TY - JOUR T1 - Culture, conformity, and carbon? A multi-country analysis of heating and cooling practices in office buildings JF - Energy Research & Social Science Y1 - 2020 A1 - Chen, Chien-fei A1 - Tianzhen Hong A1 - de Rubens, Gerardo Zarazua A1 - Yilmaz, Selin A1 - Bandurski, Karol A1 - Bélafi, Zsófia Deme A1 - De Simone, Marilena A1 - Bavaresco, Mateus Vinícius A1 - Wang, Yu A1 - Liu, Pei-ling A1 - Barthelmes, Verena M. A1 - Adams, Jacqueline A1 - D'Oca, Simona A1 - Przybylski, Łukasz AB -

This study investigates human-building interaction in office spaces across multiple countries including Brazil, Italy, Poland, Switzerland, the United States, and Taiwan. We analyze social-psychological, contextual, and demographic factors to explain cross-country differences in adaptive thermal actions (i.e. cooling and heating behaviors) and conformity to the norms of sharing indoor environmental control features, an indicator of energy consumption. Specifically, personal adjustments such as putting on extra clothes are generally preferred over technological solutions such as adjusting thermostats in reaction to thermal discomfort. Social-psychological factors including attitudes, perceived behavioral control, injunctive norms, and perceived impact of indoor environmental quality on work productivity influence occupants’ intention to conform to the norms of sharing environmental control features. Lastly, accessibility to environmental control features, office type, gender, and age are also important factors. These findings demonstrate the roles of social-psychological and certain contextual factors in occupants’
interactions with building design as well as their behavior of sharing environmental control features, both of which significantly influence building energy consumption, and thus, broader decarbonization.

VL - 61 JO - Energy Research & Social Science ER - TY - JOUR T1 - Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems JF - Applied Energy Y1 - 2019 A1 - David Blum A1 - K. Arendt A1 - Lisa Rivalin A1 - Mary Ann Piette A1 - Michael Wetter A1 - C.T. Veje KW - building simulation KW - hvac KW - Model predictive control KW - System identification AB -

Model predictive control (MPC) for buildings is attracting significant attention in research and industry due to its potential to address a number of challenges facing the building industry, including energy cost reduction, grid integration, and occupant connectivity. However, the strategy has not yet been implemented at any scale, largely due to the significant effort required to configure and calibrate the model used in the MPC controller. While many studies have focused on methods to expedite model configuration and improve model accuracy, few have studied the impact a wide range of factors have on the accuracy of the resulting model. In addition, few have continued on to analyze these factors' impact on MPC controller performance in terms of final operating costs. Therefore, this study first identifies the practical factors affecting model setup, specifically focusing on the thermal envelope. The seven that are identified are building design, model structure, model order, data set, data quality, identification algorithm and initial guesses, and software tool-chain. Then, through a large number of trials, it analyzes each factor's influence on model accuracy, focusing on grey-box models for a single zone building envelope. Finally, this study implements a subset of the models identified with these factor variations in heating, ventilating, and air conditioning MPC controllers, and tests them in simulation of a representative case that aims to optimally cool a single-zone building with time-varying electricity prices. It is found that a difference of up to 20% in cooling cost for the cases studied can occur between the best performing model and the worst performing model. The primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.

VL - 236 UR - https://linkinghub.elsevier.com/retrieve/pii/S0306261918318099https://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/plain JO - Applied Energy ER - TY - CONF T1 - Prototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings T2 - IBPSA Building Simulation 2019 Y1 - 2019 A1 - David Blum A1 - Filip Jorissen A1 - Sen Huang A1 - Yan Chen A1 - Javier Arroyo A1 - Kyle Benne A1 - Yanfei Li A1 - Valentin Gavan A1 - Lisa Rivalin A1 - Lieve Helsen A1 - Draguna Vrabie A1 - Michael Wetter A1 - Marina Sofos KW - benchmarking KW - building simulation KW - Model predictive control KW - software development AB -

