building being studied, amount of solar radiation each facade of the building receives, if sun shading was provided etc. as all these factors will be helpful in assessing the buildings performance. The architectural and construction drawings were obtained from USC facility management services which, together with the site survey were analyzed to check for any discrepancies such as a columns missing or windows not provided at the spot as documented in the drawing. b) Occupant survey: To assess the comfort of the occupants of the building it is important to survey the occupants and get a true gauge of buildings performance through their satisfaction. In this case survey was conducted by asking occupants, who were mostly students and some office staff, couple of questions such as their experience with temperature, air quality, noise and light levels inside the building. c) Data acquisition system (DAS): DAS was used to monitor, measure and analyze the temperature and relative humidity inside the RTH building to assess the indoor thermal comfort. It consists of data loggers to monitor & record the data and a software tool to analyze that data. The whole process is explained in detail in chapter 4. d) Current energy consumption data: To help proceed with post evaluation process it is important to know the energy usage of the building. The energy usage, which included 12 electricity and gas, was obtained from USC facility management services for the year 2008. Besides understanding the buildings energy consumption pattern, the energy usage data also helps in understanding the efficiency of the building by benchmarking as explained in the point below. e) Benchmarking tool: It is important to understand where the building being studied, stands in terms of energy use before we begin looking for strategies to improve the building energy performance. Benchmarking helps us to do that by comparing the particular building with buildings of similar type under the same climate zone. It tells us the energy consumed by the typical building of the type that is being studied and the range of energy that is being consumed by buildings which fall in that similar type. The kind of benchmarking tool used and its result are further explained in Chapter 2, section 2.10.2. f) Energy Consumption Simulation Model: With the advancement and proliferation of computers it has been possible to model the energy performance of an entire building or the systems within a building using computer based programs which provide us with valuable information such as building and system energy use as well as operating cost of the building. The important aspect of whole building simulation is that it takes into account the interaction between different elements of the building such as the impact of lighting, appliances, people on space conditioning loads or the impact of day lighting on electrical lighting loads. Energy modeling tools are now increasingly used to improve the energy performance of the building as well as reduced carbon emissions. Architects can 13 benefit a lot with the use of energy modeling tools as it will help them assess the impact of various design decisions they make. (The American Institute of Architects, 2009) 1.3 Benefits of Post Occupancy Evaluation (POE) The investigative part of POE helps in establishing the problem areas in the building. It enables understanding of building ’ s e ne r g y c ons um pt i on under different conditions such as different types of building envelopes, climates, systems, occupancy profile etc. This knowledge gained helps the designer in fine tuning the building so that the building performs at optimum level. It makes decision making easier as there is better understanding of the problem. There is also accountability that comes with adopting POE. Since POE helps in determining the quality of the building performance, the designers and engineers can be held accountable. Poor performance can be traced back to inappropriate design and/or construction. Future buildings can greatly benefit by adopting POE because lessons learned from past buildings of similar use and function can be used to improve the future buildings. POE also greatly benefits renovation of existing buildings as it helps understand the problem areas and is able to guide properly the necessary steps to be undertaken to improve the building performance. It helps to focus resources at the right place. The building can be adjusted to meet the changing practices, markets, social trends, codes and standards by identifying the change needed with the help of POE. It is also observed that due to involvement of the users of the building in defining how the building works for them, there is more interest and better response from the designers to find solutions to the problems affecting the building. POE helps identify 14 problem areas that lead to reduced building operating cost and maintenance. By helping users find ways to operate the building more efficiently energy, costs can be reduced. POE also helps eliminating design elements or systems affecting the performance of the building. (Post Occupancy Evaluation, 2011) 1.4 Drawbacks of Post Occupancy Evaluation (POE) It is widely accepted that POE has to be an important element of design process because it helps us learn from experience, past mistakes, helps in problem diagnosis and proper management of knowledge. However it has been observed that the early implementation of POE posed a few problems. During its early adoption the POE process was considered too costly. (CABE, 2011) The high costs associated with POE were due to unclear direction by the team implementing t he proc e s s . H i g h c os t s a re l e s s pre v a l e nt , now t ha t t he e v a l ua t ors a re c l e a re r a bout P O E ’ s role and goals. Professionals such as contractors, builders, Architects etc. also found POE to be risky and threatening. They were fearful that the results from a Post Occupancy study would lead to legal problems and create higher liability. With increase in knowledge and competencies the opposite seems more likely. Uncertain benefits were another issue. Building Owners did not see how having high performance buildings was beneficial since property values were largely driven by the location, appearance and other fe a t ure s o f t h e bui l di ng . T he m a rk e t pl a c e di dn’ t v a l u e t h e pe rfor m a n ce of the building. This however is changing now as there is more awareness about energy conservation and 15 high performing building. There is also the issue of unclear ownership. When problems are detected in the building, no one is willing to take responsibility, unclear duty of care adds to the problem. Lastly POE as a discipline has been having trouble being integrated in academics with only a handful of British schools of architecture that has POE in their syllabuses. (CABE, 2011) 1.5 Caltrans District 7 Headquarters Building: A Case Study on Post Occupancy Evaluation Fig. 1.1 North façade of Caltrans District 7 HQ, Downtown LA (http://www.flickr.com/photos/27966213@N08/3111771567/) The building is located in downtown Los Angeles. The gross area of the building is 594,000 ft 2 . Architectural firm Morphosis designed the building; MEP, façades and sustainability engineering work was handled by Arup Los Angeles. Construction type is steel frame construction. The construction work started in 2002 and ended in 2004. This 16 of fi c e bu i l di ng s e rv e s a s t he he a dqua rt e r s of Ca l i forni a ’ s D e pa rt m e nt of T ra ns por t a t i on. The building has 13 storeys with 10 storey office tower of 50,000 ft 2 rising from a 3 storey podium. There are four levels below grade. Parking is provided underground which has a capacity of 1,142 vehicles. (American-Architects, 2012) 1.5.1 Energy efficiency measures Several energy efficiency measures were incorporated in the building such as high performance glazing, daylighting controls, high efficiency chiller plant etc. Few distinguished measures are mentioned below a) Building Integrated Photovoltaic (BIPV) Fig 1.2 Photovoltaic panels on the south façade (http://morphopedia.com/projects/caltrans-district-7-headquarters) One of the great features of the Caltrans building is its electricity generating building 17 envelope. The bu i l di ng ’s south glass facade is entirely screened with building-integrated photovoltaic (BIPV) which also act as sun shading. The PV Panels generate a pproxi m a t e l y 5% of t he bui l d i ng ’ s e ne r gy , while providing shading to the facade from direct sunlight during peak summer hours without obstructing the view to the city. (Morphopedia, 2012) To get the maximum benefit out of the BIPV installation, the following points were looked into; • Angle of the panels for optimum power output • The vertical spacing between the panels to prevent self-shading • The optimum cell density in the panels to achieve the required output and maximize natural light in the offices • The positioning of the panels relative to each other in order to balance aesthetics with the occupant lines of sight. b) High performance building skin. The entire east and west façades are covered with perforated aluminum panels, or scrim which acts as a second exterior skin. Panels open and close mechanically timed with the movement of the sun and weather conditions, giving a dynamic effect to the facade, also shielding the interior from the sun. (Morphopedia, 2012). The scrim helps to reduce energy consumption, improve comfort and reduce infiltration. 18 Fig 1.3 Photovoltaic panels on the south façade (http://morphopedia.com/projects/caltrans-district-7-headquarters) 1.5.2 Post Occupancy Evaluation Results During a presentation given by an Arup employee, Shruti Kasrekar at USC in 2009, Caltrans 7 was presented as part of the case study. During this presentation, Shruti Kasrekar explained that in addition to meeting the mandatory California Title 24 energy compliance, energy efficiency target of 20% over Title 24 was set as a goal. Energy-pro (software developed by EnergySoft and approved by the California State to generate compliance simulation) was used for Title-24 energy modeling analysis. Table 1.1 shows Caltrans Energy-Pro Analysis Results which was obtained from Shruti K a s re ka r pre s e nt a t i on on “ Com put e r Energy Modeling tool ” . The analysis found that the proposed design achieved a 24% energy savings against Title-24-2001 and 44.26 % against ASHRAE 90.1-1999. 19 Energy By End Use Standard Design (kBtu/sqft-yr) Proposed Design (kBtu/sqft-yr) Compliance Margin Space Heating 10.10 7.02 3.08 Space Cooling 25.74 15.26 10.48 Indoor Fans 12.96 10.67 2.29 Heat rejection 8.74 8.27 0.47 Pumps & Misc. 20.07 5.85 14.23 Domestic Hot Water 3.77 3.23 0.53 Lighting 37.36 27.75 9.61 Receptacle 23.48 23.48 0.00 Process 22.54 22.54 0.00 Totals 164.76 124.07 40.68 Table 1.1 Caltrans Energy-Pro Analysis Results (From Ms S hrut i K a s re ka r “ Computer Energy Modeling Tool s ” USC, 2009 Presentation) Graph 1.5 below shows the comparison between the electrical consumption profile of old Caltrans 7 and the new Caltrans 7. As can be seen, there is substantial improvement in the electrical consumption between the old Caltrans Building and the new Caltrans 7 20 building. The various energy efficiency measures listed previously, and others, such as the use of daylighting controls, help explain the reduction in energy use. Fig. 1.5 Caltrans District 7 electrical consumption comparisons. (From Ms Shruti K a s re ka r “ Computer Energy Modeling Tool s ” U S C, 2009 P resentation) The red line denotes the typical base-year consumption of the old Caltrans 7 and the brown line denotes the consumption during the decommissioning of the old building in 2004, while the green line is the electrical consumption of the new Caltrans 7. This is the reason why the brown and the green line cross at the point at which the old building is completely decommissioned and the new Caltrans fully occupied. – the old building consumption in 2004/2005 drops as the building is decommissioned and occupants are transferred to the new building. As can be seen, the old Caltrans used 2.5 kwh/ft² on a typical year, whereas the new one consumes roughly 1 kWh/ft². Electrical Consumption Per Square Foot: Old vs. New DO 7 0.0000 0.5000 1.0000 1.5000 2.0000 2.5000 3.0000 Jan '04 Feb '04 Mar '04 Apr '04 May '04 Jun '04 Jul '04 Aug '04 Sep '04 Oct '04 Nov '04 Dec '04 Jan '05 Feb '05 Mar '05 Apr '05 May '05 Months Kilowat-hours Base Year (BY) 00/01 Old DO New DO 21 Chapter 2: USC Ronald Tutor Hall School of Engineering Fig 3.1 South East façade of Ronald Tutor Hall, USC, Los Angeles 2.1 Project background The Ronald Tutor Hall building houses research laboratories in three rapidly evolving fields: biomedical, information and nanotechnology. (Ainsworth, 2005) The table 2.1 shows the gross area breakdown of Ronald Tutor Hall. Gross Area Name Area Ist Floor 17,015 2nd Floor 15,838 3rd Floor 17,319 4th Floor 17,319 5th Floor 17,092 Basement 17,309 Roof 611 Total 102,503 Table 2.1 Area Distribution of RTH (from USC facility management services) 22 2.2 Building Site and Characteristics RTH is located in University of Southern California, Los Angeles. It is located at the junction of McClintock Ave. and Bloom walk. RTH current address is given as 3710 McClintock Ave, Los Angeles, CA-90089. The building is located at Latitude 34.019°, Longitude -118.288°, and Altitude 182ft above Sea Level. Fig. 2.2 RTH site context from Google Earth. The RTH building can be accessed from two corners, namely northeast corner from street Bloom Walk and northwest corner from street Mc Clintock Ave. The main entrance however is from the northeast corner. At the southwest corner is the outdoor cyber café which is landscaped by fountains, reflecting pool, large whitewashed rocks and is provided with chairs and tables shaded by umbrellas. The outdoor café helps build a sense of community among the students by giving them a common space to interact. RTH 23 building faces Olin Hall (OH) building on northeast, Hughes Aircraft electrical engineering center (HAEEC) on southwest, Seaver Science Center (SSC) building on southeast and Andrus gerontology center (AGC) on the northwest corner. Fig. 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10 shows the shadow pattern of the RTH building. The shadow analysis was done using Google Sketchup pro. From the analysis it was observed that North-East corner & South-East corner of the RTH building remain shaded most of the time because of its orientation whereas North-West corner & South-West corner received maximum amount of sunlight. However the surrounding buildings had no shading effect on the RTH building except for SSC building on the South-East corner of RTH building which casted its shadow on the RTH building during morning hour before 9am. Fig. 2.3 RTH shadow pattern at 7.00 am on North-East &South-East corner. 