<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chen, Chien-fei</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">de Rubens, Gerardo Zarazua</style></author><author><style face="normal" font="default" size="100%">Yilmaz, Selin</style></author><author><style face="normal" font="default" size="100%">Bandurski, Karol</style></author><author><style face="normal" font="default" size="100%">Bélafi, Zsófia Deme</style></author><author><style face="normal" font="default" size="100%">De Simone, Marilena</style></author><author><style face="normal" font="default" size="100%">Bavaresco, Mateus Vinícius</style></author><author><style face="normal" font="default" size="100%">Wang, Yu</style></author><author><style face="normal" font="default" size="100%">Liu, Pei-ling</style></author><author><style face="normal" font="default" size="100%">Barthelmes, Verena M.</style></author><author><style face="normal" font="default" size="100%">Adams, Jacqueline</style></author><author><style face="normal" font="default" size="100%">D&#039;Oca, Simona</style></author><author><style face="normal" font="default" size="100%">Przybylski, Łukasz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Culture, conformity, and carbon? A multi-country analysis of heating and cooling practices in office buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Energy Research &amp; Social Science</style></secondary-title><short-title><style face="normal" font="default" size="100%">Energy Research &amp; Social Science</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-03-2020</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">101344</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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’&lt;br /&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Olivier Van Cutsem</style></author><author><style face="normal" font="default" size="100%">Maher Kayal</style></author><author><style face="normal" font="default" size="100%">David Blum</style></author><author><style face="normal" font="default" size="100%">Marco Pritoni</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of MPC Formulations for Building Control under Commercial Time-of-Use Tariffs</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE PowerTech Milan 2019</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">commercial building</style></keyword><keyword><style  face="normal" font="default" size="100%">demand charge</style></keyword><keyword><style  face="normal" font="default" size="100%">Model predictive control (MPC)</style></keyword><keyword><style  face="normal" font="default" size="100%">peak demand</style></keyword><keyword><style  face="normal" font="default" size="100%">time-of-use tarrif</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Most medium and large commercial buildings in&amp;nbsp;the U.S. are subject to complex electricity tariffs that combine&amp;nbsp;both Time-of-Use (TOU) energy and demand charges. This study&amp;nbsp;analyses the performances of different economic Model Predictive&amp;nbsp;Control (MPC) formulations, from the standpoints of monthly bill&amp;nbsp;reduction, load shifting, and peak demand reduction. Simulations&amp;nbsp;are performed on many simplified commercial building models,&amp;nbsp;with multiple TOU demand charges, and under various summer&amp;nbsp;conditions. Results show that compared to energy-only MPC, the&amp;nbsp;traditional method for dealing with demand charges significantly&lt;br /&gt;reduces peak demand and owner bill, however, highlight a lack&amp;nbsp;of load shifting capability. A proposed incremental approach&lt;br /&gt;is presented, which better balances the bill components in the&amp;nbsp;objective function. In the case study presented, this method&lt;br /&gt;can improve monthly bill savings and increase load shifting&amp;nbsp;during demand response events, while keeping a similarly low&lt;br /&gt;peak demand, compared to traditional MPC methods taking into&amp;nbsp;account demand charges.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wang, Wei</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Xu, Ning</style></author><author><style face="normal" font="default" size="100%">Xu, Xiaodong</style></author><author><style face="normal" font="default" size="100%">Chen, Jiayu</style></author><author><style face="normal" font="default" size="100%">Shan, Xiaofang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering</style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title><short-title><style face="normal" font="default" size="100%">Building and Environment</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">data fusion</style></keyword><keyword><style  face="normal" font="default" size="100%">Feature selection</style></keyword><keyword><style  face="normal" font="default" size="100%">Machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">occupancy prediction</style></keyword><keyword><style  face="normal" font="default" size="100%">Physics-based model</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-09-2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">162</style></volume><pages><style face="normal" font="default" size="100%">106280</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span&gt;Fusing various sensing data sources can significantly improve the accuracy and reliability of building occupancy detection. Fusing environmental sensors and wireless network signals are seldom studied for its computational and technical complexity. This study aims to propose an integrated adaptive lasso model that is able to extract critical data features for environmental and Wi-Fi probe dual sensing sources. Through rapid feature extraction and process simplification, the proposed method aims to improve the computational efficiency of occupancy detecting models. To validate the proposed model, an onsite experiment was conducted to examine two occupancy data resolutions, (real-time and four-level occupancy resolutions). The results suggested that, among all twelve features, eight features are most relevant. The mean absolute error of the real-time occupancy can be reduced to 2.18 and F1_accuracy is about 84.36% for the four-level occupancy.&lt;/span&gt;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jingjing An</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Clustering and statistical analyses of air-conditioning intensity and use patterns in residential buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title><short-title><style face="normal" font="default" size="100%">Energy and Buildings</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">AC usage benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">Air-conditioning</style></keyword><keyword><style  face="normal" font="default" size="100%">Clustering analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">KPIs</style></keyword><keyword><style  face="normal" font="default" size="100%">residential building</style></keyword><keyword><style  face="normal" font="default" size="100%">Use pattern</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">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</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">174</style></volume><pages><style face="normal" font="default" size="100%">214 - 227</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xin Zhou</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author><author><style face="normal" font="default" size="100%">Jingjing An</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Xing Shi</style></author><author><style face="normal" font="default" size="100%">Xing Jin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparative Study of Air-Conditioning Energy Use of Four Office Buildings in China and USA</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Building envelope</style></keyword><keyword><style  face="normal" font="default" size="100%">climate</style></keyword><keyword><style  face="normal" font="default" size="100%">energy consumption</style></keyword><keyword><style  face="normal" font="default" size="100%">occupant behavior</style></keyword><keyword><style  face="normal" font="default" size="100%">office buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">technological choice</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><volume><style face="normal" font="default" size="100%">169</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Milica Grahovac</style></author><author><style face="normal" font="default" size="100%">Jianjun Hu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Control Description Language</style></title><secondary-title><style face="normal" font="default" size="100%">1st American Modelica Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">controls</style></keyword><keyword><style  face="normal" font="default" size="100%">hvac</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://simulationresearch.lbl.gov/wetter/download/2018-americanModelica-WetterGrahovacHu.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Properly designed and implemented building control sequences can significantly reduce energy consumption. However, there is currently no process with supporting tools that allows the assessment of the performance of different control sequences, export the control sequences in a vendor-neutral format for cost estimation and for implementation on a building automation system through machine-to-machine translation, and reuse the sequences for verification during commissioning.&lt;/p&gt;&lt;p&gt;This paper describes a Control Description Language (CDL) that we developed to create such a process. For CDL, we selected a subset of Modelica that allows a convenient representation of control sequences, simulation of the control sequence coupled to a building energy model, and development of translators from CDL to building automation systems. To aid in the development of such translators, we created a translator from CDL to a JSON intermediate format. In future work, we seek to work with building control providers to develop translators from CDL to commercial building automation systems.