Advanced control strategies are becoming increasingly necessary in buildings in order to meet and balance requirements for energy efficiency, demand flexibility, and occupant comfort. Additional development and widespread adoption of emerging control strategies, however, ultimately require low implementation costs to reduce payback period and verified performance to gain control vendor, building owner, and operator trust. This is difficult in an already first-cost driven and risk-averse industry. Recent innovations in building simulation can significantly aid in meeting these requirements and spurring innovation at early stages of development by evaluating performance, comparing state-of-the-art to new strategies, providing installation experience, and testing controller implementations. This paper presents the development of a simulation framework consisting of test cases and software platform for the testing of advanced control strategies (BOPTEST - Building Optimization Performance Test). The objectives and requirements of the framework, components of a test case, and proposed software platform architecture are described, and the framework is demonstrated with a prototype implementation and example test case.

JF - IBPSA Building Simulation 2019 CY - Rome, Italy ER - TY - JOUR T1 - Clustering and statistical analyses of air-conditioning intensity and use patterns in residential buildings JF - Energy and Buildings Y1 - 2018 A1 - Jingjing An A1 - Da Yan A1 - Tianzhen Hong KW - AC usage benchmarking KW - Air-conditioning KW - Clustering analysis KW - KPIs KW - residential building KW - Use pattern AB -

Energy conservation in residential buildings has gained increased attention due to its large portion of global energy use and potential of energy savings. Occupant behavior has been recognized as a key factor influencing the energy use and load diversity in buildings, therefore more realistic and accurate air-conditioning (AC) operating schedules are imperative for load estimation in equipment design and operation optimization. With the development of sensor technology, it became easier to access an increasing amount of heating/cooling data from thermal energy metering systems in residential buildings, which provides another possible way to understand building energy usage and occupant behaviors. However, except for cooling energy consumption benchmarking, there currently lacks effective and easy approaches to analyze AC usage and provide actionable insights for occupants. To fill this gap, this study proposes clustering analysis to identify AC use patterns of residential buildings, and develops new key performance indicators (KPIs) and data analytics to explore the AC operation characteristics using the long-term metered cooling energy use data, which is of great importance for inhabitants to understand their thermal energy use and save energy cost through adjustment of their AC use behavior. We demonstrate the proposed approaches in a residential district comprising 300 apartments, located in Zhengzhou, China. Main outcomes include: Representative AC use patterns are developed for three room types of residential buildings in the cold climate zone of China, which can be used as more realistic AC schedules to improve accuracy of energy simulation; Distributions of KPIs on household cooling energy usage are established, which can be used for household AC use intensity benchmarking and performance diagnoses.

VL - 174 UR - https://linkinghub.elsevier.com/retrieve/pii/S0378778818307199https://api.elsevier.com/content/article/PII:S0378778818307199?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0378778818307199?httpAccept=text/plain JO - Energy and Buildings ER - TY - JOUR T1 - Comparative Study of Air-Conditioning Energy Use of Four Office Buildings in China and USA JF - Energy and Buildings Y1 - 2018 A1 - Xin Zhou A1 - Da Yan A1 - Jingjing An A1 - Tianzhen Hong A1 - Xing Shi A1 - Xing Jin KW - Building envelope KW - climate KW - energy consumption KW - occupant behavior KW - office buildings KW - technological choice AB -

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. This study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead to AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. Overall, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.

