@article {32192, title = {Culture, conformity, and carbon? A multi-country analysis of heating and cooling practices in office buildings}, journal = {Energy Research \& Social Science}, volume = {61}, year = {2020}, month = {Jan-03-2020}, pages = {101344}, abstract = {

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{\textquoteright} 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{\textquoteright}
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.

}, issn = {22146296}, doi = {10.1016/j.erss.2019.101344}, author = {Chen, Chien-fei and Tianzhen Hong and de Rubens, Gerardo Zarazua and Yilmaz, Selin and Bandurski, Karol and B{\'e}lafi, Zs{\'o}fia Deme and De Simone, Marilena and Bavaresco, Mateus Vin{\'\i}cius and Wang, Yu and Liu, Pei-ling and Barthelmes, Verena M. and Adams, Jacqueline and D{\textquoteright}Oca, Simona and Przybylski, {\L}ukasz} } @article {32157, title = {Assessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California}, journal = {Science of The Total Environment}, volume = {686}, year = {2019}, month = {Jan-10-2019}, pages = {1251 - 1261}, abstract = {

The recent wildfires in California, U.S., have caused not only significant losses to human life and property, but also serious environmental and health issues. Ambient air pollution from combustion during the fires could increase indoor exposure risks to toxic gases and particles, further exacerbating respiratory conditions. This work aims at addressing existing knowledge gaps in understanding how indoor air quality is affected by outdoor air pollutants during wildfires{\textemdash}by taking into account occupant behaviors (e.g., movement, operation of windows and air-conditioning) which strongly influence building performance and occupant comfort. A novel modeling framework was developed to simulate the indoor exposure risks considering the impact of occupant behaviours by integrating building energy and occupant behaviour modeling with computational fluid dynamics simulation. Occupant behaviors were found to exert significant impacts on indoor air flow patterns and pollutant concentrations, based on which, certain behaviors are recommended during wildfires. Further, the actual respiratory injury level under such outdoor conditions was predicted. The modeling framework and the findings enable a deeper understanding of the actual health impacts of wildfires, as well as informing strategies for mitigating occupant health risk during wildfires

}, keywords = {computational fluid dynamics siumlation, human exposure risk, indoor air quality, NAPA wildfire, occupant behavior, respiratory injury}, issn = {00489697}, doi = {10.1016/j.scitotenv.2019.05.467}, author = {Luo, Na and Weng, Wenguo and Xu, Xiaoyu and Tianzhen Hong and Fu, Ming and Sun, Kaiyu} } @article {32160, title = {Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering}, journal = {Building and Environment}, volume = {162}, year = {2019}, month = {Jan-09-2019}, pages = {106280}, abstract = {

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.

}, keywords = {data fusion, Feature selection, Machine learning, occupancy prediction, Physics-based model}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.106280}, author = {Wang, Wei and Tianzhen Hong and Xu, Ning and Xu, Xiaodong and Chen, Jiayu and Shan, Xiaofang} } @article {31667, title = {Data fusion in predicting internal heat gains for office buildings through a deep learning approach}, journal = {Applied Energy}, volume = {240}, year = {2019}, month = {02/2019}, pages = {386 - 398}, abstract = {

Heating, Ventilation, and Air Conditioning (HVAC) is a major energy consumer in buildings. The predictive control has demonstrated a potential to reduce HVAC energy use. To facilitate predictive HVAC control, internal heat gains prediction is required. In this study, we applied Long Short-Term Memory Networks, a special form of deep neural network, to predict miscellaneous electric loads, lighting loads, occupant counts and internal heat gains in two United States office buildings. Compared with the predetermined schedules used in American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standard 90.1, the Long Short-Term Memory Networks method could reduce the prediction errors of internal heat gains from 12\% to 8\% in Building A, and from 26\% to 16\% in Building B. It was also found that for internal heat gains prediction, miscellaneous electric loads is a more important feature than occupant counts for two reasons. First, miscellaneous electric loads is the best proxy variable for internal heat gains, as it is the major component of and has the highest correlation coefficient with the internal heat gains. Second, miscellaneous electric loads contain valuable information to predict occupant count, while occupant count could not help improve miscellaneous electric loads prediction. These findings could help researchers and practitioners select the most relevant features to more accurately predict internal heat gains for the implementation of predictive HVAC control in buildings.