&lt;/p&gt;&lt;p&gt;Through a case study, we show that CDL suffices for simulation-based performance assessment of two ASHRAE-published control sequences for a variable air volume flow system of an office building. Moreover, the case study showed that merely due to differences in the control sequences, annual HVAC energy use was reduced by 30%. This difference is larger than the accuracy required when comparing different HVAC systems, thereby questioning the current practice of idealizing control sequences in building energy simulations, and demonstrating the importance of ensuring that the control sequence used during design simulations corresponds to the control sequence that will be implemented in the real building&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-2001219</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zsofia Belafi</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Andras Reith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A critical review on questionnaire surveys in the field of energy-related occupant behaviour</style></title><secondary-title><style face="normal" font="default" size="100%">Energy Efficiency</style></secondary-title><short-title><style face="normal" font="default" size="100%">Energy Efficiency</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">behaviour modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">energy efficiency</style></keyword><keyword><style  face="normal" font="default" size="100%">Energy use in buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">occupant behavior</style></keyword><keyword><style  face="normal" font="default" size="100%">questionnaire survey</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://link.springer.com/10.1007/s12053-018-9711-zhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/article/10.1007/s12053-018-9711-z/fulltext.html</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">1-21</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Occupants perform various actions to satisfy their physical and non-physical needs in buildings. These actions greatly affect building operations and thus energy use. Clearly understanding and accurately modelling occupant behaviour in buildings are crucial to guide energy-efficient building design and operation, and to reduce the gap between design and actual energy performance of buildings. To study and understand occupant behaviour, a cross-sectional questionnaire survey is one of the most useful tools to gain insights on general behaviour patterns and drivers, and to find connections between human, social and local comfort parameters. In this study, 33 projects were reviewed from the energy-related occupant behaviour research literature that employed cross-sectional surveys or interviews for data collection from the perspective of findings, limitations and methodological challenges. This research shows that future surveys are needed to bridge the gaps in literature but they would need to encompass a multidisciplinary approach to do so as until now only environmental and engineering factors were considered in these studies. Insights from social practice theories and techniques must be acquired to deploy robust and unbiased questionnaire results, which will provide new, more comprehensive knowledge in the field, and therefore occupant behaviour could be better understood and represented in building performance simulation to support design and operation of low or net-zero energy buildings.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ying Cui</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Chan Xiao</style></author><author><style face="normal" font="default" size="100%">Xuan Luo</style></author><author><style face="normal" font="default" size="100%">Qi Zhang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Actual weather data</style></keyword><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">energy use</style></keyword><keyword><style  face="normal" font="default" size="100%">Multiyear simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Peak load  </style></keyword><keyword><style  face="normal" font="default" size="100%">Typical year</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2017</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">195</style></volume><pages><style face="normal" font="default" size="100%">890-904</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xinqiao Yu</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author><author><style face="normal" font="default" size="100%">Kaiyu Sun</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Dandan Zhu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Comparative Study on Energy Performance of Variable Refrigerant Flow Systems and Variable Air Volume Systems in Office Buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">comparative analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">energy performance</style></keyword><keyword><style  face="normal" font="default" size="100%">field measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">Variable Air Volume (VAV) Systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Variable Refrigerant Flow (VRF) Systems</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Variable air volume (VAV) systems and variable refrigerant flow (VRF) systems are popularly used in office buildings. This study investigated VAV and VRF systems in five typical office buildings in China, and compared their air conditioning energy use. Site survey and field measurements were conducted to collect data of building characteristics and operation. Measured cooling electricity use was collected from sub-metering in the five buildings. The sub-metering data, normalized by climate and operating hours, show that VRF systems consumed much less air conditioning energy by up to 70% than VAV systems. This is mainly due to the different operation modes of both system types leading to much fewer operating hours of the VRF systems. Building simulation was used to quantify the impact of operation modes of VRF and VAV systems on cooling loads using a prototype office building in China. Simulated results show the VRF operation mode leads to much less cooling loads than the VAV operation mode, by 42% in Hong Kong and 53% in Qingdao. The VRF systems operated in the part-time-part-space mode enabling occupants to turn on air-conditioning only when needed and when spaces were occupied, while the VAV systems operated in the full-time-full-space mode limiting occupants’ control of operation. The findings provide insights into VRF systems operation and controls as well as its energy performance, which can inform HVAC designers on system selection and building operators or facility managers on improving VRF system operations.&amp;nbsp; &amp;nbsp;&amp;nbsp;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;br /&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Reshma Singh</style></author><author><style face="normal" font="default" size="100%">Baptiste Ravache</style></author><author><style face="normal" font="default" size="100%">Spencer M. Dutton</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CLIMATE-SPECIFIC MODELING AND ANALYSIS FOR BEST-PRACTICE INDIAN OFFICE BUILDINGS</style></title><secondary-title><style face="normal" font="default" size="100%">BS2015: 14th Conference of International Building Performance Simulation Association</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Climate specific building energy models</style></keyword><keyword><style  face="normal" font="default" size="100%">india</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ibpsa.org/proceedings/BS2015/p2714.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Hyderabad, India</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper describes the methodology and results of building energy modeling to validate and quantify the energy savings from conservation measures in medium-sized office buildings in four different climate zones in India. We present the different energy measures and their expected and simulated performances and discuss the results and the influence of climate.&amp;nbsp;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Mary Ann Piette</style></author><author><style face="normal" font="default" size="100%">Yixing Chen</style></author><author><style face="normal" font="default" size="100%">Sang Hoon Lee</style></author><author><style face="normal" font="default" size="100%">Sarah C. Taylor-Lange</style></author><author><style face="normal" font="default" size="100%">Rongpeng Zhang</style></author><author><style face="normal" font="default" size="100%">Kaiyu Sun</style></author><author><style face="normal" font="default" size="100%">Phillip N. Price</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Commercial Building Energy Saver: An energy retrofit analysis toolkit</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Building Technologies Department</style></keyword><keyword><style  face="normal" font="default" size="100%">Building Technology and Urban Systems Division</style></keyword><keyword><style  face="normal" font="default" size="100%">buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">buildings energy efficiency</style></keyword><keyword><style  face="normal" font="default" size="100%">Commercial Building Systems</style></keyword><keyword><style  face="normal" font="default" size="100%">conservation measures</style></keyword><keyword><style  face="normal" font="default" size="100%">energy efficiency</style></keyword><keyword><style  face="normal" font="default" size="100%">energy use</style></keyword><keyword><style  