VL - 169 ER - TY - JOUR T1 - Translating climate change and heating system electrification impacts on building energy use to future greenhouse gas emissions and electric grid capacity requirements in California JF - Applied Energy Y1 - 2018 A1 - Brian Tarroja A1 - Felicia Chiang A1 - Amir AghaKouchak A1 - Scott Samuelsen A1 - Shuba V. Raghavan A1 - Max Wei A1 - Kaiyu Sun A1 - Tianzhen Hong KW - Building Energy Demand KW - Climate Change Impacts KW - electric grid KW - Heating Electrification Effects AB -

Climate change and increased electrification of space and water heating in buildings can significantly affect future electricity demand and hourly demand profiles, which has implications for electric grid greenhouse gas emissions and capacity requirements. We use EnergyPlus to quantify building energy demand under historical and under several climate change projections of 32 kinds of building prototypes in 16 different climate zones of California and imposed these impacts on a year 2050 electric grid configuration by simulation in the Holistic Grid Resource Integration and Deployment (HIGRID) model. We find that climate change only prompted modest increases in grid resource capacity and negligible difference in greenhouse gas emissions since the additional electric load generally occurred during times with available renewable generation. Heating electrification, however, prompted a 30–40% reduction in greenhouse gas emissions but required significant grid resource capacity increases, due to the higher magnitude of load increases and lack of readily available renewable generation during the times when electrified heating loads occurred. Overall, this study translates climate change and electrification impacts to system-wide endpoint impacts on future electric grid configurations and highlights the complexities associated with translating building-level impacts to electric system-wide impacts.

VL - 225 UR - https://linkinghub.elsevier.com/retrieve/pii/S0306261918306962https://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/plain JO - Applied Energy ER - TY - JOUR T1 - Energy saving potential of a two-pipe system for simultaneous heating and cooling of office buildings JF - Energy and Buildings Y1 - 2017 A1 - Alessandro Maccarini A1 - Michael Wetter A1 - Alireza Afshari A1 - Goran Hultmark A1 - Niels Bergsoe A1 - Anders Vorre KW - active beams KW - energy saving KW - HVAC systems KW - low-exergy KW - modelica KW - simulation AB -

This paper analyzes the performance of a novel two-pipe system that operates one water loop to simultaneously provide space heating and cooling with a water supply temperature of around 22 °C. To analyze the energy performance of the system, a simulation-based research was conducted. The two-pipe system was modelled using the equation-based Modelica modeling language in Dymola. A typical office building model was considered as the case study. Simulations were run for two construction sets of the building envelope and two conditions related to inter-zone air flows. To calculate energy savings, a conventional four-pipe system was modelled and used for comparison. The conventional system presented two separated water loops for heating and cooling with supply temperatures of 45 °C and 14 °C, respectively. Simulation results showed that the two-pipe system was able to use less energy than the four-pipe system thanks to three effects: useful heat transfer from warm to cold zones, higher free cooling potential and higher efficiency of the heat pump. In particular, the two-pipe system used approximately between 12% and 18% less total annual primary energy than the four-pipe system, depending on the simulation case considered.

VL - 134 JO - Energy and Buildings ER - TY - RPRT T1 - A Novel Stochastic Modeling Method to Simulate Cooling Loads in Residential Districts Y1 - 2017 A1 - Jingjing An A1 - Da Yan A1 - Tianzhen Hong A1 - Kaiyu Sun AB -

District cooling systems are widely used in urban residential communities in China. Most district cooling systems are oversized;this leads to wasted investment and low operational efficiency and thus energy wastage. The accurate prediction of district cooling loads that supports rightsizing cooling plant equipment remains a challenge. This study developed a new stochastic modeling method that includes (1) six prototype house models representing a majority of apartments in the district, (2)occupant behavior models in residential buildings reflecting the temporal and spatial diversity and complexity based on a large-scale residential survey in China, and (3) a stochastic sampling process to represent all apartments and occupants in the district. The stochastic method was employed in a case study using the DeST simulation engine to simulate the cooling loads of a real residential district in Wuhan, China. The simulation results agree well with the actual measurement data based on five performance metrics representing the aggregated cooling loads, the peak cooling loads as well as the spatial load distribution,and the load profiles. Two currently used simulation methods were also employed to simulate the district cooling loads. The simulation results showed that oversimplified occupant behavior assumptions lead to significant overestimations of the peak cooling load and total district cooling loads. Future work will aim to simplify the workflow and data requirements of the stochastic method to enable its practical application as well as explore its application in predicting district heating loads and in commercial or mixed-use districts.