}, keywords = {data fusion, deep learning, Internal heat gains, Miscellaneous electric loads, Occupant count, Predictive control}, issn = {03062619}, doi = {10.1016/j.apenergy.2019.02.066}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261919303630}, author = {Zhe Wang and Tianzhen Hong and Mary Ann Piette} } @article {31670, title = {Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm}, journal = {Applied Energy}, volume = {248}, year = {2019}, month = {04/2019}, pages = {217 - 230}, abstract = {

With the development of data-driven techniques, district-scale building energy prediction has attracted increasing attention in recent years for revealing energy use patterns and reduction potentials. However, data acquisition in large building groups is difficult and adjacent buildings also interact with each other. To reduce data cost and incorporate the inter-building impact with the data-driven building energy model, this study proposes a deep learning predictive approach that fuses the building network model with a long short-term memory learning model for district-scale building energy modeling. The building network was constructed based on correlations between the energy use intensity of buildings, which can significantly reduce the computational complexity of the deep learning models for energy dynamic prediction. Five typical building groups with energy use data from 2015 to 2018 on two institutional campuses were selected to perform the validation experiment with TensorFlow. Based on the prediction error assessments, the results suggest that for total building energy use intensity prediction, the proposed model can achieve a mean absolute percentage error of 6.66\% and a root mean square error of 0.36 kWh/m2, compared to 12.05\% and 0.63 kWh/m2 of the conventional artificial neural network model and to 11.06\% and 0.89 kWh/m2 for the support vector regression model.

}, keywords = {Building Energy Modeling, Building network, Data-driven prediction, District-scale, Long short-term memory networks}, issn = {03062619}, doi = {10.1016/j.apenergy.2019.04.085}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261919307494}, author = {Wei Wang and Tianzhen Hong and Xiaodong Xu and Jiayu Chen and Ziang Liu and Ning Xu} } @article {31665, title = {Incorporating machine learning with building network analysis to predict multi-building energy use}, journal = {Energy and Buildings}, volume = {186}, year = {2019}, month = {06/2019}, pages = {80 - 97}, abstract = {

Predicting multi-building energy use at campus or city district scale has recently gained more attention; and more researchers have started to define reference buildings and study inter-impact between building groups. However, how to integrate the relationship to define reference buildings and predict multi-building energy use, using significantly less amount of building data and reducing complexity of prediction models, remains an open research question. To resolve this, this study proposed a novel method to predict multi-building energy use by integrating a social network analysis (SNA) with an Artificial Neural Network (ANN) technique. The SNA method was used to establish a building network (BN) by identifying reference buildings and determine correlations between reference buildings and non-reference buildings. The ANN technique was applied to learn correlations and historical building energy use, and then used to predict multi-building energy use. To validate the SNA-ANN method, 17 buildings in the Southeast University campus, located in Nanjing, China, were studied. These buildings have three years of actual monthly electricity use data and were grouped into four types: office, educational, laboratory, and residential. The results showed the integrated SNA-ANN method achieved average prediction accuracies of 90.67\% for the office group, 90.79\% for the educational group, 92.34\% for the laboratory group, and 83.32\% for the residential group. The results demonstrated the proposed SNA-ANN method achieved an accuracy of 90.28\% for the predicted energy use for all building groups. Finally, this study provides insights into advancing the interdisciplinary research on multi-building energy use prediction.

}, keywords = {Artificial neural networks, Building network, cold winter and hot summer climate, Energy use prediction, Machine learning}, issn = {03787788}, doi = {10.1016/j.enbuild.2019.01.002}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0378778818319765}, author = {Xiaodong Xu and Wei Wang and Tianzhen Hong and Jiayu Chen} } @article {31671, title = {Inferring occupant counts from Wi-Fi data in buildings through machine learning}, journal = {Building and Environment}, volume = {158}, year = {2019}, month = {05/2019}, pages = {281 - 294}, abstract = {