face="normal" font="default" size="100%">energyplus</style></keyword><keyword><style  face="normal" font="default" size="100%">External</style></keyword><keyword><style  face="normal" font="default" size="100%">Retrofit Energy</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation research</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">9/2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">159</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Small commercial buildings in the United States consume 47% of the total primary energy of the buildings sector. Retrofitting small and medium commercial buildings poses a huge challenge for owners because they usually lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. This paper presents the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit, which calculates the energy use of a building, identifies and evaluates retrofit measures in terms of energy savings, energy cost savings and payback. The CBES Toolkit includes a web app (APP) for end users and the CBES Application Programming Interface (API) for integrating CBES with other energy software tools. The toolkit provides a rich set of features including: (1) Energy Benchmarking providing an Energy Star score, (2) Load Shape Analysis to identify potential building operation improvements, (3) Preliminary Retrofit Analysis which uses a custom developed pre-simulated database and, (4) Detailed Retrofit Analysis which utilizes real-time EnergyPlus simulations. CBES includes 100 configurable energy conservation measures (ECMs) that encompass IAQ, technical performance and cost data, for assessing 7 different prototype buildings in 16 climate zones in California and 6 vintages. A case study of a small office building demonstrates the use of the toolkit for retrofit analysis. The development of CBES provides a new contribution to the field by providing a straightforward and uncomplicated decision making process for small and medium business owners, leveraging different levels of assessment dependent upon user background, preference and data availability.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-1004502</style></custom2><section><style face="normal" font="default" size="100%">298</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jianjun Xia</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Qi Shen</style></author><author><style face="normal" font="default" size="100%">Wei Feng</style></author><author><style face="normal" font="default" size="100%">Le Yang</style></author><author><style face="normal" font="default" size="100%">Piljae Im</style></author><author><style face="normal" font="default" size="100%">Alison Lu</style></author><author><style face="normal" font="default" size="100%">Mahabir Bhandari</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of Building Energy Use Data Between the United States and China</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">comparison</style></keyword><keyword><style  face="normal" font="default" size="100%">data analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">data model</style></keyword><keyword><style  face="normal" font="default" size="100%">Energy benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">energy monitoring system</style></keyword><keyword><style  face="normal" font="default" size="100%">energy use</style></keyword><keyword><style  face="normal" font="default" size="100%">retrofit</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">78</style></volume><pages><style face="normal" font="default" size="100%">165-175</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Buildings in the United States and China consumed 41% and 28% of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.–China Clean Energy Research Center for Building Energy Efficiency. The goal is to decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-6669E</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xin Zhou</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of Building Energy Modeling Programs: HVAC Systems</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2013</style></date></pub-dates></dates><custom2><style face="normal" font="default" size="100%">LBNL-6432E</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dandan Zhu</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author><author><style face="normal" font="default" size="100%">Chuang Wang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparative research in building energy modeling programs</style></title><secondary-title><style face="normal" font="default" size="100%">China Annual HVACR Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">advanced building software: energyplus</style></keyword><keyword><style  face="normal" font="default" size="100%">building energy modeling program</style></keyword><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">comparison</style></keyword><keyword><style  face="normal" font="default" size="100%">dest</style></keyword><keyword><style  face="normal" font="default" size="100%">doe-2</style></keyword><keyword><style  face="normal" font="default" size="100%">energyplus</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation research group</style></keyword><keyword><style  face="normal" font="default" size="100%">test</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2011</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">China (in Chinese)</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dandan Zhu</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Chuang Wang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of Building Energy Modeling Programs: Building Loads</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2012</style></date></pub-dates></dates><custom2><style face="normal" font="default" size="100%">LBNL-6034E</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Paul Raferty</style></author><author><style face="normal" font="default" size="100%">Marcus Keane</style></author><author><style face="normal" font="default" size="100%">James O&#039;Donnell</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Calibrating whole building energy models: An evidence-based methodology</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">calibration</style></keyword><keyword><style  face="normal" font="default" size="100%">Methodology</style></keyword><keyword><style  face="normal" font="default" size="100%">retrofit</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Version control</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole building energy model</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2011</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">2356-2364</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper reviews existing case studies and methods for calibrating whole building energy models to measured data. This research describes a systematic, evidence-based methodology for the calibration of these models. Under this methodology, parameter values in the final calibrated model reference the source of information used to make changes to the initial model. Thus, the final model is based solely on evidence. Version control software stores a complete record of the calibration process, and the evidence on which the final model is based. Future users can review the changes made throughout the calibration process along with the supporting evidence. In addition to the evidence-based methodology, this paper also describes a new zoning process that represents the real building more closely than the typical core and four perimeter zone approach. Though the methodology is intended to apply to detailed calibration studies with high resolution measured data, the primary aspects of the methodology (evidence-based approach, version control, and zone-typing) are independent of the available measured data.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue><section><style face="normal" font="default" size="100%">2356</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dandan Zhu</style></author><author><style face="normal" font="default" size="100%">Chuang Wang</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Comparison of DeST and EnergyPlus</style></title><secondary-title><style face="normal" font="default" size="100%">China HVAC Simulation Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">comparison</style></keyword><keyword><style  face="normal" font="default" size="100%">dest</style></keyword><keyword><style  face="normal" font="default" size="100%">energy modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">energyplus</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation research</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation research group</style></keyword><keyword><style  face="normal" font="default" size="100%">test cases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Beijing</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Co-simulation of building energy and control systems with the Building Controls Virtual Test Bed</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Building Performance Simulation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">co-simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">integrated analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">modular modelling</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2010</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This article describes the implementation of the Building Controls Virtual Test Bed (BCVTB). The BCVTB is a software environment that allows connecting different simulation programs to exchange data during the time integration, and that allows conducting hardware in the loop simulation. The software architecture is a modular design based on Ptolemy II, a software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. The BCVTB provides additions to Ptolemy II that allow the run-time coupling of different simulation programs for data exchange, including EnergyPlus, MATLAB, Simulink and the Modelica modelling and simulation environment Dymola. The additions also allow executing system commands, such as a script that executes a Radiance simulation. In this article, the software architecture is presented and the mathematical model used to implement the co-simulation is discussed. The simulation program interface that the BCVTB provides is explained. The article concludes by presenting applications in which different state of the art simulation programs are linked for run-time data exchange. This link allows the use of the simulation program that is best suited for the particular problem to model building heat transfer, HVAC system dynamics and control algorithms, and to compute a solution to the coupled problem using co-simulation.