24 Fig. 2.4 RTH shadow pattern at 11.00 am on North-East & South-East corner Fig. 2.5 RTH shadow pattern at 1.00 pm on North-East & South-East corner 25 Fig. 2.6 RTH shadow pattern at 3.00 pm on North-East & South-East corner Fig. 2.7 RTH shadow pattern at 7.00 am on North-West & South-West corner 26 Fig. 2.8 RTH shadow pattern at 11.00 am on North-West & South-West corner Fig. 2.9 RTH shadow pattern at 1.00 pm on North-West & South-West corner 27 Fig. 2.10 RTH shadow pattern at 3.00 pm on North-West & South-West corner 28 2.3 Weather & Climate According to the Californian climate zone map provided by the California Energy Commission, RTH is located in Climate Zone 9 as shown in Figure 2.11. Zone 9 is classified as Southern California Inland valley and is influenced by both coastal and interior weather. Fig. 2.11 California building climate zone map (California Energy Commission, 2010) “ T he i nl a nd w i nds bri ng hot a nd dr y a i r a nd m a ri ne a i r bri ng s c ool a nd moist air. This area has as many HDD (heating degree days) as CDD (cooling degree days). Compared to the coast, summers are warmer and winters are cooler. Rain falls in the winter averaging around 2" per month between November and April. More than 50% of the time skies are clear or pa rt l y c l oud y .” (Pacific Gas and Electric Company, 2009) Below are charts from Pacific Gas and Electric Company which shows important factors of climate that can be taken into consideration while designing the building in the 29 particular zone. Figure 2.12 below illustrates the heating degree and cooling degree days of RTH building location. According to the chart there is clear indication that building constructed in this area will need almost same amount of heating and cooling in a year. Figure 2.13, 2.14, 2.15 and 2.16 shows the temperature for California Climate Zone 9, Relative humidity for California Climate Zone 9, Extra-terrestrial radiation for California Climate Zone 9 and Prevailing wind speed & direction for California Climate Zone 9 respectively. Fig. 2.12 Heating & cooling degree days of California Climate Zone 9. (Pacific Gas and Electric Company, 2009) 30 Temperature (Typical Comfort Zone: 68-80°F) Fig. 2.13 Temperature for California Climate Zone 9 (Pacific Gas and Electric Company, 2009) Relative Humidity (Typical Comfort Zone: 20-80%) Fig. 2.14 Relative humidity for California Climate Zone 9 (Pacific Gas and Electric Company, 2009) 31 Extra-Terrestrial Radiation Daily Mean ETR: 2699 Fig. 2.15 Extra-terrestrial radiation for California Climate Zone 9 (Pacific Gas and Electric Company, 2009 Wind Speed Prevailing Wind Direction; summer: NW ; Winter: NW Natural Ventilation is most effective when wind speed is 5 mph or greater. Fig. 2.16 Prevailing wind speed & direction for California Climate Zone 9 (Pacific Gas and Electric Company, 2009) 32 2.4 Design Strategies for California Climate Zone 9 Using the software Climate Consultant 5.1 downloaded free from the website http://www.energy-design-tools.aud.ucla.edu/ and California Climate zone 9 epw file, which is a weather file obtained from the website http://www.eere.energy.gov/ Fig 2.17 and Fig 2.18 were generated. In Fig 2.9, we can see that the cooling requirement in California climate zone 9 is relatively less as compared to the heating requirement because 74% of the time Los Angeles temperature is seen ranging between 32 – 70 degrees Fahrenheit and only 14% of the time the temperature goes above 75 degrees Fahrenheit. Fig. 2.17 Temperature for Climate zone 9 (generated from Climate Consultant 5.1) Fig. 2.14 below is a psychrometric chart used by climate consultant tool, along with the weather file to generate the design strategies for California Climate zone 9. The chart is a graphical representation of the relationship between air, temperature and humidity which 33 helps in describing the climate data and the human thermal comfort conditions. (Bhattacharya, Milne, 2009) Fig. 2.18 Design strategies for Climate zone 9 (generated from Climate Consultant 5.1) Thirteen design strategies are listed for zone 9 with number of hours and the percentage of time that falls within each strategy range. Approximately 6.5% of the hours in a year fall under the acceptable comfort range. The best single cooling design strategy is Sun Shading – sun shading can help increase hours under the comfort range by over 21%. This strategy can be combined with all the other cooling strategies listed for more effectiveness. The next most effective cooling strategy is high thermal mass which accounts for 11.9% of the hours but when this is combined with night flushing through natural ventilation or adding a whole house fan, only a gain of 1.9% is observed. Los 34 Angeles is relatively dry during the summer and therefore the other important strategy for cooling is direct evaporative cooling which accounts for 8.7% of the hours. For rest of the hours, Conventional Air Conditioning must be used for cooling. When it comes to heating for California Climate Zone 9, 31.9% of the hour in a year is under comfortable range. Passive Solar Direct Gain with High Mass could add an additional 21.2% of the hours, but if the building was Low Mass then Passive Solar Direct Gain could create comfort conditions for only about 14% of the hours. The relative humidity level for California climate zone 9 is little bit low during winter which can cause mucus and dry skin condition and that is why some sort of humidification is needed which will add an additional 14.9% hour to the comfort range. However most common human activities like cooking, bathing, washing clothes add moisture to the air and so humidification is not a major concern in modern well building. Strong winds are rare in this climate zone but do occur once a while and therefore adding wind protection would give an additional 0.5% to the comfort hour. Given the climate conditions it becomes absolute necessary to have conventional heating for 29.2% of the hour per year. (Milne, Liggett, and Rashed Al- Shaali, 2007) 35 2.5 Building Plans The buildings plans are provided below with legend. Fig. 2.19 Basement Plan of RTH (AutoCAD plan from A.C Martin & Partners) Fig. 2.20 Ground Floor Plan of RTH (AutoCAD plan from A.C Martin & Partners) 36 Fig. 2.21 Second Floor Plan of RTH (AutoCAD plan from A.C Martin & Partners) Fig. 2.22 Third Floor Plan of RTH (AutoCAD plan from A.C Martin & Partners) 37 Fig. 2.23 Fourth Floor Plan of RTH (AutoCAD plan from A.C Martin & Partners) Fig. 2.24 Fifth Floor Plan of RTH (AutoCAD plan from A.C Martin & Partners) 38 Fig. 2.25 Roof Plan of RTH (AutoCAD plan from A.C Martin & Partners) 39 2.6 Occupancy zoning profile of Ronald Tutor Hall Fig. 2.26 Occupancy zoning of Ronald Tutor Hall Space Area(sq.ft) Non toxic Lab. 22027.00 Circulation 18143.00 Toxic Lab. 16400.48 Office 11439.33 Services 5617.16 Staircase & Lift 4438.38 Classroom 4100.00 Toilet 3362.00 Conference 2900.83 Dining 2480.57 Lounge & study 1896.31 Comp. & Server 769.00 Seminar 717.52 Museum 522.77 Other 7689.00 Table 2.2 Occupancy zoning of Ronald Tutor Hall Non toxic Lab. 21% Circulation 18% Toxic Lab. 16% Office 11% Services 5% Staircase & Lift 4% Classroom 4% Toilet 3% Conference 3% Dining 2% Lounge & study 2% Comp. & Server 1% Seminar 1% Museum 1% Other 8% Occupancy Zoning 40 Fig. 2.26 shows the Occupancy zoning of RTH building with all the spaces categorized according to the activity of that space. The percentage number refers to amount of space each activity occupies with respect to the gross building area. This calculation was done based on AutoCAD plans of RTH provided by USC facility management services. This zoning chart was necessary to understand the energy end-use profile of RTH. It was done to see which activity occupies the maximum space with respect to the whole building space. This way we can see which building activities take the maximum conditioning space and thus look for problems and improvement in those areas. From the above process we saw that the primary space usage of Ronald Tutor hall were divided into following categories; Non toxic lab, Circulation, Toxic lab, Office, Services, Staircase & Lift, Classroom, Toilet, Conference, Dining, Lounge & Study, Comp. & Server, Seminar, Museum and other. The toxic laboratory space has been given special mechanical design considerations because of possible hazards due to use of dangerous chemical in these spaces with potential to produce extensive fumes and cause fire. To protect the space from these hazards, following measures were taken; It is supplied with 100% outside air and there is no return air, so the ductwork is simpler, thus reducing the total static pressure. It is being conditioned 24 hours a day. It is maintained under negative pressure with respect to the adjacent spaces by keeping supply air 90-95% of the exhaust air volume so that incase of accident, 41 the harmful fumes does not spread throughout the building. VA V fume hoods with zone presence sensors and air valves are provided for quick removal of fumes incase of accidents. Three Variable Air V olume (V A V) Make up Air unit (MAU) Air Handling Unit are being used specifically to serve the lab space to have better independent control of the space. From Fig. 2.22 Non toxic Lab. room occupies the largest area of the building followed by the circulation space and toxic lab space. By adequately designing the system serving the lab spaces would ensure energy savings for the building. 2.7 Hours of Operation and Mechanical Systems Schedule Since Ronald Tutor Hall Building is a facility that should allow staff 24-hour availability to laboratories, the HVAC systems in the laboratories are designed to run 24/7. The systems serving the laboratories were designed to allow normal maintenance without shutting down the complete system. The classrooms and offices are considered 8am to 9pm operation and were designed to shutdown outside these hours. The mechanical planning of the building was handled by IBE Consulting engineers. The report ‘P roj e c t de s c ri p t i on a nd re qu i re m e n t s , 2002’ by IBE consulting engineers as design criteria for Ronald Tutor Hall does not mention operating hours for corridor spaces but based on actual visit to the site, it was found that corridor spaces are conditioned for 24 hours, 7 days a week. 42 B a s e d on re port ‘P roj e c t d e s c ri pt i on a nd re qui re m e nt s ’ from IBE consulting engineers, information on USC website for schedule of classes and actual visit to the building, the table 2.2 below was prepared. Table 2.2 Operating hours per day of the main activity area in Ronald Tutor Hall Spring & Fall Summer Winter & Spring Unit: Hrs/Day M-F Weekend M-F Weekend M-F Weekend Classroom 8am to 9pm 0 8am to 9pm 0 8am to 9pm 0 Office 8am to 5pm 0 8am to 5pm 0 8am to 5pm 0 Lab 24 24 24 24 24 24 Corridor 24 24 24 24 24 24 A s pe r IB E Cons ul t i ng E ng i ne e r ’ s re port ‘P roj e c t d e s c ri pt i on a nd re qu i re m e nt s ’, g e ne ra l controls for the RTH building were proposed as such; A modular direct digital control (DDC) system shall be provided for the HVAC system. Stand-alone modules shall control air handlers, pumps, etc. A common data highway shall link the modular controllers. Valve and damper actuators shall be electronic. A central personal computer and printer in the building will be provided. Full color graphics, monitoring, trending, set point, and sequence modification shall be available at the building and at the campus facilities offices. The system shall be capable of transferring data to and from the campus control system. Thermostats for terminal units, reheat coils and air valves be wall mounted. All control components shall be electronic. DDC system shall also be used for alarms for cold rooms, emergency generator, smoke detectors, vacuum pump, compressed air, etc. A flow meter in the steam condensate return piping shall be provided, in the building mechanical room prior to water return piping exiting the project. The control system shall be Honeywell to match the Campus requirements (IBE, 2002) 43 No pressurization schedule for the RTH building could be found in the IBE report or other documents obtained from the IBE Consulting Engineers and University facility management services. 2.8 Internal Heat Gain Profile of Ronald Tutor Hall Apart from external heat gain from solar radiation, conduction and convection, internal he a t g a i n a c c ount s for s i g ni fi c a nt l oa ds c ont ri but i ng t o t he bui l d i ng ’ s s pa c e c oo l i n g . T he most common sources of internal heat gain are electronic devices, appliances and lighting. People also add to internal heat gain but the amount varies depending on the function of the space occupied and the activity level of the occupants in these spaces. For instance, in an auditorium people may be the primary source of heat gain, due to its high occupancy density when fully occupied. To reduce the load from internal heat gain, it is important to use energy efficient equipment, appliances and lighting which waste less energy and emits less heat thus reducing internal heat gain. It was difficult to form the Ronald Tutor Hall internal heat gain profile as important information such as lighting and the appliances schedule could not be obtained. However, there is a report from IBE consulting engineers, which lists the design criteria for internal heat gain for RTH. Below are the tables that have been taken from the IBE report. These t a bl e s ha v e be e n t a ke n di r e c t l y from t he e ng i ne e r ’ s m e c h a ni c a l re por t a dd ed with comparison table. Due to lack of actual data these values were used for building the energy model. 44 Table 2.3 below shows the design criteria for sizing the HVAC system which was based on ASHRAE Handbook - Fundamentals, 1993. ASHRAE stands for American Society of Heating, Refrigerating and Air-Conditioning Engineers. It is an influential international organization with more than 50,000 members from all across the world and focus on building systems, energy efficiency, indoor air quality and sustainability within the industry. (http://www.ashrae.org/about-ashrae/) Space Basis Heat gain sensible./latent Laboratories 30 ft 2 /person 250/250 Btuh Lab Support 100 ft 2 /person 250/250 Btuh Meeting Rooms, Conference Rooms 20 ft 2 /person 250/200 Btuh Open Plan Offices 100 ft 2 /person 250/200 Btuh Individual Offices 1 person 250/200 Btuh Lobbies, foyers, corridors 200 ft 2 /person 245/200 Btuh Classrooms, Lecture Halls, 20 ft 2 /person or number of fixed seating 250/200 Btuh Table 2.3 Occupant heat gain (IBE, 2002) Table 2.4 below on which Table 2.3 is based shows representative rates at which heat and moisture are given off by human beings in different states of activity. Table 2.4 Occupant heat gain (ASHRAE 55-2004, 2004) 45 Table 2.5 shows the designed Lighting Power Density (LPD) for different areas in RTH which was based on lighting plans obtained from USC facility management services. The designed LPD is compared with the space-by space method of ASHRAE 90.1-2004. The LPD of different areas in RTH could not be verified by physical walk through survey as the permission to do so was denied for security reasons. Space Lighting load (Watts/ ft²) Title 24, 2001 (Watts/ ft²) ASHRAE 90.1-2004 (Watts/ ft²) Laboratories 2 1.8 1.4 Lab Support 2 1.8 1.4 Meeting Rooms, Conference Rooms 1.3 1.5 1.3 Offices 1.3 1.3 1.1 Lobbies, foyers, corridors 1 1.5 0.5 Classrooms, Lecture Halls, Auditorium 1.3 2 1.4 Table 2.5 Internal heat gain through Lighting Loads As seen from Table 2.5 Ron a l d T ut or H a l l ’s L i g ht i ng P o w e r D e ns i t y i s be t t e r for m o s t spaces when compared to Title 24, 2001 but does not quite meet the requirement when compared to ASHRAE 90.1-2004 standard and hence there is room for improvement. 