An important approach to curtail building energy consumption is to optimize building control based on occupancy information. Various studies proposed to estimate occupant counts through different approaches and sensors. However, high cost and privacy concerns remain as major barriers, restricting the practice of occupant count detection. In this study, we propose a novel method utilizing data from widely deployed Wi-Fi infrastructure to infer occupant counts through machine learning. Compared with the current indirect measurement methods, our method improves the performance of estimating people count: (1) we avoid privacy concerns by anonymizing and reshuffling the MAC addresses on a daily basis; (2) we adopted a heuristic feature engineer approach to cluster connected devices into different types based on their daily connection duration. We tested the method in an office building located in California. In an area with an average occupancy of 22{\textendash}27 people and a peak occupancy of 48{\textendash}74 people, the root square mean error on the test set is less than four people. The error is within two people counts for more than 70\% of estimations, and less than six counts for more than 90\% of estimations, indicating a relatively high accuracy. The major contribution of this study is proposing a novel and accurate approach to detect occupant counts in a non-intrusive way, i.e., utilizing existing Wi-Fi infrastructure in buildings without requiring the installation of extra hardware or sensors. The method we proposed is generic and could be applied to other commercial buildings to infer occupant counts for energy efficient building control.

}, keywords = {Building control, Machine learning, Occupancy estimation, Occupant count, Random forest, Wi-Fi data}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.05.015}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0360132319303336}, author = {Zhe Wang and Tianzhen Hong and Mary Ann Piette and Marco Pritoni} } @article {32165, title = {Learning occupants{\textquoteright} indoor comfort temperature through a Bayesian inference approach for office buildings in United States}, journal = {Renewable and Sustainable Energy Reviews}, year = {2019}, month = {Jan-11-2019}, pages = {109593}, abstract = {

A carefully chosen indoor comfort temperature as the thermostat set-point is the key to optimizing building energy use and occupants{\textquoteright} comfort and well-being. ASHRAE Standard 55 or ISO Standard 7730 uses the PMV-PPD model or the adaptive comfort model that is based on small-sized or outdated sample data, which raises questions on whether and how ranges of occupant thermal comfort temperature should be revised using more recent larger-sized dataset. In this paper, a Bayesian inference approach has been used to derive new occupant comfort temperature ranges for U.S. office buildings using the ASHRAE Global Thermal Comfort Database. Bayesian inference can express uncertainty and incorporate prior knowledge. The comfort temperatures were found to be higher and less variable at cooling mode than at heating mode, and with significant overlapped variation ranges between the two modes. The comfort operative temperature of occupants varies between 21.9 and 25.4{\textdegree}C for the cooling mode with a median of 23.7{\textdegree}C, and between 20.5 and 24.9{\textdegree}C for the heating mode with a median of 22.7{\textdegree}C. These comfort temperature ranges are similar to the current ASHRAE standard 55 in the heating mode but 2-3{\textdegree}C lower in the cooling mode. The results of this study could be adopted as more realistic thermostat set-points in building design, operation, control optimization, energy performance analysis, and policymaking.

}, issn = {13640321}, doi = {10.1016/j.rser.2019.109593}, author = {Wang, Zhe and Hong, Tianzhen} } @article {31662, title = {Linking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification}, journal = {Applied Energy}, volume = {236}, year = {2019}, month = {02/2019}, pages = {55 - 69}, abstract = {

With rapid advances in sensing and digital technologies, cyber-physical systems are regarded as the most prominent platforms to improve building design and management. Researchers investigated the possibility of integrating energy management system with cyber-physical systems as energy-cyber-physical systems to promote building energy management. However, minimizing energy consumption while fulfilling building functions for energy-cyber-physical systems is challenging due to the dynamics of building occupants. As occupant behavior is one major source of uncertainties for energy management, ignoring it often results in energy wastes caused by overheating and overcooling as well as discomfort due to insufficient thermal and ventilation services. To mitigate such uncertainties, this study proposed an occupancy linked energy-cyber-physical system that incorporates WiFi probe-based occupancy detection. The proposed framework utilized ensemble classification algorithms to extract three types of occupancy information. It creates a data interface to link energy management system and cyber-physical systems and allows automated occupancy detection and interpretation through assembling multiple weak classifiers for WiFi signals. A validation experiment in a large office room was conducted to examine the performance of the proposed occupancy linked energy-cyber-physical systems. The experiment and simulation results suggest that, with a proper classifier and occupancy type, the proposed model can potentially save about 26.4\% of energy consumption from the cooling and ventilation demands.