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jérôme Henri Kämpf</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Darren Robinson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A comparison of global optimization algorithms with standard benchmark functions and real-world applications using EnergyPlus</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Building Performance Simulation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">application using energyplus</style></keyword><keyword><style  face="normal" font="default" size="100%">building energy minimization</style></keyword><keyword><style  face="normal" font="default" size="100%">covariance matrix adaptation evolution strategy algorithm and hybrid differential evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">particle swarm optimization and hooke-jeeves</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">103-120</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimize the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems. To shed light on this issue we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimizing standard benchmark functions and real-world building energy optimization problems of varying complexity. From this we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified controls sequence of the building energy system that does not represent actual practice, further reinforcing their utility.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marija Trcka</style></author><author><style face="normal" font="default" size="100%">Jan Hensen</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Co-simulation for performance prediction of integrated building and HVAC systems - An analysis of solution characteristics using a two-body system</style></title><secondary-title><style face="normal" font="default" size="100%">Simulation Modelling Practice and Theory</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2010</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">957-970</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Integrated performance simulation of buildings and heating, ventilation and air-conditioning (HVAC) systems can help in reducing energy consumption and increasing occupant comfort. However, no single building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to analyze integrated building systems and to enable rapid prototyping of innovative building and system technologies. One way to alleviate this problem is to use co-simulation to integrate different BPS tools. Co-simulation approach represents a particular case of simulation scenario where at least two simulators solve coupled differential-algebraic systems of equations and exchange data that couples these equations during the time integration.&lt;/p&gt;&lt;p&gt;This article analyzes how co-simulation influences consistency, stability and accuracy of the numerical approximation to the solution. Consistency and zero-stability are studied for a general class of the problem, while a detailed consistency and absolute stability analysis is given for a simple two-body problem. Since the accuracy of the numerical approximation to the solution is reduced in co-simulation, the article concludes by discussing ways for how to improve accuracy.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><section><style face="normal" font="default" size="100%">957</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liping Wang</style></author><author><style face="normal" font="default" size="100%">Julie Gwilliam</style></author><author><style face="normal" font="default" size="100%">Phillip Jones</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Case study of zero energy house design in UK</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2009</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">41</style></volume><pages><style face="normal" font="default" size="100%">1215-1222</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">11</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lixia Wu</style></author><author><style face="normal" font="default" size="100%">Mingsheng Liu</style></author><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author><author><style face="normal" font="default" size="100%">Gang Wang</style></author><author><style face="normal" font="default" size="100%">Thomas G. Lewis</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CCLEP Reduces Energy Consumption by More than 50% for a Luxury Shopping Mall</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">115</style></volume><pages><style face="normal" font="default" size="100%">492-501</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Continuous Commissioning Leading Project (CCLEP) process is an ongoing process to apply system optimization theory and advanced technologies to commercial retrofit projects. It was developed by Liu et al (2006) through a U.S. Department of Energy grant to the University of Nebraska and the Omaha Public Power District (OPPD) for continuous commissioning applications in commercial retrofit projects. The CCLEP process, procedures and seven case study results have already been presented (Liu et al 2006). &lt;/p&gt;&lt;p&gt; CCLEP was applied to a luxury shopping mall and office building. The case study building has ten single fan dual-duct VAV AHUs, 123 dual-duct pneumatic controller pressure independent terminal boxes, and a central heating and cooling plant. Major retrofit efforts include upgrading pneumatic to DDC controls for all AHUs, installing main hot deck dampers, replacing the boiler, installing VFD on fans and pumps, and installing Fan Airflow Stations (FAS) and Pump Waterflow Stations (PWS). This paper presents the optimal control strategies, which include main hot deck damper control, supply fan control integrated with FAS, return fan control, optimal control for terminal boxes, chilled water temperature and chilled water pump speed control, hot water temperature and hot water pump control. The measured hourly utility data after CCLEP show that annual HVAC electricity consumption is reduced by 56% and gas use is reduced by 36%. &lt;/p&gt;&lt;p&gt; This paper demonstrates the energy savings and system performance improvement through retrofits and optimal system control. This paper will present the case study building information, CCLEP major retrofits, CCLEP optimal control strategies, CCLEP results and conclusions&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A close look at the China design standard for energy efficiency of public buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASHRAE 90.1</style></keyword><keyword><style  face="normal" font="default" size="100%">building energy standard</style></keyword><keyword><style  face="normal" font="default" size="100%">China</style></keyword><keyword><style  face="normal" font="default" size="100%">commercial buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">energy efficiency</style></keyword><keyword><style  face="normal" font="default" size="100%">gb50189-2005</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">41</style></volume><pages><style face="normal" font="default" size="100%">426-435</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper takes a close look at the China national standard GB50189-2005, Design Standard for Energy Efficiency of Public Buildings, which was enforced on July 1, 2005. The paper first reviews the standard, then compares the standard with ASHRAE Standard 90.1-2004 to identify discrepancies in code coverage and stringency, and recommends some energy conservation measures that can be evaluated in the design of public buildings to achieve energy savings beyond the standard. The paper also highlights several important features of 90.1-2004 that may be considered as additions to the GB50189-2005 standard during the next revision. At the end the paper summarizes the latest developments in building energy standards and rating systems in China and the US.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><work-type><style face="normal" font="default" size="100%">Research Article</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaobing Liu</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">doe-2</style></keyword><keyword><style  face="normal" font="default" size="100%">energy efficiency</style></keyword><keyword><style  face="normal" font="default" size="100%">gshp</style></keyword><keyword><style  face="normal" font="default" size="100%">vrf</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">42</style></volume><pages><style face="normal" font="default" size="100%">584-589</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;With the current movement towards net zero energy buildings, many technologies are promoted with emphasis on their superior energy efficiency. The variable refrigerant flow (VRF) and ground source heat pump (GSHP) systems are probably the most competitive technologies among these. However, there are few studies reporting the energy efficiency of VRF systems compared with GSHP systems. In this article, a preliminary comparison of energy efficiency between the air-source VRF and GSHP systems is presented. The computer simulation results show that GSHP system is more energy efficient than the air-source VRF system for conditioning a small office building in two selected US climates. In general, GSHP system is more energy efficient than the air-source VRV system, especially when the building has significant heating loads. For buildings with less heating loads, the GSHP system could still perform better than the air-source VRF system in terms of energy efficiency, but the resulting energy savings may be marginal.