ER - TY - JOUR T1 - Spatial Distribution of Internal Heat Gains: A Probabilistic Representation and Evaluation of Its Influence on Cooling Equipment Sizing in Large Office Buildings JF - Energy and Buildings Y1 - 2017 A1 - Qi Zhang A1 - Da Yan A1 - Jingjing An A1 - Tianzhen Hong A1 - Wei Tian A1 - Kaiyu Sun KW - air handling unit KW - chiller plant KW - equipment sizing KW - internal heat gain KW - spatial distribution KW - spatial diversity KW - stochastic AB -

Internal heat gains from occupants, lighting, and plug loads are significant components of the space cooling load in an office building. Internal heat gains vary with time and space. The spatial diversity is significant, even for spaces with the same function in the same building. The stochastic nature of internal heat gains makes determining the peak cooling load to size air-conditioning systems a challenge. The traditional conservative practice of considering the largest internal heat gain among spaces and applying safety factors overestimates the space cooling load, which leads to oversized air-conditioning equipment and chiller plants. In this study, a field investigation of several large office buildings in China led to the development of a new probabilistic approach that represents the spatial diversity of the design internal heat gain of each tenant as a probability distribution function. In a large office building, a central chiller plant serves all air handling units (AHUs), with each AHU serving one or more floors of the building. Therefore, the spatial diversity should be considered differently when the peak cooling loads to size the AHUs and chillers are calculated. The proposed approach considers two different levels of internal heat gains to calculate the peak cooling loads and size the AHUs and chillers in order to avoid oversizing, improve the overall operating efficiency, and thus reduce energy use.

ER - TY - JOUR T1 - A Thorough Assessment of China’s Standard for Energy Consumption of Buildings JF - Energy and Buildings Y1 - 2017 A1 - Da Yan A1 - Tianzhen Hong A1 - Cheng Li A1 - Qi Zhang A1 - Jingjing An A1 - shan Hu KW - China KW - code and standard KW - energy consumption KW - energy efficiency KW - Energy Use Intensity KW - outcome-based code AB -

China’s Design Standard for Energy Efficiency of Public Buildings (the Design Standard) is widely used in the design phase to regulate the energy efficiency of physical assets (envelope, lighting, HVAC) in buildings. However, the standard does not consider many important factors that influence the actual energy use in buildings, and this can lead to gaps between the design estimates and actual energy consumption. To achieve the national energy savings targets defined in the strategic 12th Five-Year Plan, China developed the first standard for energy consumption of buildings GB/T51161-2016 (the Consumption Standard). This study provides an overview of the Consumption Standard, identifies its strengths and weaknesses, and recommends future improvements. The analysis and discussion of the constraint value and the leading value, two key indicators of the energy use intensity, provide insight into the intent and effectiveness of the Consumption Standard. The results indicated that consistency between China’s Design Standard GB 50189-2015 and the Consumption Standard GB/T51161-2016 could be achieved if the Design Standard used the actual building operations and occupant behavior in calculating the energy use in Chinese buildings. The development of an outcome-based code in the U.S. was discussed in comparison with China’s Consumption Standard, and this revealed the strengths and challenges associated with implementing a new compliance method based on actual energy use in buildings in the U.S. Overall, this study provides important insights into the latest developments of actual consumption-based building energy standards, and this information should be valuable to building designers and energy policy makers in China and the U.S.

ER - TY - CONF T1 - Application of a stochastic window use model in EnergyPlus T2 - SimBuild 2012, 5th National Conference of IBPSA-USA, August 1-3, 2012 Y1 - 2012 A1 - Spencer M. Dutton A1 - Hui Zhang A1 - Yongchao Zhai A1 - Edward A. Arens A1 - Youness Bennani Smires A1 - Samuel L. Brunswick A1 - Kyle S. Konis A1 - Philip Haves AB -

Natural ventilation, used appropriately, has the potential to provide both significant HVAC energy savings, and improvements in occupant satisfaction.