}, keywords = {Building occupancy, Energy-Cyber-Physical Systems, ensemble algorithm, Wi-Fi probe technology}, issn = {03062619}, doi = {10.1016/j.apenergy.2018.11.079}, author = {Wei Wang and Tianzhen Hong and Nan Li and Ryan Qi Wang and Jiayu Chen} } @article {31664, title = {Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China}, journal = {Building Simulation}, volume = {12}, year = {2019}, month = {03/2019}, pages = {411 - 424}, abstract = {

Urbanization has led to changes in urban morphology and climate, while urban open space has become an important ecological factor for evaluating the performance of urban development. This study presents an optimization approach using computational performance simulation. With a genetic algorithm using the Grasshopper tool, this study analyzed the layout and configuration of urban open space and its impact on the urban micro-climate under summer and winter conditions. The outdoor mean Universal Thermal Climate Index (UTCI) was applied as the performance indicator for evaluating the quality of the urban micro-climate. Two cases{\textemdash}one testbed and one real urban block in Nanjing, China{\textemdash}were used to validate the computer-aided simulation process. The optimization results in the testbed showed UTCI values varied from 36.5 to 37.3 {\textdegree}C in summer and from -4.9 to -1.9 {\textdegree}C in winter. In the case of the real urban block, optimization results show, for summer, although the average UTCI value increased by 0.6 {\textdegree}C, the average air velocity increased by 0.2 m/s; while in winter, the average UTCI value increased by 1.7 {\textdegree}C and the average air velocity decreased by 0.2 m/s. These results demonstrate that the proposed computer-aided optimization process can improve the thermal comfort conditions of open space in urban blocks. Finally, this study discusses strategies and guidelines for the layout design of urban open space to improve urban environment comfort.

}, issn = {1996-3599}, doi = {10.1007/s12273-019-0510-z}, url = {http://link.springer.com/10.1007/s12273-019-0510-zhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/article/10.1007/s12273-019-0510-z/fulltext.html}, author = {Xiaodong Xu and Yifan Wu and Wei Wang and Tianzhen Hong and Ning Xu} } @article {31362, title = {Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems}, journal = {Applied Energy}, volume = {236}, year = {2019}, month = {02/2019}, pages = {410 - 425}, abstract = {

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

}, keywords = {building simulation, hvac, Model predictive control, System identification}, issn = {03062619}, doi = {10.1016/j.apenergy.2018.11.093}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261918318099https://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/plain}, author = {David Blum and K. Arendt and Lisa Rivalin and Mary Ann Piette and Michael Wetter and C.T. Veje} } @article {31672, title = {Predicting plug loads with occupant count data through a deep learning approach}, journal = {Energy}, volume = {181}, year = {2019}, month = {05/2019}, pages = {29 - 42}, abstract = {

Predictive control has gained increasing attention for its ability to reduce energy consumption and improve occupant comfort in buildings. The plug loads prediction is a key component for the predictive building controls, as plug loads is a major source of internal heat gains in buildings. This study proposed a novel method to apply the Long-Short-Term-Memory (LSTM) Network, a special form of Recurrent Neural Network, to predict plug loads. The occupant count and the time have been confirmed to drive the plug load profile and thus selected as the features for the plug load prediction. The LSTM network was trained and tested with ground truth occupant count data collected from a real office building in Berkeley, California. Results from the LSTM network markedly improve the prediction accuracy compared with traditional linear regression methods and the classical Artificial Neural Network. 95\% of 1-h predictions from LSTM network are within {\textpm}1 kW of the actual plug loads, given the average plug loads during the office hour is 8.6 kW. The CV(RMSE) of the predicted plug load is 11\% for the next hour, and 20\% for the next 8 h. Lastly, we compared four prediction approaches with the office building we monitored: LSTM vs. ARIMA, with occupant counts vs. without occupant counts. It was found, the prediction error of the LSTM approach is around 4\% less than the ARIMA approach. Using occupant counts as an exogenous input could further reduce the prediction error by 5\%{\textendash}6\%. The findings of this paper could shed light on the plug load prediction for building control optimizations such as model-predictive control.