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><work-type><style face="normal" font="default" size="100%">Research Article</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marija Trcka</style></author><author><style face="normal" font="default" size="100%">Jan Hensen</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Co-simulation of innovative integrated HVAC systems in buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Building Performance Simulation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building performance simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">co-simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">hvac simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">innovative building system modelling and simulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.informaworld.com/smpp/section?content=a913244253&amp;fulltext=713240928</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">209-230</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Integrated performance simulation of buildings HVAC systems can help in reducing energy consumption and increasing occupant comfort. However, no single building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to analyze integrated building systems and to enable rapid prototyping of innovative building and system technologies. One way to alleviate this problem is to use co-simulation, as an integrated approach to simulation. This article elaborates on issues important for co-simulation realization and discusses multiple possibilities to justify the particular approach implemented in the here described co-simulation prototype. The prototype is validated with the results obtained from the traditional simulation approach. It is further used in a proof-of-concept case study to demonstrate the applicability of the method and to highlight its benefits. Stability and accuracy of different coupling strategies are analyzed to give a guideline for the required coupling time step.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><section><style face="normal" font="default" size="100%">209</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liping Wang</style></author><author><style face="normal" font="default" size="100%">Nyuk Hien Wong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Coupled simulations for naturally ventilated rooms between building simulation (BS) and computational fluid dynamics (CFD) for better prediction of indoor thermal environment</style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2009</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">44</style></volume><pages><style face="normal" font="default" size="100%">95-112</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Walter F. Buhl</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Stephen E. Selkowitz</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparing computer run time of building simulation programs</style></title><secondary-title><style face="normal" font="default" size="100%">Building Simulation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">computer run time</style></keyword><keyword><style  face="normal" font="default" size="100%">doe-2</style></keyword><keyword><style  face="normal" font="default" size="100%">energyplus</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation program</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">210-213</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper presents an approach to comparing computer run time of building simulation programs. The computing run time of a simulation program depends on several key factors, including the calculation algorithm and modeling capabilities of the program, the run period, the simulation time step, the complexity of the energy models, the run control settings, and the software and hardware configurations of the computer that is used to make the simulation runs. To demonstrate the approach, simulation runs are performed for several representative DOE-2.1E and EnergyPlus energy models. The computer run time of these energy models are then compared and analyzed.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Dale A. Sartor</style></author><author><style face="normal" font="default" size="100%">Paul A. Mathew</style></author><author><style face="normal" font="default" size="100%">Mehry Yazdanian</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparisons of HVAC Simulations between EnergyPlus and DOE-2.2 for data centers</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">data center</style></keyword><keyword><style  face="normal" font="default" size="100%">doe-2</style></keyword><keyword><style  face="normal" font="default" size="100%">energy performance</style></keyword><keyword><style  face="normal" font="default" size="100%">energyplus</style></keyword><keyword><style  face="normal" font="default" size="100%">simulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">115 Part 1</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Convergence of IT and Facilities Real-Time and Historic Data Leads to Data Center Efficiency</style></title><secondary-title><style face="normal" font="default" size="100%">ITHERM</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Panel: Energy Efficient Data Center</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2008</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Orlando, FL</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liping Wang</style></author><author><style face="normal" font="default" size="100%">Nyuk Hien Wong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Coupled simulations for naturally ventilated residential buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Automation in Construction</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2008</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">386-398</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marija Trcka</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Jan Hensen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of Co-Simulation Approaches for Building and HVAC/R System Simulation</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Building Simulation 2007</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Beijing, China</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marija Trcka</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Jan Hensen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of co-simulation approaches for building and HVAC/R system simulation. </style></title><secondary-title><style face="normal" font="default" size="100%">Proc. of the 10th IBPSA Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ibpsa.org/proceedings/BS2007/p503_final.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Beijing, China</style></pub-location><pages><style face="normal" font="default" size="100%">1418-1425</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Appraisal of modern performance-based energy codes, as well as heating, ventilation, air- conditioning and refrigeration (HVAC/R) system*design require use of an integrated building and system performance simulation program. However, the required scope of the modeling library of such integrated tools often goes beyond those offered in available simulation programs. One remedy for this situation would be to develop the required models in an existing simulation program. However, due to the lack of model interoperability, the model would not be available in other simulation programs. We suggest co-simulation for HVAC/R system simulation as an approach to alleviate the above issues. In co-simulation, each subsystem is modeled and simulated in the appropriate simulation program, potentially on different computers, and intermediate results are communicated over the network during execution time. We discuss different co-simulation approaches and give insights into specific prototypes. Based on the prototypes, we compare the approaches in terms of accuracy, stability and execution time, using a simple case study. We finish with results discussions and recommendations on how to perform co-simulation to maintain the required accuracy of simulation results.