Central to the development of natural ventilation models is the need to accurately represent the behavior of building occupants. The work covered in this paper describes a method of implementing a stochastic window model in EnergyPlus. Simulated window use data from three stochastic window opening models was then compared to measured window opening behavior, collected in a naturally-ventilated office in California. Recommendations regarding the selection of stochastic window use models, and their implementation in EnergyPlus, are presented.

JF - SimBuild 2012, 5th National Conference of IBPSA-USA, August 1-3, 2012 CY - Madison, WI UR - https://escholarship.org/uc/item/2gm7r783 ER - TY - JOUR T1 - Modeling and Measurement Constraints in Fault Diagnostics for HVAC Systems JF - ASME Journal of Dynamic Systems, Measurement, and Controls Y1 - 2010 A1 - Massieh Najafi A1 - David M. Auslander A1 - Peter L. Bartlett A1 - Philip Haves A1 - Michael D. Sohn AB - Many studies have shown that energy savings of five to fifteen percent are achievable in commercial buildings by detecting and correcting building faults, and optimizing building control systems. However,in spite of good progress in developing tools for determining HVAC diagnostics, methods to detect faults in HVAC systems are still generally undeveloped. Most approaches use numerical filtering or parameter estimation methods to compare data from energy meters and building sensors to predictions from mathematical or statistical models. They are effective when models are relatively accurate and data contain few errors. In this paper, we address the case where models are imperfect and data are variable, uncertain, and can contain error. We apply a Bayesian updating approach that is systematic in managing and accounting for most forms of model and data errors. The proposed method uses both knowledge of first principle modeling and empirical results to analyze the system performance within the boundaries defined by practical constraints. We demonstrate the approach by detecting faults in commercial building air handling units. We find that the limitations that exist in air handling unit diagnostics due to practical constraints can generally be effectively addressed through the proposed approach. ER - TY - JOUR T1 - A Statistical Pattern Analysis Framework for Rooftop Unit Diagnostics JF - International Journal of Heating, Ventilating, Air-Conditioning and Refrigeration Research Y1 - 2010 A1 - Massieh Najafi A1 - David M. Auslander A1 - Philip Haves A1 - Michael D. Sohn ER - TY - Generic T1 - Systems Approach to Energy Efficient Building Operation: Case Studies and Lessons Learned in a University Campus T2 - 2010 ACEEE Summer Study on Energy Efficiency in Buildings Y1 - 2010 A1 - Satish Narayanan A1 - Michael G. Apte A1 - Philip Haves A1 - Mary Ann Piette A1 - John Elliott AB -

This paper reviews findings from research conducted at a university campus to develop a robust systems approach to monitor and continually optimize building energy performance. The field analysis, comprising three projects, included detailed monitoring, model-based analysis of system energy performance, and implementation of optimized control strategies for both district and building-scale systems. One project used models of the central cooling plant and campus building loads, and weather forecasts to analyze and optimize the energy performance of a district cooling system, comprising chillers, pumps and a thermal energy storage system. Fullscale implementation of policies devised with a model predictive control approach produced energy savings of about 5%, while demonstrating that the heuristic policies implemented by the operators were close to optimal during peak cooling season and loads. Research was also conducted to evaluate whole building monitoring and control methods. A second project performed in a campus building combined sub-metered end-use data, performance benchmarks, energy simulations and thermal load estimators to create a web-based energy performance visualization tool prototype. This tool provides actionable energy usage information to aid in facility operation and to enable performance improvement. In a third project, an alternative to demand controlled ventilation enabled by direct measurements of building occupancy levels was assessed. Simulations were used to show 5-15% reduction in building HVAC system energy usage when using estimates of actual occupancy levels.