46 Table 2.6 below shows the heat gain due to miscellaneous i t e m s a s pe r re port ‘P roj e c t de s c ri pt i on a nd re qui re m e nt s , 2002’ by IBE consulting engineers. Space Miscellaneous % Gain to return/exhaust air Laboratories 10.0 Watts/ ft² 0 Lab Support 20.0 Watts/ ft² 0 Meeting Rooms, Conference Rooms 1.0 Watts/ ft² 0 Offices 1.0 Watts/ ft² 0 Individual Enclosed Offices 2.5 Watts/ ft² Lobbies, foyers, corridors 0.5 Watts/ ft² 0 Classrooms, Lecture Halls, 1.0 Watts/ ft² 0 Information Technology Suite 25.0 Watts/ ft² 0 Table 2.6 Internal heat gain through miscellaneous items (IBE, 2002) 47 2.9 Mechanical System As per the ‘Ca l i forn i a E ne r gy Com m i s s i on ’, m echanical systems are said to be the second largest consumer of energy in most buildings with lighting taking the first spot. Fans and cooling equipments are thought to be the largest consumer of energy for most buildings in non-mountainous California climates followed by space heating and service water heating. Fig. 2.27 Typical building electricity use (CEC, 2008) 48 2.9.1 HV AC system of Ronald Tutor Hall Chilled water and low pressure steam are supplied from a centralized Campus distribution system Heating hot water is produced from instantaneous low pressure steam heat exchangers and is supplied with the help of Heating Hot Water Pump (HHWP) to ensure quick supply. The system is located in the basement mechanical room. Campus low-pressure steam is utilized to generate the heating hot water. Separate Air Handling Unit (AHU) are provided for Classrooms, offices & Laboratories 2.9.2 Air Handling Unit (AHU): Fig. 2.28 Schematic AHU (http://blt.colorado.edu/html/bld_comps/ahu.html#specs) An Air Handling Unit (AHU) is part of a Heating, Ventilating and Air Conditioning (HVAC) system. It is composed of several integrated pieces of equipment consisting of 49 air control dampers, heating & cooling coils, sound attenuators, filter racks and blowers. Fig 2.28 shows how an AHU works in general. In some cases outdoor and return air are mixed and filtered to make the air suitable for supply to the occupants of the building. The filtered air is than heated or cooled as per the need and the conditioned air is then supplied to the building by means of ductwork. Some AHUs only condition outside air and not the re-circulated air from the building, such AHUs are called make up air unit (MAU) (Curtiss and Breth, 2002), 100% Outside Air Units are being used to condition the laboratory space in the RTH building. Due to the possible hazards, recirculation of air is undesirable at these locations. Figure 2.29 shows the kind of Air Handling unit that are installed in RTH. The product line is called Custom-Air line and it was developed by United Metal Products. Fig. 2.29 Air Handling Unit type in Ronald Tutor Hall (http://www.unitedmetal.com/our-products/custom-air/ ) Variable Air V olume (VA V) AHU systems are used in the RTH building because VA V systems are more appropriate for a building where variance in occupancy among various zones is expected. V A V fans are supplied with variable speed controls thus allowing for 50 the system to adjust supply air volume according to demand in the zones. (Curtiss and Breth, 2002). VAV systems typically send either cold or hot air through the system and thus avoid the mixing of cooled and heated air. As per the HVAC report, for classroom and offices, Variable Air Volume (VAV) boxes with terminal reheat are provided for each 600 ft 2 at the perimeter and 1,000 ft 2 in the interior of the building. Also a VAV box is provided for corner offices, classrooms and conference rooms. As for the laboratories, each lab module is provided with Supply Air Valve (SAV) connected with reheat coil along with supply air diffusers, exhaust grilles, general exhaust air valve and fume hood exhaust air valves. There are a total of five Air Handling Units in Ronald Tutor Hall. A description for each of the Air Handling Unit is given in the table below along with the spaces it serves. AIR HANDLING UNIT LOC- ATION AREA SERVED SUPPLY UNIT CFM RETURN FAN UNIT CFM COOLIN G COIL PRE- HEAT COIL MINIMUM OUTSIDE AIR CFM AHU-1 ROOF 1st - 5th floor offices 41,600 30,380 Yes No 9,285 AHU-2 ROOF Class 10,000 clean room & Lab in Baseme nt 31,840 NA Yes Yes 100% AHU-3 ROOF Class 1000 clean room 28,200 NA Yes Yes 100% AHU-4 ROOF 5th floor Lab 32,560 NA Yes Yes 100% AHU-5 ROOF 1st - 5th floor offices 52,740 51,890 Yes No 10,300 Table: 2.7 Ronald Tutor Hall AHU descriptions (from USC Facility management services) 51 2.9.3 Fan Coil Unit (FCU) The Fan coil units in RTH are only used for cooling. Most of the FCU ’s in RTH are located next to the area they are serving to simplify the duct work. In areas with adequate space such as the B a s e m e nt m e c ha n i c a l a nd e l e c t r i c a l room , t he F CU ’ s a re l oc a t e d i ns i de the space they are s e rv i ng . A l l t he F CU ’ s i n R T H a re c e i l i ng m ou nt e d. F CU ’ s a re much cheaper than AHU ’ s but noi s i e r because of their e l e c t ri c m ot or fa ns . T he y ’re preferred for conditioning service areas such as an electrical room or mechanical room as these spaces gain lot of heat because of the equipment in them and they need continuous conditioning. Also the noise from FCU makes them better suited for service areas. The Fan coil Unit installed in Ronald Tutor hall is manufactured by DA TA AIRE INC. The figure below shows the kind of Fan Coil Unit installed in Ronald Tutor Hall. Fig: 2.30 Fan coil Unit type in Ronald Tutor Hall ( http://www.dataaire.com/inside.cfm?p=floor&c=4 ) The table 2.8 list the number of Fan Coil Units installed in Ronald Tutor Hall along with its description and the area it serves. 52 FAN COIL UNIT LOCATI- ON AREA SERVED SUPPLY FAN MAX. CFM COOLING COIL TOTAL (BTU/HR) COOLING COIL SENSIBLE (BTU/HR) FILTER EFFICIENCY (%) FCU/ B-1 BASEMEN T ELECT. ROOM BASEMENT ELEC. ROOM 2,500 86,100 63700 30 FCU/ B-2 BASEMEN T MECH. ROOM BASEMENT MECH. ROOM 1,225 33900 26600 30 FCU/ G-1 & FCU/ G-2 HALLWAY # 133 ELEC. TEL/DATA #134 #132 550 12500 11000 30 FCU/2 -1 & FCU/2 -2 HALLWAY # 203 ELEC. TEL/DATA #248 #219 550 12500 11000 30 FCU/3 -1 & FCU/3 -2 CORR. TEL/DATA #304 #324 ELEC. / LOUNG. #332 #305 550 12500 11000 30 FCU/4 -1 & FCU/4 -2 CORR. TEL/DATA #404 #424 ELEC. / LOUNG. #432 #405 550 12500 11000 30 FCU/5 -1 & FCU/5 -2 CORR. TEL/DATA #404 #522 ELEC. / GLASS. #524 #515 550 12500 11000 30 FCU/ R1 DUCT SHAFT ENCLOSU RE ON ROOF ELEVATOR MACHINE ROOM 2,500 86100 63700 30 Table 2.8 RTH fan coil unit descriptions (from USC Facility management services) In table 2.7 the basement and ground floor is designated as B & G and second, third, fourth and fifth floor is designated as 2, 3, 4 and 5 respectively. From the table one can see that there are two FCU in each floor serving areas such as mechanical room, electrical room, telecomm. & data room etc. There is also one FCU located on duct shaft enclosure on roof which serves the elevator machine room. 53 2.10 Ronald Tutor Hall energy consumption profile In addition to identifying the different factors that may affect the energy consumption of the building such as building envelope, internal heat gain, user occupancy profile, HVAC systems etc this study also looked at the actual energy consumed by checking electric and gas bills for the entire year of 2008, the graph for which is provided at the section 2.10.1- Current Ronald Tutor Hall Energy consumption data To start the energy modeling process it is essential to first decide the tool which would be used to do the energy modeling. In this case eQUEST was used. The reason for using eQUEST is explained in chapter 3, section 3.1.3 - Energy Consumption Simulation Model. Using the development design wizard in eQUEST and by inputting all the information required such as the type of the building, location of the building, number of floors, area of the building, U and R value of building envelopes, the system type etc. energy model for RTH was created. The simulated result of a building from different building energy modeling tools may show different energy consumption profiles based on how each tool is programmed and so it becomes all the more important to have the actual energy consumption of the building. This way comparison can be made between actual and simulated energy consumption profile and thus model can be calibrated to behave as the actual building. Unable to gather data from previous years, du e t o t he U ni v e rs i t y ’ s P rivacy Policy I was able to obtain the electricity and gas consumption for the year 2008 from Mr. Victor 54 Aspurez who works at U ni v e rs i t y ’ s Facility Management Services after persistent requests. This data helped in comparing my simulated model to the actual energy consumption profile. It also helped in benchmarking the energy consumption of Ronald Tutor Hall against other buildings of the same type and under the same weather conditions. The tool used for benchmarking is called EnergyIQ which is sponsored by California Energy Commission's Public Interest Energy Research (PIER). The benchmarking of RTH and the way it works is discussed in detail in section 2.10.2 - Benchmarking the Energy Consumption of Ronald Tutor Hall with Energy IQ. 2.10.1 Current Ronald Tutor Hall Energy Consumption Data USC facility management services (FMS) was approached for the RTH energy usage data for the year 2008. Electricity & Gas usage data was provided in excel file. During the simulation process, which is discussed in chapter 5, it was observed that the simulation result showed a very different energy usage pattern than the data provided. To verify the historical energy usage data provided, FMS was approached again but this time the meeting was with the director of energy services at FMS. It was learned that not only the historical electricity consumption varied from the initial data provided, the gas usage record as shown in the initial data did not exist. There was no gas consumption for RTH and the heating hot water came from the campus steam system. The historical electricity usage data provided included loads from lightings, equipments, pumps and fans and did not include loads from chiller, cooling tower and boiler as these items did not exist in the building. Fig. 2.27 shows the historical electricity usage of RTH for the year 2008. 55 Fig 2.31 Ronald Tutor Hall energy Consumption chart for year 2008 From Fig. 2.31 one can see that the electricity usage is lowest for summer months and higher for fall and spring months. This is possibly because fall and spring months have more activities happening in terms of classes and conferences held. The electricity usage for the whole year as such is fairly constant with a maximum variation of only 20 MWH except for the month of October. The RTH building is primarily an internally dominated building. In other words, cooling of the building is driven by lab equipments, office equipments, lighting, ventilation etc. and not on the weather. Ronald Tutor Hall is a building of research facilities and so it has a great deal of equipment for research purposes. Since the equipment, lighting and ventilation requirement in the building is almost constant throughout the year, this makes the electricity usage fairly constant throughout the year. 240 260 280 300 320 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Actual Electricity (MWH) Actu al Ele … 56 2.10.2 Benchmarking the Energy Consumption of Ronald Tutor Hall with Energy IQ EnergyIQ tool was used for benchmarking RTH energy performance. It is a non- residential energy benchmarking tool developed by U.S. Department of Energy's Lawrence Berkeley National Laboratory (LBNL) and is sponsored by California Energy Commission's Public Interest Energy Research (PIER) program. (Energy IQ, 2011). It helps in benchmarking by comparing the particular building with the energy performance of the buildings of the same type located in the same region. EnergyIQ has been chosen as a benchmarking tool because it is based solely on California data unlike numerous other benchmarking tools which include national averages making it significantly more difficult to navigate the data. The tool is still under de v e l opm e nt a nd c urre n t l y onl y t he b e nc hm a rk i ng fe a t ure i s a v a i l a bl e a m on g i t ’ s numerous other feature. The tool lets you fill in the location, type of the building, the area etc. to create a peer group which can then be used to compare with your own building to see where it stands in terms of energy consumption. There is a separate section to fill in information for your building where you can fill in the amount of energy consumed, the period when the energy was consumed etc among other general details. 57 To begin the Benchmarking, the following data was fed into the EnergyIQ tool; Building Type: Lab/R&D Facility Vintage: 1991 through Present Building Location: California South Coast Building Size: 25,001 - 150,000 ft 2 Data sets: California only (CEUS) Total Electricity – 3547247 kWh/yr Total Gas - 6628226.5 kBTU/yr Gross Area – 102503 ft 2 Fig 2.32 below shows the graph generated from EnergyIQ tool with summary on the side, showing electricity usage comparison with 14 buildings of similar type in the South coast, California. Fig 2.32 RTH electricity usage comparison with South Coast California buildings. (Energy IQ, 2011) From the graph we can see that the RTH building consumes 118.1 kBTU/sf-yr whereas the energy consumed typically by buildings of the same type is 46.5 kBTU/sf-yr as mentioned in the summary with the electricity usage ranging from 42.5 kBTU/sf-yr to 261.8 kBTU/sf-yr. The RTH building is placed at 85 th percentile in the graph which 58 means that 85% of the buildings use less t ot a l e l e c t r i c i t y t ha n R T H , t ha t ’ s a pprox imately 12 buildings out of 14 which are better than RTH building. From the above result from the EnergyIQ tool, it is clear that either there is an unusually high equipment usage or there is lot of work to be done to make RTH energy efficient as it fares very badly in its energy usage. 2.11 Ronald Tutor Hall Building Envelope Profile Quoting Yogesh Seth an Architect with A.C Martin partners “ W e w a nt e d t o c re a t e a v i bra nt e nv i ronm e nt t ha t c om pl e m e nt e d s urroundi ng buildings but encouraged a great deal of interaction, the open-air courtyard spills into the lobby to facilitate chance meetings, interactivity and a collaborative atmosphere for the whole engineering c om m uni t y .” ( A i ns w ort h, 2005) Quoting Dwight C "Jim" Baum, chairman of the Viterbi School Board of Councilors “ T ut or H a l l i s a pl a c e for s t ude nt s t o c om e t og e t he r t o re l a x, t o s oc i a l i z e , t o g ra b a bi t e , p l ug i n t he i r l a p t ops a nd, m o s t i m port a nt l y , be c om e a c om m uni t y ” (Ainsworth, 2005) From the report ‘P roj e c t d e s c ri pt i on a nd r e qui re m e nt s , 2002 ’ obtained by IBE consulting engineers, it was learned that the RTH building envelope has been designed to exceed the requirements of June 1st, 2001 California Energy Code for minimum thickness of roof and wall insulation. As for the glazing, the entire exterior glazing type in the RTH building is double pane Low-E with SHGC value of 0.40 and U-factor of 0.69 which meets the Title 24 2001 requirement. The RTH building has no external shading to minimize the effects of solar radiation on 59 the building interior. Internal blinds are only provided to the office spaces. The RTH wall envelope consists of pattern with brick and stone veneer which are hooked to a furred wall. The furred wall is composed of batt insulation with R11, at the exterior wall of metal stud and gypsum board. T he t ot a l t h i c kne s s of w a l l i s 10 1/ 2” t hi c k. Fig. 2.33 South west façade of Ronald Tutor Hall On places where windows occur, there is aluminum storefront with double pane Low E glass. The top of the window has a custom extruded aluminum mullion cap which proj e c t s by 6” a nd a c t s a s prot e c t i on fro m w a t e r a nd g i v e s some help in shading as seen on Fig. 2.33 and the detail section on Fig 2.37. Adding to the wall envelope are the vertical blinds which helps in cutting down excess light when used thus providing visual comfort, it also provides thermal comfort by preventing direct exposure to solar radiation. 60 Fig. 2.34 North-East & North-West façade of RTH Fig. 2.35 North-West & South-West facade of RTH 61 Fig. 2.36 South-West & South-East façade of RTH T he roof e nv e l ope c a n b e s e e n prop e rl y d e t a i l e d i n F i g . 2.30 be l ow . T he roof s l a b i s of 8” concrete a nd xxx” of rigid insulation covered by modified bitumen roof. The floor slab is a l s o of 8” t hi c k c onc re t e . T he c e i l i ng be l o w the floor slab is either suspended gypsum board ceiling or suspended T bar grid ceiling depending on the location. The corridor has suspended T bar grid ceiling. From Fig.2.34, 2.35 & 2.36, it can be seen the typical wall detail of Ronald Tutor Hall. The wall is primarily composed of metal stud and gypsum board cladded with brick and stone veneer. Punched in windows or store-front areas are composed of fixed aluminum framed double pane units with clear glass and Solarban 60 low-e coating. 