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Qingyan Chen</style></author><author><style face="normal" font="default" size="100%">Zhao Zhang</style></author><author><style face="normal" font="default" size="100%">Wangda Zuo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computational fluid dynamics for indoor environment modeling: past, present, and future</style></title><secondary-title><style face="normal" font="default" size="100%">the 6th International Indoor Air Quality, Ventilation and Energy Conservation in Buildings Conference (IAQVEC 2007)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><pub-location><style face="normal" font="default" size="100%">Sendai, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">1-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><num-vols><style face="normal" font="default" size="100%">3</style></num-vols></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Danielle Monfet</style></author><author><style face="normal" font="default" size="100%">Radu Zmeureanu</style></author><author><style face="normal" font="default" size="100%">Roland Charneux</style></author><author><style face="normal" font="default" size="100%">Nicolas Lemire</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computer Model of a University Building Using the EnergyPlus Program</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Building Simulation 2007</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Beijing, China</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liping Wang</style></author><author><style face="normal" font="default" size="100%">Nyuk Hien Wong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A convenient coupled simulation method for thermal environment prediction in naturally ventilated buildings</style></title><secondary-title><style face="normal" font="default" size="100%">2nd PALENC conference and 28th AIVC conference, 27-29 September</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2007</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arunabha Sen</style></author><author><style face="normal" font="default" size="100%">Nibedita Das</style></author><author><style face="normal" font="default" size="100%">Ling Zhou</style></author><author><style face="normal" font="default" size="100%">Bao Hong Shen</style></author><author><style face="normal" font="default" size="100%">Sudheendra Murthy</style></author><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Coverage Problem for Sensors Embedded in Temperature Sensitive Environments</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Infocom, 2007</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">5/2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Anchorage, AL</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author><author><style face="normal" font="default" size="100%">Wei, X.</style></author><author><style face="normal" font="default" size="100%">Andrei G. Fedorov</style></author><author><style face="normal" font="default" size="100%">Yogendra K. Joshi</style></author><author><style face="normal" font="default" size="100%">Navdeep Bajwa</style></author><author><style face="normal" font="default" size="100%">Anyuan Cao</style></author><author><style face="normal" font="default" size="100%">Pulickel Ajayan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Carbon Nanotube (CNT)-Centric Thermal Management of Future High Power Microprocessors</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE CPMT International Symposium and Exhibition on Advanced Packaging Materials</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2006</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Atlanta, GA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Andreas Weber</style></author><author><style face="normal" font="default" size="100%">Ian Beausoleil-Morrison</style></author><author><style face="normal" font="default" size="100%">Brent T. Griffith</style></author><author><style face="normal" font="default" size="100%">Teemu Vesanen</style></author><author><style face="normal" font="default" size="100%">Sébastien Lerson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Case Study Demonstrating the Utility of Inter-Program Comparative Testing for Diagnosing Errors in Building Simulation Programs</style></title><secondary-title><style face="normal" font="default" size="100%">eSim 2006</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2006</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Toronto, Canada</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author><author><style face="normal" font="default" size="100%">Zheng, B</style></author><author><style face="normal" font="default" size="100%">Mingsheng Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Case Study of Continuous Commissioning in an Office Building</style></title><secondary-title><style face="normal" font="default" size="100%">the 6th International Conference of Enhanced Building Operations</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Shenzhen, China</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peng Xu</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Case Study of Demand Shifting with Thermal Mass in Two Large Commercial Buildings</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">112</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">Pt. 1</style></issue><custom2><style face="normal" font="default" size="100%">LBNL-58649</style></custom2><section><style face="normal" font="default" size="100%">572</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author><author><style face="normal" font="default" size="100%">S. Nara</style></author><author><style face="normal" font="default" size="100%">P. Vijayan</style></author><author><style face="normal" font="default" size="100%">Tang, T.</style></author><author><style face="normal" font="default" size="100%">W. Lai</style></author><author><style face="normal" font="default" size="100%">Patrick E. Phelan</style></author><author><style face="normal" font="default" size="100%">Ravi S. Prasher</style></author><author><style face="normal" font="default" size="100%">David W. Song</style></author><author><style face="normal" font="default" size="100%">J. Wang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of the Temperature Oscillation Technique to Measure the Thermal Conductivity of Fluids</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Heat and Mass Transfer</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Temperature oscillation technique</style></keyword><keyword><style  face="normal" font="default" size="100%">Thermal conductivity</style></keyword><keyword><style  face="normal" font="default" size="100%">thermal diffusivity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2006</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S001793100600144X</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">2950-2956</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The temperature oscillation technique to measure the thermal diffusivity of a fluid consists of filling a cylindrical volume with the fluid, applying an oscillating temperature boundary condition at the two ends of the cylinder, measuring the amplitude and phase of the temperature oscillation at any point inside the cylinder, and finally calculating the fluid thermal diffusivity from the amplitude and phase values of the temperature oscillations at the ends and at the point inside the cylinder. Although this experimental technique was introduced by Santucci and co-workers nearly two decades ago, its application is still limited, perhaps because of the perceived difficulties in obtaining accurate results. Here, we attempt to clarify this approach by first estimating the maximum size of the liquid’s cylindrical volume, performing a systematic series of experiments to find the allowable amplitude and frequency of the imposed temperature oscillations, and then validating our experimental setup and the characterization method by measuring the thermal conductivity of pure water at different temperatures and comparing our results with previously published work.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">17-18</style></issue><section><style face="normal" font="default" size="100%">2950</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author><author><style face="normal" font="default" size="100%">S. Nara</style></author><author><style face="normal" font="default" size="100%">P. Vijayan</style></author><author><style face="normal" font="default" size="100%">Tang, T.</style></author><author><style face="normal" font="default" size="100%">W. Lai</style></author><author><style face="normal" font="default" size="100%">Patrick E. Phelan</style></author><author><style face="normal" font="default" size="100%">Ravi S. Prasher</style></author><author><style face="normal" font="default" size="100%">David W. Song</style></author><author><style face="normal" font="default" size="100%">J. Wang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of the Temperature Oscillation Technique to Measure the Thermal Conductivity of Fluids</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Heat and Mass Transfer</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Temperature oscillation technique</style></keyword><keyword><style  face="normal" font="default" size="100%">Thermal conductivity</style></keyword><keyword><style  face="normal" font="default" size="100%">thermal diffusivity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2006</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S001793100600144X</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">2950-2956</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The temperature oscillation technique to measure the thermal diffusivity of a fluid consists of filling a cylindrical volume with the fluid, applying an oscillating temperature boundary condition at the two ends of the cylinder, measuring the amplitude and phase of the temperature oscillation at any point inside the cylinder, and finally calculating the fluid thermal diffusivity from the amplitude and phase values of the temperature oscillations at the ends and at the point inside the cylinder. Although this experimental technique was introduced by Santucci and co-workers nearly two decades ago, its application is still limited, perhaps because of the perceived difficulties in obtaining accurate results. Here, we attempt to clarify this approach by first estimating the maximum size of the liquid’s cylindrical volume, performing a systematic series of experiments to find the allowable amplitude and frequency of the imposed temperature oscillations, and then validating our experimental setup and the characterization method by measuring the thermal conductivity of pure water at different temperatures and comparing our results with previously published work.