JF - 2010 ACEEE Summer Study on Energy Efficiency in Buildings PB - Omnipress CY - Asilomar, California, USA SN - 0-918249-60-0 ER - TY - JOUR T1 - Towards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning JF - Building Research and Information Y1 - 2009 A1 - Brian E. Coffey A1 - Sam Borgeson A1 - Stephen E. Selkowitz A1 - Joshua S. Apte A1 - Paul A. Mathew A1 - Philip Haves AB -

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

VL - 37:5 ER - TY - Generic T1 - Application of Machine Learning in Fault Diagnostics of Mechanical Systems T2 - International Conference on Modeling, Simulation and Control Y1 - 2008 A1 - Massieh Najafi A1 - David M. Auslander A1 - Peter L. Bartlett A1 - Philip Haves JF - International Conference on Modeling, Simulation and Control ER - TY - Generic T1 - Fault Diagnostics and Supervised Testing: How Fault Diagnostic tools can be Proactive? T2 - Eleventh International Conference on Intelligent Systems and Controls Y1 - 2008 A1 - Massieh Najafi A1 - David M. Auslander A1 - Peter L. Bartlett A1 - Philip Haves AB - The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems. JF - Eleventh International Conference on Intelligent Systems and Controls UR - http://www.actapress.com/Content_of_Proceeding.aspx?proceedingID=503 ER - TY - Generic T1 - Overcoming the Complexity of Diagnostic Problems due to Sensor Network Architecture T2 - Eleventh International Conference on Intelligent Systems and Controls Y1 - 2008 A1 - Massieh Najafi A1 - David M. Auslander A1 - Peter L. Bartlett A1 - Philip Haves AB -

In fault detection and diagnostics, limitations coming from the sensor network architecture are one of the main challenges in evaluating a system's health status. Usually the design of the sensor network architecture is not solely based on diagnostic purposes, other factors like controls, financial constraints, and practical limitations are also involved. As a result, it quite common to have one sensor (or one set of sensors) monitoring the behaviour of two or more components. This can significantly extend the complexity of diagnostic problems. In this paper a systematic approach is presented to deal with such complexities. It is shown how the problem can be formulated as a Bayesian network based diagnostic mechanism with latent variables. The developed approach is also applied to the problem of fault diagnosis in HVAC systems, an application area with considerable modeling and measurement constraints.

JF - Eleventh International Conference on Intelligent Systems and Controls UR - https://www.actapress.com/Content_Of_Proceeding.aspx?ProceedingID=503 ER - TY - CONF T1 - Energy Index Evaluation of Buildings in Function of the External Temperature T2 - Proc. Building Simulation 2007 Y1 - 2007 A1 - Papa, Renata Pietra A1 - Patricia Romeiro da Silva Jota A1 - Assis, Eleonora JF - Proc. Building Simulation 2007 CY - Beijing, China ER - TY - RPRT T1 - Energy Performance of Underfloor Air Distribution Systems Y1 - 2007 A1 - Fred S. Bauman A1 - Thomas L. Webster A1 - Hui Jin A1 - Wolfgang Lukaschek A1 - Corinne Benedek A1 - Edward A. Arens A1 - Paul F. Linden A1 - Anna Lui A1 - Walter F. Buhl A1 - Darryl J. Dickerhoff PB - California Energy Commission - Public Interest Energy Research Program ER - TY - CONF T1 - Simulation Enhanced Prototyping of an Experimental Solar House T2 - Proc. Building Simulation 2007 Y1 - 2007 A1 - Ruchi Choudhary A1 - Godfried Augenbroe A1 - Russell Gentry A1 - Huafen Hu JF - Proc. Building Simulation 2007 CY - Beijing, China ER - TY - Generic T1 - Carbon Nanotube (CNT)-Centric Thermal Management of Future High Power Microprocessors T2 - IEEE CPMT International Symposium and Exhibition on Advanced Packaging Materials Y1 - 2006 A1 - Prajesh Bhattacharya A1 - Wei, X. A1 - Andrei G. Fedorov A1 - Yogendra K. Joshi A1 - Navdeep Bajwa A1 - Anyuan Cao A1 - Pulickel Ajayan JF - IEEE CPMT International Symposium and Exhibition on Advanced Packaging Materials CY - Atlanta, GA ER - TY - CONF T1 - Parametric Analysis of a Solar Desiccant Cooling System using the SimSPARK Environment T2 - IBPSA Building Simulation 2005 Y1 - 2005 A1 - Etienne Wurtz A1 - Chadi Maalouf A1 - Laurent Mora A1 - Francis Allard JF - IBPSA Building Simulation 2005 CY - Montreal, Canada ER - TY - Generic T1 - Comparison of a generalized pattern search and a genetic algorithm optimization method T2 - Proc. of the 8th IBPSA Conference Y1 - 2003 A1 - Michael Wetter A1 - Jonathan A. Wright ED - Godfried Augenbroe ED - Jan Hensen AB -