}, keywords = {deep learning, Long short term memory network, Occupant count, Plug loads, prediction, Predictive control}, issn = {03605442}, doi = {10.1016/j.energy.2019.05.138}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0360544219310205}, author = {Zhe Wang and Tianzhen Hong and Mary Ann Piette} } @conference {31980, title = {Prototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings}, booktitle = {IBPSA Building Simulation 2019}, year = {2019}, address = {Rome, Italy}, abstract = {

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

}, keywords = {benchmarking, building simulation, Model predictive control, software development}, author = {David Blum and Filip Jorissen and Sen Huang and Yan Chen and Javier Arroyo and Kyle Benne and Yanfei Li and Valentin Gavan and Lisa Rivalin and Lieve Helsen and Draguna Vrabie and Michael Wetter and Marina Sofos} } @article {31547, title = {Quayside Energy Systems Analysis}, year = {2019}, month = {03/2019}, keywords = {District Heating and cooling, modelica}, author = {Michael Wetter and Jianjun Hu} } @article {32159, title = {Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China}, journal = {Sustainability}, volume = {11}, year = {2019}, month = {Jan-07-2019}, pages = {3683}, abstract = {

In areas with a dry and hot climate, factors such as strong solar radiation, high temperature, low humidity, dazzling light, and dust storms can tremendously reduce people{\textquoteright}s thermal comfort. Therefore, researchers are paying more attention to outdoor thermal comfort in urban environments as part of urban design. This study proposed an automatic workflow to optimize urban spatial forms with the aim of improvement of outdoor thermal comfort conditions, characterized by the universal thermal climate index (UTCI). A city with a dry and hot climate{\textemdash}Kashgar, China{\textemdash}is further selected as an actual case study of an urban block and Rhino \& Grasshopper is the platform used to conduct simulation and optimization process with the genetic algorithm. Results showed that in summer, the proposed method can reduce the averaged UTCI from 31.17 to 27.43 {\textdegree}C, a decrease of about 3.74 {\textdegree}C, and reduce mean radiation temperature (MRT) from 43.94 to 41.29 {\textdegree}C, a decrease of about 2.65 {\textdegree}C.

}, keywords = {dry and hot areas; outdoor thermal comfort; urban morphology; urban performance simulation; genetic algorithm-driven}, doi = {10.3390/su11133683}, url = {https://www.mdpi.com/2071-1050/11/13/3683https://www.mdpi.com/2071-1050/11/13/3683/pdf}, author = {Xu, Xiaodong and Yin, Chenhuan and Wang, Wei and Xu, Ning and Hong, Tianzhen and Li, Qi} } @article {31666, title = {The Squeaky wheel: Machine learning for anomaly detection in subjective thermal comfort votes}, journal = {Building and Environment}, volume = {151}, year = {2019}, month = {03/2019}, pages = {219 - 227}, abstract = {

Anomalous patterns in subjective votes can bias thermal comfort models built using data-driven approaches. A stochastic-based two-step framework to detect outliers in subjective thermal comfort data is proposed to address this problem. The anomaly detection technique involves defining similar conditions using a k-Nearest Neighbor (KNN) method and then quantifying the dissimilarity of the occupants{\textquoteright} votes from their peers under similar thermal conditions through a Multivariate Gaussian approach. This framework is used to detect outliers in the ASHRAE Global Thermal Comfort Database I \& II. The resulting anomaly-free dataset produced more robust comfort models avoiding dubious predictions. The proposed method has been proven to effectively distinguish outliers from inter-individual variabilities in thermal demand. The proposed anomaly detection framework could easily be applied to other applications with different variables or subjective metrics. Such a tool holds great promise for use in the development of occupancy responsive controls for automated building HVAC systems.