62 Fig. 2.37 Exterior wall section of RTH ((from USC Facility management services) Legend 2 1/2" glass matt gypsum sheathing 4 Batt Insulation 7 Modified Bitumen Roof 8 Rigid Insulation 9 Aluminum Coping 18 Gypsum board 19 Treated wood nailer 21 Shim as Required 22 sealant & backer rod 24 4" cant strip 25 drip 26 6 x 16" Galvanized metal studs @ 12" O.C TYP. U.N.O 32 Architectural concrete 34 Aluminum flashing 37 Aluminum storefront 46 Stone veneer 53 3/8" dia X 2 1/2 embedded hilti KB11 @ 12" O.C 57 concrete 61 steel tube frame 84 weather resistant barrier 85 Custom extruded aluminum mullion cap. 86 weep vents @ 24" O.C 63 T he w a l l be l ow g ra de i s 12” Con c re t e w a l l . A s pe r t he T i t l e 24 prescriptive compliance report for the Ronald Tutor Hall obtained from IBE Consulting Engineers, window area covers 27.30 % of total wall area. Fig. 2.38 Window sill at Stone wall detail (from USC Facility management services) Legend 2 1/2" glass matt gypsum sheathing 4 Batt Insulation 18 Gypsum board 22 sealant & backer rod 25 drip 26 6 x 16" Galvanized metal studs @ 12" O.C TYP. U.N.O 31 0.145 dia - 1 1/8"EMB Powder actuated fastener @ 6" O.C 32 Architectural concrete 34 Aluminum flashing 37 Aluminum storefront 46 stone veneer 61 steel tube frame 79 Aluminum gypsum board receiver 84 weather resistant barrier 86 weep vents @ 24" O.C 64 Fig. 2.39 North East wall entry soffit view Fig. 2.40 North East wall entry soffit section detail (from USC Facility management services) 65 Legend 1 Brick 2 1/2" glass matt gypsum sheathing 4 Batt Insulation 13 Alum. & Glass Curtain wall 18 Gypsum board 20 Stainless steel flashing 21 Shim as Required 22 sealant & backer rod 23 4"x16 GA. MTL Stud used as DIAG. bracing @ 24" O.C 26 6 x 16" Galvanized metal studs @ 12" O.C TYP. U.N.O 53 3/8" dia X 2 1/2 embedded hilti KB11 @ 12" O.C 54 5 - #10-16 self tapping screw 55 Firestop 57 Concrete 58 L/4X4X3/8"Angle w/min. 6" bearing at each end. 62 Fleming Brick Veneer Anchors spaced @ 12" O.C Horiz. And 16" O.C Vert. 84 weather resistant barrier 86 weep vents @ 24" O.C Fig 2.40 shows the detail section of the soffit at the main entrance of the RTH building which is from the North-East corner and the elevation of it can be seen on Fig. 2.39 66 Fig. 2.41 Second floor terrace section detail (detail from A.C Martin partners) 67 Legend 1 Brick 4 Batt Insulation 10 Thinset Stone 11 Waterproof Membrane 12 Compressible filler & Sealant 18 Gypsum board 20 Stainless steel flashing 21 Shim as Required 22 sealant & backer rod 23 4"x16 GA. MTL Stud used as DIAG. bracing @ 24" O.C 31 0.145 DIA - 1 1/8" EMB Powder actuated fastener @ 6" O.C 32 Architectural Concrete 35 Round Chamfer 36 STL. Handrail/Guardrail 37 Alum. Storefront 39 Floor Drain 44 Furred Wall 4"x20 GA. MTL Studs @ 16" O.C & 5/8" gyp. Board on one side 52 Alum. Channel to match curtain wall 54 5 - #10-16 self tapping screw 56 Dovetail brick veneer concrete anchor 12" O.C Horiz. 16" O.C Vert. 58 L/4X4X3/8"Angle w/min. 6" bearing at each end. 80 L 3"X3"X3/8"w/1/2" diax6" LG Welded Studs @ 1"-4" O.C Max. Table 2.9a & 2.9b below l i s t s t h e s um m a r y of Rona l d T ut or H a l l ’s e nv e l ope pro pe rt ies and compares those values to the standard value as defined in ASHRAE 90.1-2004. The U, R & SHGC value of the Ronald Tutor Hall were obtained from the Title 24 prescriptive compliance report from the IBE Consulting Engineers. It might seem inappropriate to compare the Rona l d T u t or H a l l ’s existing envelope with the relatively new ASHRAE standards as opposed to the standards used at the time of construction; however such comparison can aid in the revelation of the current situation of the building and assist the subsequent retrofits. From table 2.9a & 2.9b we can see that the RTH 68 envelope properties satisfactorily complies with Title 24, 2001 as the RTH was designed to meet the Title 24 code in its design phase but when compared with ASHRAE 90.1- 2004 which is newer and stricter code, RTH fails to comply. Type Ronald Tutor Hall Title 24, 2001 ASHRAE Standard 90.1-2004 Climate Zone 3B U- Value Insulation R-Value U factor R value Max U- Value Insulation Min. R- value Roof 0.075 13.30 0.078 11 0.063 15 Wall above grade 0.205 11 0.189 11 0.124 13 Wall below grade 0.262 NR NR NR 1.140 NR Table 2.9a Envelope profile of RTH Ronald Tutor Hall Title 24, 2001 ASHRAE Standard 90.1-2004 Climate Zone 3B Window Window Window U-Value SHGC Max U-factor Max SHGC Max U-Value Max SHGC 0.69 0.4 0.81 0.61 0.57 0.25 Table 2.9b Envelope profile of RTH From the shadow analysis done using Google sketch up pro as discussed in section 2.2 - Building Site and Characteristics and the survey of the site, it was observed that RTH receives a lot of solar radiation on its northwest and southwest surfaces and these surfaces also have large areas under glazing. There is no solar shading provided for these surfaces. Solar shading can be examined for these surfaces to check if it helps in reducing the heat gain from these surfaces so that it reduces the cooling load in the spaces that have these surfaces as part of their wall. 69 Chapter 3: Research Background, Procedure & Methodology The objective of the research is to suggest strategies which can be implemented in the RTH building to make it efficient in its energy consumption. To achieve that, a post occupancy evaluation process was carried out. To proceed with the post occupancy evaluation process, background research was conducted which separated the entire research work into four main categories. 3.1 Background Research In order to proceed with post occupancy energy evaluation of Ronald Tutor Hall, the research has been broken down into four main categories listed below: Fig 3.1 Research flowchart 70 3.1.1 Groundwork Research During this first stage, information that is needed to start the evaluation process was gathered. The information collected included Architectural drawings, mechanical drawings, energy bills for the year 2008, chilled water usage data and building operation schedules. This stage also involved numerous visits to the building to experience the environment inside as well as to inspect whichever area was accessible. The climatic condition of the site was also studied which is covered in chapter 2. The building occupants were asked about their comfort inside the building, questions such as, if it is too noisy, too dark, too hot or too cold were asked to the users of the building. To better manage the groundwork research, the process was broken down to four sub categories listed below. a) Occupancy user profile: This step deals with understanding the zoning of the building in terms of space allotted for different activities. The architectural plans received from the USC facility management services was referred to create a chart that gives the percentage of space each activity, such as dining, corridor, restroom etc. occupies in the building. This step was necessary as it makes clear the activities that occupy the maximum and minimum space in the building. Once the zones are broken down it is easier to comprehend the demand on the system that serves that particular activity area. Naturally the system serving the activity with largest area would have more demand on its load. b) Building Envelope profile: Building envelope is an important element to consider in 71 the energy efficient design as it helps to maintain the indoor environment together with the mechanical system. Foundation, roof, walls, doors and windows form the physical component of the envelope. For the post evaluation study it was necessary to create envelope profile of the RTH inorder to assess the efficiency of the envelope. The construction drawings were referred to create this profile. Important material property values that could be gathered from the construction drawings were R value, U value, SHGC which are necessary in determining the effectiveness of the envelope. These values were put in table and compared with Title 24 and ASHRAE 90.1 2004 to check if it meets the requirement. c) Internal heat gain profile: To determine how much energy is required to maintain thermal comfort in the various zones, both in heating or cooling, it is very important to assess the heat gained in that space through different source. The sources inside spaces that generate heat and thus affect cooling loads are lightings, plug-loads such as computers, plotter, printers, cooking appliances, and peoples. By understanding the internal heat gain profile, existing conditions inside the space can be better understood. d) HVAC profile: It has been documented by 2010 released building energy data book that 37% of energy consumed by the buildings in commercial sector goes to space conditioning as illustrated in Fig. 3.2 although end-use splits vary considerably by building type, for instance for floor-space devoted to food-sale, refrigeration consumes most of the energy. The RTH building is an internally load dominated building with no 72 natural ventilation provided and thus relying on the HVAC system to maintain indoor comfort levels. So it becomes all the more important that the HVAC profile is created to understand the mechanical system and ensure that it has been designed appropriately to meet the energy requirement in an efficient way. S E D S i n F i g 3.2 s t a nds for ‘S t a t e E ne r gy D a t a S y s t e m ’. Fig 3.2 Typical commercial sector energy end use (Buildings Energy Data Book, 2010) 73 3.1.2 Indoor Thermal Comfort Research Fig 3.3 Indoor thermal comfort research flowchart This step of the research is about finding whether the environment inside Ronald Tutor Hall (RTH) Building is thermally comfortable for the occupants. This is done by monitoring two important factors associated with thermal comfort which are indoor temperatures and relative humidity (RH). Fig 3.3 shows the Indoor thermal comfort research procedure. Data Acquisition System (DAS) which was composed of several programmable data loggers and transducers was set up inside different areas of RTH building to monitor temperature and RH in accordance to the procedure for measuring and reporting commercial building energy performance provided by National Renewable 74 Energy Laboratory (NREL) (Barley et al. 2005). The data collected was then compared to the thermostat settings of different areas in the building to see if the data from two source matches which was necessary to validate thermostat settings and avoid discrepancies. The validated data is then compared with external temperature and ASHRAE 55 2004 which gives guidelines for Thermal Environmental Conditions for Human Occupancy and thus we obtain our thermal comfort and mechanical system performance. External temperature reading was taken from the website weather- underground which gives weather information for worldwide locations. Downtown Los Angeles was selected as the location for external temperature reference as it falls under same climate zone of RTH. It is understood that there can be microclimates existing within the same climate zone, however since there was no recorded weather data for the site, the nearest location with the recorded weather data was selected. There was also survey of the occupants conducted to gauge users comfort. The occupants were asked questions such as what they thought of the noise level inside the building, the air quality, the temperature inside, the lighting, if it was too bright or too dark etc. The only major complain most of the occupants had was that the temperature inside was often too cold for comfort. 3.1.3 Energy modeling tools Energy modeling tool eQuest was used to assist with the energy improvement strategies for RTH. The first step in eQuest was to simulate the current energy performance of RTH 75 with the help of calibration. The next step was to take this calibrated model and introduce elements such as sunshade, then check how it affects the energy consumption and thus come upon strategies that lowers the energy consumption of RTH. eQUEST was selected to simulate the energy consumption performance of RTH. eQUEST uses DOE-2 as its foundation for calculations. DOE-2 is the most widely recognized building energy simulation program currently available after two decades of continued development and enhancement. (Energy Design Resources, 2010) “The DOE-2 software was developed by James J. Hirsch & Associates (JJH) in collaboration with Lawrence Berkeley National Laboratory (LBNL), with LBNL DOE-2 work performed mostly under funding from the United States Department of Energy (USDOE) and other work performed mostly under funding from a wide range of industry organizations and ourselves. ” (http://www.doe2.com/) eQUEST was selected as a primary simulation tool because it uses DOE-2 for calculation and like the DOE2 webpage mentions, it is a sophisticated yet easy to use energy modeling tool. The tool gives the option of creating a very basic model to a fairly detailed model. The tool covers all the important aspects of the design that would impact the energy use such as Architectural design, HVAC equipment, building type & size, floor plan layout, construction materials, area usage & occupancy and lighting system which helps in creating a very effective energy model. The simulation results generated are in a very nice, easy to understand graphical format and one has the option of displaying the estimated building energy usage in a monthly or annual format. It is also possible to do multiple energy efficiency simulations and view all the results in side by side graphics. 76 The other great feature is the ability to compare the alternative design results. The best part of using eQUEST tool is, the results are generated quickly and does not take long time to give simulation result. 3.1.4 Energy Consumption Baseline Research In order to understand the RTH energy consumption trend, the electricity and gas usage record for the year 2008 was collected from the university facility management services. From this record we can see the peak months for electricity and gas usage as well as the ratio of electricity and gas usage each month which are essential information to understand the building performance. There was as such no irregularity found in the energy usage record. This point has been further discussed in detail in chapter 4 under section 4.7 Ronald Tutor Hall energy consumption profile. 3.2 Research Methodology Fig. 3.4a & 3.4b gives the entire procedure in a flowchart diagram to explain how the project will be carried forward. The information collected and analyzed in the groundwork research which constitutes occupancy user profile, building envelope profile, internal heat gain profile and HVAC profile will be fed to the energy modeling tool eQUEST to build the RTH model. This model will be referred to as as-built-model and is not calibrated yet. The s i m u l a t i on re s ul t fr om t he ‘ a s bui l t m ode l ’ w i l l be c om p a re d t o t he actual energy consumption profile of RTH after which it will be calibrated so that the as- built-model model simulation result matches with the energy consumption profile of 77 RTH. This model after calibration will be referred to as calibrated-model. The calibrated model will be worked upon with different situations such as introducing sunshade or changing the system operation schedule for staircase & corridor area or removing the low e coating from the south façade of RTH etc. and check if it improves the energy consumption performance of the RTH. The final proposed-model will be the model with lower energy consumption after having made desirable changes to the calibrated model. Fig 3.4a Research Methodology flowchart 78 Fig 3.4b Research Methodology flowchart 79 Chapter 4: Indoor Thermal Comfort Research of Ronald Tutor Hall 4.1 Introduction This research was carried out to check if the temperature and relative humidity inside the building is at a comfortable range. To decide what a comfortable range is, ASHRAE standard 55-2004 was referred to, which has its own definition for what is thermal comfort. ASHRAE standard 55-2004 is one of the standards set by ASHRAE for Thermal Environmental Conditions for Human Occupancy. To carry out the research, temperature and humidity data loggers were used. It may seem that checking the thermostat settings installed in the building would be sufficient to know if the temperature inside is maintained at a comfortable range but the problem with this approach was accepting the thermostat reading as the actual temperature maintained inside with nothing to validate it. Data loggers were intended to validate the thermostat settings and the building system response. Also, it is often found that the actual performance of the building is not the same as the calculated performance done through building energy modeling tools. Data loggers help us by validating the thermostat settings. 