Building and HVAC system design can significantly improve if numerical optimization is used. However, if a cost function that is smooth in the design parameter is evaluated by a building energy simulation program, it usually becomes replaced with a numerical approximation that is discontinuous in the design parameter. Moreover, many building simulation programs do not allow obtaining an error bound for the numerical approximations to the cost function. Thus, if a cost function is evaluated by such a program, optimization algorithms that depend on smoothness of the cost function can fail far from a minimum.

For such problems it is unclear how the Hooke-Jeeves Generalized Pattern Search optimization algorithm and the simple Genetic Algorithm perform. The Hooke-Jeeves algorithm depends on smoothness of the cost function, whereas the simple Genetic Algorithm may not even converge if the cost function is smooth. Therefore, we are interested in how these algorithms perform if used in conjunction with a cost function evaluated by a building energy simulation program.

In this paper we show what can be expected from the two algorithms and compare their performance in minimizing the annual primary energy consumption of an office building in three locations. The problem has 13 design parameters and the cost function has large discontinuities. The optimization algorithms reduce the energy consumption by 7% to 32%, depending on the building location. Given the short labor time to set up the optimization problems, such reductions can yield considerable economic gains.

JF - Proc. of the 8th IBPSA Conference CY - Eindhoven, Netherlands VL - III UR - http://www.ibpsa.org/proceedings/BS2003/BS03_1401_1408.pdf ER - TY - Generic T1 - A convergent optimization method using pattern search algorithms with adaptive precision simulation T2 - Proceedings of the 8th IBPSA Conference Y1 - 2003 A1 - Michael Wetter A1 - Elijah Polak ED - Godfried Augenbroe ED - Jan Hensen KW - coordinate search KW - direct search KW - genetic algorithm KW - hooke–jeeves KW - optimization KW - particle swarm optimization AB -

In solving optimization problems for building design and control, the cost function is often evaluated using a detailed building simulation program. These programs contain code features that cause the cost function to be discontinuous. Optimization algorithms that require smoothness can fail on such problems. Evaluating the cost function is often so time-consuming that stochastic optimization algorithms are run using only a few simulations, which decreases the probability of getting close to a minimum. To show how applicable direct search, stochastic, and gradient-based optimization algorithms are for solving such optimization problems, we compare the performance of these algorithms in minimizing cost functions with different smoothness. We also explain what causes the large discontinuities in the cost functions.

JF - Proceedings of the 8th IBPSA Conference CY - Eindhoven, Netherlands VL - III ER - TY - CONF T1 - Thermal Energy Storage System Sizing T2 - IBPSA Building Simulation '89 Y1 - 1989 A1 - Dominique Dumortier A1 - Ron C. Kammerud A1 - Birdsall, Bruce E. A1 - Brandt Andersson A1 - Joseph H. Eto A1 - William L. Carroll A1 - Frederick C. Winkelmann JF - IBPSA Building Simulation '89 CY - Vancouver, BC, Canada UR - http://www.ibpsa.org/proceedings/BS1989/BS89_357_362.pdf U2 - LBNL-27203 ER -