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">17-18</style></issue><section><style face="normal" font="default" size="100%">2950</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liping Wang</style></author><author><style face="normal" font="default" size="100%">Nyuk Hien Wong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Coupling between the CFD simulation and building simulation for better prediction of natural ventilation</style></title><secondary-title><style face="normal" font="default" size="100%">the 2nd International conference on sustainable architecture and urban design in tropical regions, Jogjakarta</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2006</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liping Wang</style></author><author><style face="normal" font="default" size="100%">Nyuk Hien Wong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A coupling method to increase the accuracy of natural ventilation prediction in thermal simulation program</style></title><secondary-title><style face="normal" font="default" size="100%">the 2nd International conference on sustainable architecture and urban design in tropical regions, Jogjakarta</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2006</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author><author><style face="normal" font="default" size="100%">Patrick E. Phelan</style></author><author><style face="normal" font="default" size="100%">Ravi S. Prasher</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computational Analysis of the Colloidal Stability of Nanofluids</style></title><secondary-title><style face="normal" font="default" size="100%">International Mechanical Engineering Congress &amp; Exposition</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2005</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Orlando, FL</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zheng, B</style></author><author><style face="normal" font="default" size="100%">Mingsheng Liu</style></author><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Continuous Commissioning of an Office Building</style></title><secondary-title><style face="normal" font="default" size="100%">the 5th International Conference of Enhanced Building Operations</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Pittsburgh, PA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Drury B. Crawley</style></author><author><style face="normal" font="default" size="100%">Jon W. Hand</style></author><author><style face="normal" font="default" size="100%">Michael Kummert</style></author><author><style face="normal" font="default" size="100%">Brent T. Griffith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Contrasting the Capabilities of Building Energy Performance Simulation Programs</style></title><secondary-title><style face="normal" font="default" size="100%">IBPSA Building Simulation 2005</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2005</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Montreal, Canada</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chanvit Chantrasrisalai</style></author><author><style face="normal" font="default" size="100%">Daniel E. Fisher</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparative Analysis of One-Dimensional Slat-Type Blind Models</style></title><secondary-title><style face="normal" font="default" size="100%">SimBuild 2004, Building Sustainability and Performance Through Simulation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2004</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Boulder, Colorado, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization </style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">coordinate search</style></keyword><keyword><style  face="normal" font="default" size="100%">direct search</style></keyword><keyword><style  face="normal" font="default" size="100%">genetic algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">hooke–jeeves</style></keyword><keyword><style  face="normal" font="default" size="100%">optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">particle swarm optimization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2004</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">989-999</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><section><style face="normal" font="default" size="100%">989</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Elijah Polak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A convergent optimization method using pattern search algorithms with adaptive precision simulation</style></title><secondary-title><style face="normal" font="default" size="100%">Building Services Engineering Research and Technology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2004</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">327-338</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Thermal building simulation programs, such as EnergyPlus, compute numerical approximations to solutions of systems of differential algebraic equations. We show that the exact solutions of these systems are usually smooth in the building design parameters, but that the numerical approximations are usually discontinuous due to adaptive solvers and finite precision computations. If such approximate solutions are used in conjunction with optimization algorithms that depend on smoothness of the cost function, one needs to compute high precision solutions, which can be prohibitively expensive if used for all iterations. For such situations, we have developed an adaptive simulation–precision control algorithm that can be used in conjunction with a family of derivative free optimization algorithms. We present the main ingredients of the composite algorithms, we prove that the resulting composite algorithms construct sequences with stationary accumulation points, and we show by numerical experiments that using coarse approximations in the early iterations can significantly reduce computation time.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Godfried Augenbroe</style></author><author><style face="normal" font="default" size="100%">Jan Hensen</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of a generalized pattern search and a genetic algorithm optimization method</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. of the 8th IBPSA Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ibpsa.org/proceedings/BS2003/BS03_1401_1408.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Eindhoven, Netherlands</style></pub-location><volume><style face="normal" font="default" size="100%">III</style></volume><pages><style face="normal" font="default" size="100%">1401-1408</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author><author><style face="normal" font="default" size="100%">Yongcheng Jiang</style></author><author><style face="normal" font="default" size="100%">Yan-shu Miao</style></author><author><style face="normal" font="default" size="100%">Jun Xiong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computer Measurement and Automation System for Gas-fired Heating Furnace</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Harbin Institute of Technology (Chinese)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">374-378</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Elijah Polak</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Godfried Augenbroe</style></author><author><style face="normal" font="default" size="100%">Jan Hensen</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A convergent optimization method using pattern search algorithms with adaptive precision simulation</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 8th IBPSA Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">coordinate search</style></keyword><keyword><style  face="normal" font="default" size="100%">direct search</style></keyword><keyword><style  face="normal" font="default" size="100%">genetic algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">hooke–jeeves</style></keyword><keyword><style  face="normal" font="default" size="100%">optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">particle swarm optimization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><pub-location><style face="normal" font="default" size="100%">Eindhoven, Netherlands</style></pub-location><volume><style face="normal" font="default" size="100%">III</style></volume><pages><style face="normal" font="default" size="100%">1393-1400</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Norman Bourassa</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Yu Joe Huang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Computer Simulation Appraisal of Non-Residential Low Energy Cooling Systems in California</style></title><secondary-title><style face="normal" font="default" size="100%">2002 ACEEE Summer Study on Energy Efficiency in Buildings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2002</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Asilomar, California, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;An appraisal of the potential performance of different Low Energy Cooling (LEC) systems in nonresidential buildings in California is being conducted using computer simulation. The paper presents results from the first phase of the study, which addressed the systems that can be modeled, with the DOE-2.1E simulation program.&lt;/p&gt;&lt;p&gt;The following LEC technologies were simulated as variants of a conventional variable-air-volume system with vapor compression cooling and mixing ventilation in the occupied spaces:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Air-side indirect and indirect/direct evaporative pre-cooling&lt;/li&gt; &lt;li&gt;Cool beams&lt;/li&gt; &lt;li&gt;Displacement ventilation&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;Results are presented for four populous climates, represented by Oakland, Sacramento, Pasadena and San Diego. The greatest energy savings are obtained from a combination of displacement ventilation and air-side indirect/direct evaporative pre-cooling. Cool beam systems have the lowest peak demand but do not reduce energy consumption significantly because the reduction in fan energy is offset by a reduction in air-side free cooling. Overall, the results indicate significant opportunities for LEC  technologies to reduce energy consumption and demand in non-residential  new construction and retrofit.