80 4.2 Data Acquisition System (DAS) Installation of Ronald Tutor Hall 4.2.1 DAS Equipment To carry out the indoor thermal comfort research on Ronald Tutor hall, a Data Acquisition system was required which in this case was composed of software called HOBOware Pro, data loggers from Onset called HOBO U12 Data Loggers, a Windows Computer and a USB interface cable for connecting loggers with a direct USB interface so that the data can be transferred to the computer. Fig.4.1 DAS setup 81 4.2.1a HOBOware Pro: HOBOware Pro is developed by Onset Computer Corp. It does not require much time to learn the software and is easy to use. The software allows you to view, graph and analyze the data with just the clicking of a mouse. The data can be further exported to a spreadsheet for detailed analysis. It is also possible to view multiple data files on the same screen which is very useful in comparing the data. It gives you the option of selecting the data required to be logged such as temperature, humidity etc. and the interval at which the data gets logged, also one can set time at which point the data logger starts logging. One can also verify memory used and battery life. Fig 4.2 HOBOware showing data reading in graph form from Hobo # 8 82 4.2.1b HOBO U12 Data Logger: It is manufactured by ONSET Company. It is an indoor data logger. It measures temperature, Relative humidity & Light Intensity Intensity and has a spare channel and socket to record a fourth input. Its features include high accuracy measurement, large memory for long term deployments. (ONSET, 2010) Fig.4.3 HOBO U12 Data Logger used for data logging 4.3 DAS Installation Procedure & Method Before the Data Acquisition System (DAS) was installed in the building there were certain steps which had to be taken first. These steps were; a) Installation of software HOBOware pro in PC b) Normalization of Data loggers – Data loggers which were planned to be installed in the building had to be normalized first. The reason for normalizing is, many times two data loggers located at same spot would not give exactly the same reading. So, in order to make sure that all data loggers can be accurately compared they are normalized first. The normalization process involves taking each data logger, connecting it to the computer 83 with the USB interface and then launching each of them using HOBOware pro software. Before launching the Data loggers, we have to specify items that have to be logged in the data logger; in this case temperature and relative humidity and light intensity was specified. Next step is to specify the interval at which the data logger will log data, which means if the data logger should take reading at every 30 minutes interval or every one hour Interval, in this case it was every 1hour interval. The time has to be set at which the data logger will start logging. Finally a name has to be specified to the data logger so that the data logged from particular data logger can be saved under that name for better organizing of data. Once these steps are taken, the data logger can be launched. Fig. 4.4 Readings from 7data loggers for temperature, relative humidity and light intensity for Normalization process. After the launching process, all the data loggers were put in a zippered plastic (Ziploc) 84 bag and kept inside the refrigerator a minute before the data loggers started logging. The data loggers were kept inside the fridge for 2 hours. Afterwards, they were taken out of the refrigerator and kept at room temperature for another 2hours. All the data loggers were then wrapped in newspaper and kept in sunlight for another 2hours. One by one the data loggers were connected to the PC via USB interface. Then with the help of HOBOware software the data from each data logger was exported as an excel file and named according to the naming of the data logger. All the data from different excel file was then grouped together in one excel file to make it easy for comparison. The average reading was taken which was then compared to the data of each data logger and the difference was saved for each data logger for future monitoring adjustment. The data is adjusted by adding or subtracting the recorded value difference from the readings of those data loggers that were above or below the average value recorded. In some cases the data is adjusted by multiplying with a chosen fraction number which was not required in this case. c) Deciding data loggers/Hobo location – It is important to carefully decide where to place the Hobos in the building as the information gained should be helpful in serving the purpose of the installation. d) Installing data logger on site – It is recommended to attach a sticker with contact information on the data logger so that one can be contacted if someone finds a logger lying on the floor or is just curious about the device and wants to know what it is. Also it is recommended to take readings from the data logger every two days to make sure some readings can be saved just incase something happens to the data logger. 85 4.4 Location of Hobos/Data Loggers Below are figures that show the location of H obo’ s i n t he b uilding. Fig. 4.5 Location of Hobo 6 & 7 (AutoCAD plan from A.C Martin & Partners) Fig. 4.6 Location of Hobo 1, 9, 10, 11 & 12 (AutoCAD plan from A.C Martin & Partners) 86 Below are photographs of Hobo installed in the building. Fig. 4.7 Location of Hobo 8 Fig. 4.9 Location of Hobo 9 Fig. 4.8 Location of Hobo 7 Fig. 4.10 Location of Hobo 6 87 Hobo 6 is located in the atrium at the ground floor and Hobo 8 is located in the atrium above at the second floor. The reason for locating Hobo 6 & 8 at their respective locations was to check for temperature difference at these two levels (stratification). Hobo 7 is located at ground floor at the dining space to see the temperature variation the space has which is often crowded by students. Hobo 9 is located in 3 rd floor beside the Thermostat which is near the elevator. The reason for placing Hobo 9 beside the Thermostat is to check if the reading from Hobo9 and Thermostat setting would match each other. Hobo 10 is located in the 3 rd floor along the corridor hanging down from diffuser in the Ceiling. This was to check the temperature level near the diffuser. Hobo 11 is located at a Lab facing north east and Hobo 12 is located at a Lab facing south west. The reason for locating Hobo 11 & 12 at their respective locations was to check the indoor temperature variation in these two room s c ons i d e ri ng t he y ’re on oppos i t e c orne rs . 4.5 Analysis of the Data Logger Results The data loggers were installed in the building on 23 rd October 2009 and were allowed to take readings until 31 st October 2009. The readings from 24 th & 26 TH October was decided to put in the report as those two days saw a greater fluctuation of outdoor temperature although reading from all the other days were also analyzed. The data for outside air temperature was taken from the website http://www.wunderground.com/US/CA/Los_Angeles.html which gives weather information for worldwide locations. Downtown Los Angeles (DTLA) was selected as the location for outside air temperature as it falls under the same climate zone as RTH. It 88 is recognized that there may be significant differences within a climate zone. Despite this fact DTLA was chosen as the reference for outside air temperature as it was the closest in distance in comparison to other options available, also there was no data recorded for the period needed from the University weather monitoring system where the building is located. Fig. 4.11 & 4.12 shows reading from Hobo # 6 & 8 which were located in the atrium on the Ground floor and above the atrium at Second floor. The thermostat settings are kept at 72º F for these locations. Fig.4.11 Indoor Temperature Readings from Hobo number 6 & 8 on 10/24/09 From Fig.4.11 we can see that the outside temperature ranges from a maximum of 81.5 degree Fahrenheit to minimum of 62º F whereas on Fig 4.12 the outside temperature ranges from maximum of 90º F to minimum of 64º F. Legend OT refers to outside temperature, legend H6 refers to readings from Hobo 6, legend H8 refers to readings from Hobo8. In both the cases above the inside temperature is maintained at almost 72º F 50 55 60 65 70 75 80 85 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time(Hrs) Temp( deg. F) OT H6 H8 89 although H6 located in the atrium on the Ground floor shows a slightly higher temperature recordings than H8 located above the atrium at Second floor. Fig. 4.12 Indoor Temperature Readings from Hobo number 6 & 8 on 10/26/09 From the above chart we can conclude that the HVAC systems for these locations are on for 24 hours a day and that is why the almost smooth straight line in the graph for temperature recorded by Hobo 6 & 8 for all those hours. We can also see that there is little temperature stratification in the space. From the mechanical system drawings of the building, it is seen that that the Air Handling units serving this zone have both preheat coil and cooling coil which means a space can be heated or cooled according to the need of the space. Considering the indoor temperature profile, a number of scenarios are possible. It is however clear that the RTH bui l di ng i s i nt e rna l l y dom i na t e d a s i t ’ s a laboratory cum office building. All of the people, equipment and lights in the space are producing heat. Office and laboratory equipments add to the internal heat gain. A large percentage of these internal loads are transferred directly to the space- which is why the 50 55 60 65 70 75 80 85 90 95 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Time (Hrs) Temp(Deg. F) OT H6 H8 90 building starts to heat up and requires exhaust fans to vent out this heat. There are also toxic fumes that get released in the chemical laboratory which needs an exhaust fan to vent it out. Since RTH is internally dominated, we can say with certainty that in the above indoor temperature profile, only the cooling is kicking in. According to ASHRAE 55 2004 the indoor temperature should be kept in the range of 68-75 degrees Fahrenheit for winter and 73 – 79 degrees Fahrenheit for summer. We can see that the temperature maintained inside meets the ASHRAE standard for thermal comfort. However there is room for reducing the cooling load in this area by increasing the thermostat setting. Given the nature of the space, in this case a corridor area, it does not seem necessary to have a constant temperature of 72º F as observed in the figure above. Instead a set point of 73-79 degrees Fahrenheit can be set for the system which will reduce the cooling load. Additionally it is recommended that the HVAC system schedule be changed from a 24/7 operation to one where the system can shut-down after hours. In the next chapter the simulated building model will be carefully analyzed to look for periods where the system can be actually shut down without compromising the comfort of the occupants. 91 Fig. 4.13 Indoor Temperature Readings from Hobo number 11 & 12 on 10/24/09 Fig. 4.14 Indoor Temperature Readings from Hobo number 11 & 12 on 10/26/09 50 55 60 65 70 75 80 85 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time(Hrs) Temp(Deg. F) OT H11 H12 50 55 60 65 70 75 80 85 90 95 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time(Hrs) Temp(Deg. F) T0 H11 H12 92 Figures 4.13 & 4.14 shows the indoor temperature reading from Hobo number 11 & 12 which were located on the 3 rd floor inside the laboratory room, facing north-east and south-west respectively. OT in the chart refers to outside temperature. The Hobo 11 located on south-west corner gives a slightly higher level of inside temperature reading then the Hobo 12 located on north-east laboratory, which makes sense as the south-west corner receives more direct solar gain than the north-east corner. However, in both the cases, the profile of the Indoor temperature graph is almost a smooth straight line with just a variation of 2º F. RTH laboratories were designed to have their system on for 24 hours because of the possible hazard that occurs in labs. From the graph we can see that the system is working 24 hours as the temperature inside the space is maintained at 72º F throughout the 24 hours period. As the space is a laboratory space there does not seem much scope to reduce load on the system from the existing load, however it would make sense to set the thermostat setting a little higher, at 75º F instead of 72º F which is still comfortable temperature and under ASHRAE range of comfort, thus easing the load on the system and conserve energy. It is important to point out that the ten students who use the lab were asked what they thought of the temperature inside the lab. Seven of them responded that the lab was on the colder side while the remaining 3 found it comfortable. 93 Fig. 4.15, 4.16, 4.17 & 4.18 shows the Indoor humidity readings from Hobo # 6, 8, 11 & 12 respectively. Hobo 6 is located at the atrium on the ground floor, Hobo 8 is located above the atrium on the second floor, Hobo 11 is located on the 3rd floor inside the lab facing north-east and Hobo 12 is located on the 3rd floor inside the lab facing south-west corner. OH in chart refers to Relative humidity outside. Outside Relative Humidity is seen ranging between 37 – 90% on the 24th of Oct, 2009 and about the same range on the 26th of Oct 2009 but with different fluctuation pattern. The indoor humidity profile is seen ranging from 55-60% for both atrium and lab space on 10/24/09 and 30-56% for both atrium and lab space on 10/26/09. There is essentially no difference in the indoor humidity level at the base of the atrium and above the atrium. As for lab space, the lab facing north-east corner has a slightly higher indoor humidity level then the lab facing south-west corner, although the difference is negligible. According to ASHRAE 55 2004 standard, indoor humidity levels should be maintained between 30 – 60 % which we can see is maintained in Ronald Tutor Hall. Fig. 4.15 Indoor Humidity Readings from Hobo number 6 & 8 on 10/24/09 30 35 40 45 50 55 60 65 70 75 80 85 90 95 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time(Hrs) RH(%) OH H6 H8 94 Fig. 4.16 Indoor Humidity Readings from Hobo number 6 & 8 on 10/26/09 Fig. 4.17 Indoor Humidity Readings from Hobo number 11 & 12 on 10/24/09 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time(Hrs) RH(%) OH H6 H8 30 35 40 45 50 55 60 65 70 75 80 85 90 95 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time(Hrs) RH(%) OH H11 H12 95 Fig. 4.18 Indoor Humidity Readings from Hobo number 11 & 12 on 10/26/09 Fig. 4.19 shows the Indoor temperature reading from Hobo # 10 which was located on the 3 rd floor below the diffuser on the ceiling on 11/04/09. This particular Hobo was repeatedly found to be missing after its installation and that is why data could not be Fig. 4.19 Indoor temperature Readings from Hobo number 10 on 11/04/09 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time(Hrs) RH(%) OH H11 H12 96 collected for same period as the other Hobos, which is why the data is shown for 11/04/09. From the chart we can see that the outside temperature ranges from 55 – 69 degrees Fahrenheit whereas the inside temperature is maintained at almost 70º F dipping to 69º F during noon hours and for a brief period rising to 71º F during evening hours. The reason behind locating the Hobo # 10 near the diffuser was to check the temperature difference near the diffuser and the whole space and to also see if the system is working the whole time. The almost straight line in the indoor temperature profile for the whole 24hours clearly suggests that the system is on for 24 hours although it is a corridor space. The thermostat setting, set for the space was 72 degrees Fahrenheit. Considering the external temperature being low that particular day I was expecting the temperature reading from Hobo # 10 to be slightly higher as I expected the heating to be on. I am assuming that the building envelope and internal heat gain from the building is helping the system to ease load on its heating. As it is, the corridor space is at the internal core of the building with Lab. on both of its side throughout its length, so it remains warmer then the perimeter zone. The reading from Hobo # 9 which was located at the same floor but on the northwest end of the corridor near the elevator showed the same kind of indoor temperature profile but was slightly higher in comparison. Its temperature ranged from 70 – 72 degrees Fahrenheit and at one point even reaching 73 degrees Fahrenheit. This shows that the northwest space where Hobo # 9 was located, which also happens to face a large glazing 97 area is warmer then the spot near the diffuser where Hobo # 10 was located, at the centre portion of the floor. This makes sense as the cooling load on the central portion of the building is always higher due to high internal heat gain as compared to the perimeter zone. The higher temperature reading from Hobo #9 compared to Hobo #10 has to possibly do with reheating of the particular space as the outside temperature was colder that day. IDPH ASHRAE 55-2004 Humidity 20% - 60 % 30% - 60 % Temperature 68 - 75 (winter) 68 - 75 (winter) 73 – 79 (summer) 73 - 79 (summer) Table 4.1 Recommended Indoor Humidity and temperature from ASHRAE &IDPH Hobo # 1 was located at the staircase block on the third floor for the period between 11/03/09 – 11/10/09. During the period of evaluation it was seen that the indoor temperature ranged between 71 – 73 degrees Fahrenheit throughout the day while the external temperature ranged between 54 – 80 degrees Fahrenheit. Looking at the profile there is no doubt that the staircase space is conditioned for 24 hours a day. This is one area that can be looked into for reducing considerable load on the system as it is not very necessary to fully condition a staircase block. The simulated building model can be analyzed to see if the building envelope will help in keeping this staircase space at a comfortable indoor temperature range without the help of the system or with very little help of the system. 98 4.6 Summary From the above research it was observed that the thermostat setting for all the occupied space is kept at 72º F for both summer and winter months. It was also observed that lights were left on in the classrooms, conference rooms and labs even when the space was unoccupied. An unusual observation was also made during this research. It was found that the data loggers reading from 26 th October 2009 shows unusual drop in the humidity level for all the spaces where data logger was installed despite the indoor temperature being constant. No explanation could be found for this phenomenon. It was also noticed that the spaces such as corridor and the staircase area are conditioned 24/7. M a n y of t he V A V s y s t e m s ’ s c he dul e s c a n be m a ni pu l a t e d t o a ddr e s s t hi s i s s ue , provided comfort ranges can be maintained, especially during occupied hours. Survey was conducted among twenty frequent users of the building. They were asked to answer either i n ‘g ood’ or ‘bad ’ about the temperature, noise level, smell and lighting level inside the building. The survey was conducted to gauge the occupants comfort. Table 4.21 shows the result of the survey. Items Good Bad Temperature 3 17 Noise level 20 0 Smell 20 0 lighting level 20 0 Table 4.2 Indoor comfort survey 99 A s s e e n from T a bl e 4.2, a l l t he i t e m s i n t he s urv e y w e re c he c ke d ‘g ood’ e x c e pt f or t he indoor temperature. 17 users of the building found indoor temperature to be bad and the reason cited was that the temperature maintained inside is on the colder side. In the above research indoor air temperature and indoor humidity was measured to determine thermal comfort. However besides air temperature and humidity other factors that determine thermal comfort are; Metabolic rate – It is the rate at which our body burn calories to get energy for different functions of the body such as breathing, heartbeat, blood circulation etc. While burning these calories our body releases heat. The amount of heat released varies with the kind of physical activity the individual goes through. At resting position, the metabolic rate is lower than when the person is working hard, such as when lifting heavy boxes. In ASHRAE the standard metabolic rate is measured in MET. Clothing - Depending on the layers of clothing, a person can feel warm or cold as clothing acts as insulation with more layers adding to higher insulation property. Good layers of clothing can keep a person warm in winter but same layers of clothing in summer would cause overheating as it prevent heat loss. Air speed – It is the speed of air moving across a person. The air speed can warm or cool the person depending on the temperature of the air and the environment of the individual. Room with still or stagnant air can cause occupants to feel stuffy whereas air movement 100 in warm or humid condition can lead to increase in heat loss due to convection without any change in air temperature. Radiant temperature- It is the heat emitted by an object such as office equipment, lab. equipment, lighting etc. Radiant temperature has greater influence than air temperature on how we gain or lose heat to the environment. Operative temperature – ASHRAE 55-2004 Standard defines operative temperature as the uniform temperature of an imaginary black enclosure in which an occupant would exchange the same amount of heat by radiation plus convection as in the actual nonuniform environment. Fig. 4.20 shows the ASHRAE comfort chart showing the comfort zone for winter and summer respectively. 1.0 clo and 0.5 clo refer to layers of clothing typical for winter and summer respectively. Thermal comfort and its calculation is discussed in detail in Chapter 1, section 1.2.1-Thermal Comfort and section 1.2.1a-Thermal Comfort Calculation. Based on the above research it was found that all the spaces examined met the ASHRAE- 55 2004 standard for comfortable indoor temperature and humidity. It is important to note that the dates for data logger installation in the RTH building are different from the dates c hos e n t o a na l y z e RT H hi s t ori c a l e ne rgy c ons um pt i on. D a t a l og g e r’s re a di ng s a re t a ke n in the month of October and November in the year 2009. Historical energy consumption 101 of the RTH building collected are for the year 2008 and weather data for the year 2008 was used for this study. Fig. 4.20 ASHRAE 55-2004 standard comfort chart (ASHRAE 55-2004, 2004) 102 Chapter 5: Building Energy Consumption Simulation Model There are many parameters which need to be determined before starting the work on creating a simulation model. These parameters include geometry, thermal zones, building panels, windows and doors, the lighting system, internal equipment, occupancy and their schedules, HVAC systems; weather data etc. For the same reason groundwork research on Ronald Tutor Hall (RTH) building was done which was discussed in chapter 2 to facilitate the work on creating RTH virtual model. The energy simulation tool eQUEST was used to create the model. The model was then calibrated to reflect the actual energy performance of RTH for the year 2008. The calibrated model was then used to analyze different strategies that would help with improving RTH energy consumption. 5.1 Weather Data The weather file in the format EnergyPlus (epw) for the year 2008 was obtained from the c om pa ny c a l l e d “ W e a t he r A na l y t i c s ” . T he fi l e w a s s i t e b a s e d r a t he r t ha n z one b a s e d . T hi s made the weather data reflect the real weather condition that existed for the Ronald Tutor Hall building in the year 2008. Zone based weather file on the other hand are too general as several micro climates can exist within a single zone. However to use the weather file in eQuest, it had to be converted from EnergyPlus (epw) files into eQUEST/DOE-2 (bin) file which was done using converter eQ_WthProc. 103 5.2 Codes and Standards A series of codes and standards were used for reference, including ANSI/ASHRAE/IESNA Standard 90.1-2004, ANSI/ASHRAE/IESNA 90.1-2010, California Title 24-2001, California Title 24-2008, ASHRAE 14-2002, FEMP M&V Guidelines-2008, and IPMVP-2012. The documents helped in analyzing the inputs for the model and obtain default values for the cases where the values were missing. It helped in calibration of the model. They were used to check the acceptable error range for calibration. The codes also helped in analyzing strategies that would improve the building energy consumption. 5.3 Creating the RTH Virtual Model On starting eQUEST, the user gets two options or “wizard s” as called in eQUEST to start the model. The first wizard is called Schematic Design Wizard and the second one is called Design Development Wizard. The schematic design wizard is used for projects which are smaller/simpler structures and the ones which do not have enough information needed to create a detailed model. The Design Development (DD) Wizard, on the other hand, is used for larger, more complicated structures for which enough information is available to be able to create a detailed model. The Design Development Wizard was chosen to create detail model of Ronald Tutor Hall building. 104 5.3.1 Design Development Wizard On entering Design Development (DD) wizard, the user is taken to the Project Navigator screen which helps in creating the model. From this screen one can navigate to different components such as Project/Site/Utility, CHW plant equipment, HW plant equipment, Bldg Shell Components, Air-Side System Types etc and create and edit those components. Fig. 5.1 below shows the screenshot of the DD wizard screen. Fig. 5.1 DD wizard screenshot 5.3.2 Project/Site/Utility – This contains the general information of the project. It consists of 7 wizard screens but only 3 can be used for filling in the project information. This particular component allows the user to fill in information such as name of the 105 project, type of the building, building location & jurisdiction, number of seasons to include, type of utility for electricity & gas and the year for which the building needs to be analyzed. It is in this component that a user can choose the specific weather file that is applicable to the site. Fig. 5.2 shows the screenshot of one of the wizard screen out of three, for the Project/Site/Utility component showing the information filled in for RTH building. Fig. 5.2 Project/Site/Utility wizard screenshot 5.3.3 Bldg Shell Components - This allows the user to create and edit different floors of the building. Each floor is referred to as shell. There are 25 wizard screens allotted to each floor of which 11 screens can be used to fill in information for that particular floor. 106 The information to be filled in includes area of the floor, envelope construction details, interior construction details, building operation schedule, building footprint, interior lighting loads, miscellaneous loads, areas allotted to each activity such as classroom, laboratory etc. and zone group definitions where each space on the floor can be attached to a particular zone and HVAC system serving that space. Fig. 5.3 & 5.4 shows the screenshot of the ground floor building envelope construction detail and window details. Fig. 5.3 Ground floor envelope construction 107 Fig. 5.4 Ground floor window details 5.3.4 Air-side System Types - This allows the user to create and edit different HVAC systems in the building. There are 7 wizard screens allotted to each system which are used to fill in information for that particular system. The information includes, type of system, thermostat set points for different season, design temperatures, air flows, type of fan, fan schedules etc. Fig. 5.5 & 5.6 below shows the eQUEST input for Air Handling Unit 1 (AHU 1). 108 Fig. 5.5 Air Handling Unit 1(AHU 1) system input Fig. 5.6 Air Handling Unit 1(AHU 1) fan system eQUEST input 109 5.3.5 CHW plant equipment – This contains the chilled water system information. RTH is a part of the USC chilled water loop, there is no chiller or cooling tower in the building. However, a mechanical system without chiller is considered incomplete and cannot be simulated. There must be a chiller and a cooling water system in the model. As a result, the virtual component is allowed to exist in the model for simulation purpose. 5.3.6 HW plant equipment - This contains information for the hot water system. Heating Hot Water for RTH comes from the campus steam system. There are no boilers in the building. However, a mechanical system without Hot Water System is considered incomplete and cannot be simulated. Therefore, the virtual component is allowed to exist in the building for simulation purpose. 5.4 Thermal Zones Ronald Tutor Hall (RTH) building has 6 floors; each floor is served by multiple HVAC systems. Also each space depending on their activity has different lighting density, equipment operation schedules, occupancy schedules, HVAC system etc. For this reason the thermal zoning of RTH was done according to the activity of the space which would enable editing the settings of a particular space when trying different alternatives to improve energy consumption. Fig. 5.7 shows the 3 rd floor zoning in eQUEST. The spaces with light gray colors are unconditioned zones. 110 Fig. 5.7 RTH 3 rd floor zoning in eQUEST. The various thermal zones created were then grouped under 5 main thermal zones which were created based on the type of HVAC system serving those zones. Table 5.1 shows the 5 main thermal zones for the RTH building. 111 Name HVAC System Activity Area(ft²) Zone 1 AHU 1 B stair, G stair, G dining, G toilet, G lobby, G corridor, G work, 2nd stair, 2nd lobby, 2nd lounge, 2nd Conference, 2nd library, 3rd office, 3rd corridor 1, 3rd lab 1, 3rd lobby, 3rd lounge, 3rd toilet, 3rd stair, 3rd elevator, 4th office 1, 4th lab1, 4th lobby, 4th toilet, 4th corridor 1, 4th conference, 4th stair, 5th office, 5th toilet, 5th stair 25970 Zone 2 AHU 2 B lab 1, B corridor, B lobby, B toilet 10325 Zone 3 AHU 3 B lab 2, B server, 1820 Zone 4 AHU 4 5th lobby, 5th lab, 5th office 2, 5th conference, 5th corridor 12474 Zone 5 AHU 5 G classroom, G office, G corridor 2, 2nd office, 2nd computer, 2nd toilet, 2nd corridor, 2nd seminar, 2nd lab 2, 2nd corridor, 3rd lab 2, 3rd office 2, 3rd corridor, 4th lab 2, 4th corridor, 4th office 2 34923 Table 5.1 Thermal zones in RTH 5.5 Geometric Model A geometric model is created in the bldg shell component. When a floor is created in the bldg shell component, the user is asked to define the footprint for that floor. There are default shapes available for the footprint but the custom feature was used for the RTH model to have a more accurate footprint. The CAD plans were imported to eQUEST and the floor outlines were then traced. Fig. 5.8 below shows the wizard screen where footprint is defined. Fig. 5.9 below shows the 5 th floor footprint traced in eQUEST. 