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-50677</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Priya Sreedharan</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of Chiller Models for use in Model-Based Fault Detection</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference for Enhancing Building Operations</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2001</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Austin, TX</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD).  Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression chillers.  Three different models were studied: the Gordon and Ng Universal Chiller model (2nd generation) and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles, and the DOE-2 chiller model, as implemented in CoolToolsTM, which is empirical. The models were compared in terms of their ability to reproduce the observed performance of an older, centrifugal chiller operating in a commercial office building and a newer centrifugal chiller in a laboratory.  All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-48149</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Simon J. Rees</style></author><author><style face="normal" font="default" size="100%">Jeffrey D. Spitler</style></author><author><style face="normal" font="default" size="100%">Michael J. Holmes</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of Peak Load Predictions and Treatment of Solar Gains in the Admittance and Heat Balance Load Calculation Procedures</style></title><secondary-title><style face="normal" font="default" size="100%">Building Services Engineering Research &amp; Technology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://bse.sagepub.com/content/21/2/125</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">21</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Calculation of design cooling loads is of critical concern to designers of HVAC systems. The work reported here has been carried out under a joint ASHRAE-CIBSE research project to compare design cooling calculation methods. Peak cooling loads predicted by the ASHRAE heat balance method are compared with those predicted by a number of implementations of the admittance method using different window models. The results presented show the general trends in overprediction or underprediction of peak load. Particular attention is given to different window modelling practices. The performance of the methods is explained in terms of some of the underlying assumptions in the window models, and by reference to specific inter-model comparisons.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Simon J. Rees</style></author><author><style face="normal" font="default" size="100%">Jeffrey D. Spitler</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of North American and U.K. Cooling Load Calculation Procedures - Results</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><volume><style face="normal" font="default" size="100%">104</style></volume><pages><style face="normal" font="default" size="100%">36-46</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Calculation of design cooling loads is of critical concern to designers of HVAC systems. The work reported here has been carried out under a joint ASHRAE/CIBSE research project to compare design cooling calculation methods. Three calculation methods have been tested, the ASHRAE heat balance method and radiant time series method, and the admit- tance method, used in the U.K. The results presented in this paper show the general trends in over/underprediction of peak load in the simplified methods compared to the heat balance method. The performance of the simplified methods is explained in terms of some of the underlying assumptions in the methods and by reference to specific examples.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><section><style face="normal" font="default" size="100%">36</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jeffrey D. Spitler</style></author><author><style face="normal" font="default" size="100%">Simon J. Rees</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of North American and U.K. Cooling Load Calculation Procedures - Methodology</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><volume><style face="normal" font="default" size="100%">104</style></volume><pages><style face="normal" font="default" size="100%">47-61</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper describes the methodology used in a quanti- tative comparison between the current North American and United Kingdom cooling load calculation methods. Three calculation methods have been tested as part of a joint ASHRAE/CIBSE research project: the ASHRAE heat balance method and radiant time series method and the admittance method, used in the U.K. A companion paper (Rees et al.1998) describes the results of the study. The quantitative comparison is primarily organized as a parametric study—each building zone/weather day combination compared may be thought of as a combination of various parameters, e.g., exterior wall type, roof type, glazing area, etc. Specifically, this paper describes the overall organization of the study, the parameters and parameter levels that can be varied, and the tools developed to create input files, automate the load calculations, and extract the results. A brief descrip- tion of the cooling load calculation procedure implementa- tions is also given. The methodology presented and the tools described could also be used to make comparisons between other calculation methods.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><section><style face="normal" font="default" size="100%">47</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Edward F. Sowell</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Component-Based and Equation-Based Solvers for HVAC Simulation: a Comparison of HVACSIM+ and SPARK</style></title><secondary-title><style face="normal" font="default" size="100%">System Simulation in Buildings &#039;98</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/98</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Liège, Belgium</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Tim I. Salsbury</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Condition Monitoring in HVAC Subsystems using First Principles Models</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><volume><style face="normal" font="default" size="100%">102</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">Pt. 1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Component-Based Modelling of VAV Systems</style></title><secondary-title><style face="normal" font="default" size="100%">System Simulation in Buildings &#039;94</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1994</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/1994</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Liège, Belgium</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Kenny, G.</style></author><author><style face="normal" font="default" size="100%">Susan Roaf</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Climate Change and Passive Cooling in Europe</style></title><secondary-title><style face="normal" font="default" size="100%">PLEA&#039;92 Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1992</style></year></dates><pub-location><style face="normal" font="default" size="100%">Auckland, New Zealand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joseph H. Eto</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Comparison of Weather Normalization Techniques for Commercial Building Energy Use</style></title><secondary-title><style face="normal" font="default" size="100%">DOE/ASHRAE/BTECC Conference on Thermal Performance of the Exterior Envelopes of Buildings III</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1985</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/1985</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">LBNL</style></publisher><pub-location><style face="normal" font="default" size="100%">Clearwater Beach, FL </style></pub-location><custom2><style face="normal" font="default" size="100%">LBNL-21217</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joseph H. Eto</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cooling Strategies Based on Indicators of Thermal Storage in Commercial Building Mass</style></title><secondary-title><style face="normal" font="default" size="100%">Second Symposium on Improving Building Systems in Hot and Humid Climates</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1985</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/1985</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">College Station, Texas</style></pub-location><custom2><style face="normal" font="default" size="100%">LBNL-19912</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joseph H. Eto</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Commercial Building Cogeneration Opportuntities</style></title><secondary-title><style face="normal" font="default" size="100%">ACEEE Summer Study in Energy Efficient Buildings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1984</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/1984</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://aceee.org/files/proceedings/1984/data/papers/SS84_Panel1_Paper_059.pdf#page=1</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Santa Cruz, CA</style></pub-location><custom2><style face="normal" font="default" size="100%">LBNL-18176</style></custom2></record></records></xml>