112 Fig. 5.8 Building footprint screen in eQUEST. Fig. 5.9 RTH 5 th floor footprint traced in eQUEST To have a complete geometric model, each floor footprint needs to be defined and then information such as orientation, area of the floor, floor to floor height, envelope construction details, window details, door details, and interior construction details need to 113 be filled in for each floor. Once all the construction information is filled in, eQUEST generates the geometric model. Fig. 5.10 shows the geometric model of RTH. It is important to note here that the surrounding buildings were not modeled in eQUEST because they did not cast any shadow on the RTH building thus having no shading effect on the building. The shadow analysis is discussed in Chapter 2; section 2.1- Building Site and Characteristics. Fig. 5.10 RTH geometric model in eQUEST 5.6 Simulation Result After completing the virtual model of RTH building on eQUEST, the simulation is run. Fig 5.11 shows the comparison of the simulation result with the historical electrical 114 consumption. The historical electricity consumption includes load from lighting, equipment and fans and does not include loads from cooling towers and boilers as there are no cooling towers and boilers. Heating hot water comes from the campus steam system. There is no comparison for gas usage as there is no gas consumption. In the simulation result it was observed that good amount of electricity consumption went into space cooling which is energy consumed by the virtual chiller defined in the eQUEST model. However in the RTH building, energy inlet for space cooling is chilled water and not electricity. Chilled water is served by a chiller which is not located in the RTH building. Chilled water usage for the RTH building is monitored separately. Therefore energy for space cooling is treated independently and not as part of the RTH electricity consumption profile. However, for the sake of comparison, simulated electricity consumption profile with and without space cooling load was included in the Fig. 5.11 along with the historical electrical consumption profile. From Fig 5.11, one can see that the difference between simulated and actual result is very high. Also, the space cooling load is higher for July-October months as is evident by the difference between two DOE 2 result profiles. The weather data for 2008 was referred from the site http://www.wunderground.com/ which showed that temperature for July- October months was higher than the other months in 2008. This is possibly why the space cooling loads are higher for these months. Fig 5.12 below shows the electricity end use for the RTH building. Miscellaneous equipment or plug loads consumes the highest 115 electricity followed by lighting. The reason for high miscellaneous load is due to large laboratory equipments. Fig. 5.11 Difference between actual and simulated electricity (DOE 2) Fig. 5.12 RTH Electricity end use. 5.7 Calibration In this step, the results from the simulation are compared with the historical energy consumption data and the difference between the two results is analyzed to decide whether the simulated result is acceptable. However, to compare the two results, the 0 100 200 300 400 500 600 700 800 900 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Actual Electricity(MW H) 9% 0% 8% 1% 52% 29% Cooling Heat Reject. Vent.Fans Pumps & Aux. Misc. Equip. Lighting 116 calibrator must be careful that the data from the simulation and historical energy consumption are in the same time period (hourly, daily, monthly or annually) and same unit (kWh, kBTU, etc). A calibrated model has simulation result which when compared to the historical energy consumption data, the difference between the data is within the specified range permitted to be considered calibrated. 5.7.1 Analyzing Simulation Results To calibrate a model, its simulation result needs to be compared with the historical energy consumption data and the difference between the two data needs to be analyzed. To help with this analysis, there are several indices used, of which the two most popular ones are; (1) CVRMSE (Coefficient of Variation of the Root Mean Square Error) (2) NMBE (Normalized Mean Bias Error) In the two above formulas, yi are the values historical energy consumption data, yi are the values of simulated results, y is the arithmetic mean value of energy usage data, n is the total number of data, p is the number of parameter (for calibrating energy models, p=1). (Yang, 2012) Once the difference between the results is analyzed, there are different codes and standards that can be referred to check the acceptable error range requirements. Table 5.2 117 shows the acceptable error range from three different standards for monthly data. After deciding upon the standard to follow for calibration, one can come to conclusion whether the particular model is calibrated or not. ASHRAE 14 FEMP IPMVP CVRMSE ±5% ±5% ±10% NMBE ±15% ±20% ±15% Table 5.2 Acceptable error range 5.7.2 Calibration of RTH Model Table 5.3 & 5.4 were generated after analyzing the initial RTH simulation result. The table shows the acceptable error range from three different standards and the error percentage of the simulated result. Table 5.3 includes space cooling load and Table 5.4 excludes space cooling load. From both the table it is clear that the simulated result error is way higher than the acceptable range. Total Electricity ASHRAE 14 FEMP IPMVP CVRMSE 114% ±5% ±5% ±10% NMBE -118% ±15% ±20% ±15% Table 5.3 Error analysis of simulated result. Electricity(no space cooling) ASHRAE 14 FEMP IPMVP CVRMSE 92% ±5% ±5% ±10% NMBE -95% ±15% ±20% ±15% Table 5.4 Error analysis of simulated result excluding space cooling After running several simulations, it was concluded that the values given for the historical electricity consumption for the RTH building were inaccurate as the simulated result values were constantly much higher than the actual electricity consumption profile 118 despite taking all possible measures to correct the model. The original copy of the utility bill for the RTH building was requested from the USC facility management services to confirm the observation but the management declined the request. To proceed with the calibration anyway, it was decided to check what happens when the miscellaneous equipment loads (which are often called plug loads) is removed from the model. The miscellaneous equipment load includes loads from printers, plotters, copying machine, laboratory equipments, appliances etc. The plug load values were all based on re port ‘P roj e c t d e s c ri p t i on a nd re qu i re m e nt s , 2002’ by IB E consulting engineers which was an initial design report and did not reflect the existing situation. It was not possible to crosscheck the values because there was no equipment schedule available and the permission to physically investigate the equipments & appliances in the RTH building was denied. Most rooms are kept locked and need ID for access. On removing the plug loads from the model, it was observed that the simulation result almost perfectly matched with the historical energy consumption as seen in Fig. 5.13 below. To make sure that the model is calibrated, the result was analyzed with CVRMSE and NMBE and as can be seen from Table 5.5 below, the result satisfies the error range permitted by all three standards for both CVRMSE and NMBE. This meant that the RTH model is now calibrated. The calibrated electricity consumption includes load from lightings, fans and pumps and does not include space cooling load, miscellaneous equipment loads, heating load and load from cooling towers and boilers. 119 Fig. 5.13 RTH Calibrated model electricity consumption comparison Electricity(no space cooling) ASHRAE 14 FEMP IPMVP CVRMSE 1% ±5% ±5% ±10% NMBE 0% ±15% ±20% ±15% Table 5.5 Error analysis of RTH calibrated model It is important to note here that this calibrated model could not be used for analyzing strategies to improve energy consumption because removing the plug loads made the model unrealistic despite being calibrated. The loads from cooling and fan in the simulated result were affected by the plug load removal. There was substantial decrease in load from cooling and fan. Therefore it was decided that further calibration needs to be done. 5.7.3 Final Calibrated RTH Model For this calibration, the plug loads were included. However, since the plug loads values were unverified, to achieve calibration the plug loads value from each space was reduced and the simulation was run. The reducing of the plug load values was done until the point 0 50 100 150 200 250 300 350 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Actual Electricity (MWH) DOE 2 120 where the error from the simulated result was at a margin which could be considered as calibrated. The space cooling load was treated independently and was calibrated separately. Fig. 5.14 shows the comparison between calibrated simulated electricity consumption and the historical electricity consumption for the RTH building for the year 2008. The electricity profile here includes load from lighting, fans, heat reject, and miscellaneous equipment. Fig. 5.14 RTH Calibrated model electricity consumption comparison For calibrating the space cooling, it was required to convert the RTH chilled water consumption for the year 2008 to end use electricity. To do that, the formula below was used. Here Pc is electricity consumption (kWh), Ew is energy consumption in chilled water (kWh) and C is cooling load efficiency of chiller (kW/ton). (Yang, 2012) 0 50 100 150 200 250 300 350 400 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Electricity (MWH) 121 In this case, C equals to 1.3. In real scenario there are efficiency curves for chillers, however for simplification the efficiency of the chiller in the model was assumed to be constant and equal to the nominal coefficient of performance (COP). Fig. 5.15 shows the comparison between calibrated space cooling and the actual space cooling. The summer months show higher cooling load for both calibrated and actual cooling as temperatures were higher in those periods as referred from the site http://www.wunderground.com/. However, for calibrated space cooling, the loads during summer months are much higher when compared to the load for actual cooling for the same months. The reason for this unusual high load for calibrated space cooling during summer months could not be determined. Also the source of the difference between calculated and observed cooling could not be determined. Fig. 5.15 RTH cooling comparison Table 5.6 shows the error analysis of the simulated result for both electricity and chilled water (cooling). The electricity usage profile can be considered calibrated as per NMBE 0 20 40 60 80 100 120 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Cooling (MWH) DOE 2 122 but under CVRMSE, it is considered un-calibrated as it does not meet the allowed margin of error. As for chilled water usage profile, it is considered calibrated under both CVRMSE and NMBE. Chilled Water Electricity ASHRAE 14 FEMP IPMVP CVRMSE 5% 14% ±5% ±5% ±10% NMBE -1% -13% ±15% ±20% ±15% Table 5.6 Error analysis of RTH calibrated model Fig. 5.16 shows the effect of reducing plug load values (for calibration) on different items in the simulation result. Actual plug load here refers to the use of plug load values which w e re ba s e d on i ni t i a l re port ‘P roj e c t de s c ri pt i on a nd re qu i re m e nt s , 2002’ by IB E consulting engineers and does not reflect the existing condition. Apart from the obvious effect on the simulated result plug load, reducing plug load also reduced load from cooling, fans and lights. Fig. 5.16 Effect of reduced plug load on different items. 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 Cooling Heat Reject. Fans Plug Load Lights Actual Plug Load (MWH) Reduced Plug Load (MWH) 123 From Fig.5.16 it becomes quite clear that it is important to create and use a plug load schedule that reflects the existing condition. Using inaccurate plug load values not only affects the simulated plug load result but- it also affects the other loads on the system, therefore calibration using inaccurate plug load does not give a realistic energy model. However for this research, because of the unavailability of the plug load reflecting existing condition, this calibrated model was accepted as the closest reflection of the actual building and was used to analyze strategies, which could improve the energy performance of the RTH building. 124 5.8 Measures to improve RTH Energy Consumption 1) Occupancy Sensor On several occasions, while having a walkthrough of the RTH building, it was observed that the lights were left on in the conference room, classrooms, seminar rooms and laboratories despite the space being unoccupied. This caused a lot of energy waste and was the reason for looking into considering occupancy sensors as an energy saving alternative. According to ASHRAE standard 90.1 2004, as shown in Table 5.6 below, all the spaces with occupancy sensor can have 10% power adjustment if the total conditioned floor area of the building exceeds 5000 ft 2 and 15% if it is under 5000 ft 2 . Table 5.6 Power Adjustment Percentages for Automatic Lighting controls (ASHRAE 90.1-2004, 2004) RTH total conditioned floor area exceeds 5000 ft 2 , so 10% was subtracted from the total LPD allotted in conference rooms, classrooms, seminar rooms and laboratories. The simulation result after the power adjustment shows 150 MWH saving in electricity consumption in a year as shown in Fig. 5.17. The saving is equal to approximately 22 residential houses average electricity consumption in California annually. 125 Fig. 5.17 Comparison between RTH model with and without Occupancy Sensor. 2) Thermostat set point While conducting indoor thermal comfort research of Ronald Tutor Hall which is discussed in Chapter 4, it was found that the thermostat setting for all the spaces was set at 72º F. for summer and 68º F for winter. The temperature maintained inside the building was verified by installing data loggers. The temperature inside met the ASHARE 55, 2004 requirement for thermal comfort. However when 20 frequent user of the building were surveyed on what they thought of the temperature inside the building, 17 of them responded that the temperature inside was on the colder side. To address that problem, Thermostat setting was changed to 78º F for summer and the winter set point was kept the same which is still under ASHRAE range of indoor temperature comfort. The simulation result after the changes shows that this setting saves electricity consumption 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 w/o Occ. Sensor w/Occ. Sensor Annual Electricity usage (MWh) 126 by 25 MWH annually as shown in Fig. 5.18. The saving is equal to approximately 4 residential houses average electricity consumption in California annually. Fig. 5.18 Comparison between different thermostat settings. 3) Lighting Power Density (LPD) The LPD of all the areas were observed to exceed the ASHRAE Standard 90.1-2004. This provides significant room for improvement. One of the improvement strategies would be 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 2800 2900 3000 3100 3200 3300 3400 3500 72º F 78º F Annual Electricity usage (MWh) 127 to replace current light bulbs to more energy efficient ones such as Compact fluorescent lamps (CFLs) or Light Emitting Diodes (LEDs). The spaces which require ambient lighting like classrooms should be installed with CFLs whereas spaces which require focused or spot lighting, like work desks should have LEDs. Frequent on/off cycling reduce the lifetime of CFLs, so spaces with such requirement like closets should have LED installation. Also spaces which require dimmer switches should consider LED installation as not all CFLs can be used with them. For outdoors LEDs are preferred as CFLs are sensitive to temperature and need protection. (Eartheasy, 2012) Fig. 5.19 shows the energy savings in different items after 20% reduction in LPD for each space. The total energy saving is equal to 523.9 MWH which is equal to approximately 520 residential houses average electricity consumption in California annually. Fig. 5.19 Energy savings after 20% LPD reduction 0 500 1000 1500 2000 2500 Cooling Heat Reject. Fans Lights Actual LPD (MWH) 20% less LPD (MWH) 128 4) Energy star roof RTH building is located at a site which receives lot of sunlight and the roof remains most exposed part of the building. The surface of the roof is coated with modified bitumen. Bitumen coated roof can reach surface temperature as high as 190º F because of its dark color and poor reflective properties which causes it to absorb about 90% of the sunlight heat. Bitumen is also very dense which causes it to retain heat and stay warmer even when the sun goes down. This heat gain has adverse effect on the cooling load of the building. Such a roof also contributes to the urban heat island effect. Therefore energy star rated roof would be a good consideration for improving the energy performance of RTH building. An Energy star rated roof is said to reduce surface temperature to as low as 100º F thus decreasing the amount of heat transferred into a building. It is also said to reduce peak cooling demand by 10-15%. The energy star rated roof achieves this by their high solar reflective properties. It was not possible to model energy star roof on eQUEST because of its limited selection in materials. Still, using custom layer by layer roof construction on eQUEST, bitumen layer was replaced by aluminum metal for its reflective properties and the rest layer was kept same. On doing so it was observed that annual space cooling load reduced by 1MWh which proved that reflective roofing thus help in easing cooling load. 6) Overhangs. There are no overhangs provided for RTH building despite having a large percentage of glazing on the South-West and North-West corner which happens to receive strong 129 sunlight most of the day. The RTH model was provided with overhangs for South-West and North-West corner to check if it had any impact on the energy consumption. The simulation result showed that providing overhangs made no significant impact on the energy consumption. 7) Triple Low E glazing The existing RTH building has double low E glazing on all the windows. The RTH model was provided with triple low E glazing on all the windows to check if it had any impact on the energy consumption. The simulation result showed that providing triple low e glazing made no significant impact on the energy consumption. 130 Chapter 6: Conclusion and Future Work 6.1 Conclusion The research and the subsequent energy modeling of RTH led to many findings that could improve the energy consumption of RTH. However there were many difficulties both in obtaining the information for the building as well as energy modeling of the building. Original utility bill copies could not be obtained and the plug loads could not be verified, and there was difficulty in using the modeling tool, which resulted in an energy model t ha t w a s n’ t a c c ura t e . D e s pi t e t he i s s ue s , by defining the scope and removing the extraneous variables, the simulation still proved effective in assisting in analyzing several strategies that would help improve energy consumption. Based on the study following conclusions were made; 1) Indoor thermal comfort All the spaces inside RTH were found to satisfy ASHRAE 90.1 2004 standard for comfortable indoor temperature and humidity. However on conducting survey of 20 users of the building, it was found that 85% of them found the indoor temperature to be on the colder side. This directed the focus on thermostat set-points which was changed to 78º F for summer and the winter set point was kept the same which was still under the ASHRAE range of comfort. This setting was not only expected to improve the indoor thermal comfort but it was also found to improve the energy consumption as seen from the simulation result. 131 2) Miscellaneous equipment Based on the type of building, the load from the miscellaneous equipments can be very hi g h a nd i n R T H bui l di ng ’ s c a se, miscellaneous equipment accounted for the highest consumption of electricity as seen in the electricity end use chart generated by simulation result. This is because RTH has several complex laboratory equipments besides office equipment and other appliances. This stresses the importance on purchasing energy efficient products as cumulative load from all these products will have huge impact on energy usage. 3) Building Envelope. It was found that the building envelope of RTH did not meet the ASHRAE 90.1 2004 standard which left room for improvement. However this would mean an expensive re nov a t i on but i t ’ s s t i l l w ort hy of c ons i de ra t i on i f re t rofi t t i ng i s done i n t h e f ut ure . Furthermore, some of the tested changes did not result in significant savings, so advance simulation would be extremely valuable. 4) Lighting Power Density (LPD) Like the building envelope, the LPD of all the spaces in RTH did not meet the ASHRAE 90.1 2004 standard thus leaving room for improvement. Also based on the RTH electricity end use chart generated by simulation result, lighting was found to be the second highest load behind miscellaneous equipment. On many occasion it was observed that lights were left on in rooms without occupants. Also spaces like 5 th , 3rd and 2 nd floor 132 laboratories which receive enough daylight still had their lights left on during daytime. Therefore having a better lighting control mechanism was considered necessary to avoid unnecessary wastage of energy besides switching to more energy efficient bulbs. 6.2 Future Work It is important that the simulation model is correctly modeled to get realistic results when analyzing different strategies for energy savings. The RTH simulation model is not accurate because the data for actual energy consumption is wrong, also the plug loads for the building could not be verified. Therefore future work priority should be to correct the model so that the model can be used for analyzing other energy saving strategy for RTH building in the future. Below are the lists of future work to be considered. 1) Original copy of utility bills should be obtained from the USC facility management services and check if the electricity consumption for the year 2008 is more than the a m ount prov i de d for t hi s s t ud y . I f i t ’ s m ore , t he di f f e re nc e s houl d be c om pa r e d w i t h t he miscellaneous equipment load (plug load) of RTH simulation result to see if the value matches. If the value matches, it would reinforce that the first simulation result was correct. This would mean that the initial model was modeled correctly and the same model can be used for analyzing various other strategies to improve RTH energy consumption. If the values do not match, then point 2 below should be followed to achieve the correct model. 133 2) T he pl ug l oa d v a l ue s for t he m ode l w e re a l l ba s e d on re port ‘P roj e c t d e s c ri pt i o n a nd re qui re m e nt s , 2002 ’ by IB E c ons ul t i ng e ng i ne e rs w hi c h w a s a n i ni t i a l de s i g n re po rt a nd did not reflect the existing situation. Therefore, the schedule should be prepared for all the equipment in RTH building and the actual plug loads should be used in the eQUEST model for more realistic results. 3) Another energy modeling tool like Energy Pro, Energy Plus or IESVE should be used to model the RTH building using the same building inputs so that the results can be c om pa re d a nd be us e d t o v a l i da t e e a c h ot h e r ’ s re s ul t s . 4) RTH receives a good amount of sunlight on its North-West and South-West corner which have large areas under glazing. However no overhangs or fins are provided. Solar s ha di ng de v i c e s c a n be l ooke d i nt o f or i m prov i ng e ne r gy c ons um pt i on i f t he re ’ s consideration for retrofitting in the future. 5) Occupancy sensors seem like a good energy saving strategy. However occupancy sensor performance is dependent on the user occupancy, lighting control patterns, sensor selection and commissioning. There is no definite measurement methodology to check the energy savings and there is the high initial cost that comes with its installation. Therefore a good research and analysis is needed to come up with a design that would help in benefitting from the installation of occupancy sensor. Default values used in Title 24 would be a starting estimate. 134 6) Except for the thermostat set points, nothing else in the HVAC system was analyzed to improve energy consumption. The systems can be looked into in more detail to see if changing any settings would improve RTH energy consumption. 135 Bibliography ASHRAE 55-2004. 2004. Thermal Environmental Conditions for human Occupancy. Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers, INC. ASHRAE Standard 90.1-2004. 2004. Energy Standard for Building Except Low-Rise Residentail Buildings. Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. ASHRAE. 2012. "ASHRAE Brings Technology, People Power in Support of Engineering for Change" Accessed January 7, 2013. https://www.ashrae.org/news/2012/ashrae-brings- technology-people-power-in-support-of--engineering-for-change American-Architects. 2012."Caltrans District 7 Headquarters" Accessed August 10. http://www.american-architects.com/en/projects/34972_caltrans_district_7_headquarters /11/featured Ainsworth, Diane. 2005. "Tutor Opens" Accessed January 7 2009 http://viterbi.usc.edu/news/news/2005/2005_02_02_tutor.htm LA:USC - Viterbi School of Engineering. Brill, Michael., Stephen T. Margulis., and Ellen Konar. 1985. Using Office Design to Increase Productivity. Buffalo, NY: Workplace Design and Productivity. Brandemuehl, Michael. 2005. "Predicting Thermal Comfort". Online doc for Class, AREN 3050 Environmental Systems for Buildings I from University of Colorado, Boulder. Accesed Oct. 2012. http://ceae.colorado.edu/~brandem/aren3050/docs/ThermalComfort.pdf Buildings Energy Data Book. 2010 "3.1 : Commercial Sector Energy Consumption." Accessed September 1, 2012 http://buildingsdatabook.eren.doe.gov/TableView.aspx? table=3.1.4 (). Barley, D., Deru, M., Pless, S., and Torcellini, P. 2005. Procedure for measuring and reporting commercial building energy performance. Golden, CO: National Renewable Energy Laboratory. CEC-400-2008-017-CMF-Rev 1. 2008. Building Energy Efficiency Standards Nonresidential Compliance Manual Commission Second Draft Manual. Sacramento: California Energy Commission 136 Curtiss, Peter, and Newton Breth. 2002. HVAC instant answers. New York: McGraw- Hill. California Energy Commission. 2010 "Energy Maps of California - Califonia Energy Commission." Accessed January 6 2010. http://www.energy.ca.gov/maps/renewable/ building_climate_zones.html CABE. 2011. "Post-occupancy evaluation | Sustainable Places" Accessed March 22 2011 http://webarchive.nationalarchives.gov.uk/20110118095356/http:/www.cabe.org.uk/sustai nable-places/advice/post-occupancy-evaluation EnergyIQ. 2011 "EnergyIQ | Action-Oriented Energy Benchmarking." Accessed February 11, 2011. http://energyiq.lbl.gov/ Energy Design Resources. 2010. "eQUEST®" Accessed June 10. http://www.energy designresources.com/resources/software-tools/equest.aspx Eartheasy. 2012 "Energy-Efficient Lighting: LED & CFL bulb information, including where to buy" Accessed Dec. 04 http://eartheasy.com/live_energyeff_lighting.htm Federal Facilities Council. 2001. Learning from our buildings: a state-of-the-practice summary of post-occupancy evaluation..Washington, D.C.: National Academy Press FEMP. 2008. M&V Guidelines: Measurement and Verification for Federal Energy Project, Version 3.0 HSE . 2012 “ Thermal comfort: The six basic factors." Accessed October 12 http://www.hse.gov.uk/temperature/thermal/factors.htm Hirsch, J. J. 2010. "eQUEST. " Accessed November 10 2009. http://www.doe2.com /equest/ IBE Consulting Engineers, 2003. "Project Description and Requirements" Project Report. for Ronald Tutor Hall. USC Lin, Shih-Hsin. 2008 "Watt Hall Eneregy Management System Implementation Initiative." Thesis. University of Southern California Meir, Isaac A., Garb, Yaakov., Jiao, Dixin., and Alex Cicelsky. 2009. "Post-Occupancy Evaluation: An Inevitable Step Toward Sustainability" In Advances in Building Energy Research Vol 3, edited by Mat Santamouris. Hoboken: Earthscan. Milne, Murray., Liggett, Robin., and Al-Shaali, Rashed. 2008 Climate Consultant 3.0: A Tool For Visualizing Building Energy Implications Of Climates. LA: UCLA Department 137 of Architecture and Urban Design Morphopedia. 2012 "Caltrans District 7 Headquarters." Accessed Aug. 18. http://morphopedia.com/projects/caltrans-district-7-headquarters ONSET HOBO Data Loggers. 2010. "HOBO U12 Temperature Data Logger - U12-001" Accessed October 25. http://www.onsetcomp.com/products/data-loggers/u12-001 Preiser, Wolfgang F. E., Harvey Z. Rabinowitz., and Edward T. White.1988. Post Occupancy Evaluation. New York: Van Nostrand Reinhold Post Occupancy Evaluation. 2011 "Getting results from Post Occupancy Evaluation" Accessed March 22 http://www.postoccupancyevaluation.com/results.shtml Pacific Gas and Electric Company. 2009 "Guide to California Climate Zones." Accessed November 16 http://www.pge.com/mybusiness/edusafety/training/pec/toolbox/arch /climate/index.shtml The American Institute of Architects. 2009. "Energy-Modeling" Accessed Jan. 20 2011 Http://wiki.aia.org/wiki%20pages/energy%20modeling.aspx Yang, Guang. 2012. "Energy Simulation in Existing Buildings: Calibrating the Model for Retrofit Studies." Thesis. University of Southern California.
Abstract (if available)
Abstract
Buildings account for about 40 percent of total U.S. energy consumption. It is therefore important to shift our focus on important measures that can be taken to make buildings more energy efficient. With the rise in number of buildings day by day and the dwindling resources, retrofitting buildings is the key to an energy efficiency future. Post occupancy evaluation (POE) is an important tool and is ideal for the retrofitting process. POE would help to identify the problem areas in the building and enable researchers and designers to come up with solutions addressing the inefficient energy usage as well as the overall wellbeing of the users of the building. The post occupancy energy evaluation of Ronald Tutor Hall (RTH) located at the University of Southern California is one small step in that direction. RTH was chosen to study because
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Dulom, Duyum
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Post occupancy energy evaluation of Ronald Tutor Hall using eQUEST; computer based simulation of existing building and comparison of data
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School of Architecture
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Master of Building Science
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Building Science
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01/30/2013
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01/21/2013
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calibration,energy simulation,OAI-PMH Harvest,post occupancy evaluation,Ronald Tutor Hall,thermal comfort
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Tags
calibration
energy simulation
post occupancy evaluation
Ronald Tutor Hall
thermal comfort