}, keywords = {anomaly detection, ASHRAE global thermal comfort database, K-nearest neighbors, Multivariate Gaussian, Occupancy responsive controls, Subjective votes, thermal comfort}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.01.050}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0360132319300861}, author = {Zhe Wang and Thomas Parkinson and Peixian Li and Borong Lin and Tianzhen Hong} } @article {30727, title = {Bidirectional low temperature district energy systems with agent-based control: Performance comparison and operation optimization}, journal = {Applied Energy}, volume = {209}, year = {2018}, doi = {10.1016/j.apenergy.2017.10.072}, author = {Felix Bunning and Michael Wetter and Marcus Fuchs and Dirk Muller} } @article {31313, title = {Buildings.Occupants: a Modelica package for modelling occupant behaviour in buildings}, journal = {Journal of Building Performance Simulation}, year = {2018}, month = {11/2018}, pages = {1 - 12}, abstract = {

Energy-related occupant behaviour is crucial to design and operation of energy and control systems in buildings. Occupant behaviours are often oversimplified as static schedules or settings in building performance simulation ignoring their stochastic nature. The continuous and dynamic interaction between occupants and building systems motivates their simultaneous simulation in an efficient manner. In the past, simultaneous simulation has relied on co-simulation approaches or customized source code changes to building simulation programmes. This paper presents Buildings. Occupants, an open-source package implemented in Modelica, for the simulation of occupant behaviours of lighting, windows, blinds, heating and air conditioning systems in office and residential buildings. Examples were presented to illustrate how the models in the Occupants package are capable to simulate stochastic occupant behaviours. The major contribution of this work is to introduce the equation-based modelling approach to simulate occupant behaviours in buildings and to develop an open-source Occupants package in the Modelica language

}, keywords = {modelica, Modelica Buildings Library, Modelica Occupants Package, Occupant Behaviour, Occupant behaviour modelling}, issn = {1940-1493}, doi = {10.1080/19401493.2018.1543352}, url = {https://www.tandfonline.com/doi/full/10.1080/19401493.2018.1543352https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.1543352}, author = {Zhe Wang and Tianzhen Hong and Ruoxi Jia} } @conference {31743, title = {Control Description Language}, booktitle = {1st American Modelica Conference}, year = {2018}, month = {08/2018}, abstract = {

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.

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.

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

}, keywords = {buildings, controls, hvac}, url = {https://simulationresearch.lbl.gov/wetter/download/2018-americanModelica-WetterGrahovacHu.pdf}, author = {Michael Wetter and Milica Grahovac and Jianjun Hu} } @article {31495, title = {Efficient modeling of optically-complex, non-coplanar exterior shading: Validation of matrix algebraic methods}, journal = {Energy and Buildings}, volume = {174}, year = {2018}, month = {09/2018}, pages = {464 - 483}, abstract = {

It has long been established that shading windows with overhangs, fins, and other types of non-coplanar systems (NCS) is one of the most effective ways of controlling solar heat gains in buildings because they intercept solar radiation prior to entry into the building. Designers however often specify non-opaque materials (e.g., louvers, fritted glass, expanded metal mesh) for these systems in order to admit daylight, reduce lighting energy use, and improve indoor environmental quality. Most simulation tools rely on geometric calculations and radiosity methods to model the solar heat gain impacts of NCS and cannot model optically-complex materials or geometries. For daylighting analysis, optically-complex NCS can be modeled using matrix algebraic methods, although time-efficient parametric analysis has not yet been implemented. Determining the best design and/or material for static or operable NCS that minimize cooling, heating, and lighting energy use and peak demand requires an iterative process. This study describes and validates a matrix algebraic method that enables parametric energy analysis of NCS. Such capabilities would be useful not only for design but also for development of prescriptive energy-efficiency standards, rating and labeling systems for commercial products, development of design guidelines, and development of more optimal NCS technologies.

A facade or "F" matrix, which maps the transfer of flux from the NCS to the surface of the window, is introduced and its use is explained. A field study was conducted in a full-scale outdoor testbed to measure the daylight performance of an operable drop-arm awning. Simulated data were compared to measured data in order to validate the models. Results demonstrated model accuracy: simulated workplane illuminance was within 11-13\%, surface luminance was within 16-18\%, and the daylight glare probability was within 6-9\% of measured results. Methods used to achieve accurate results are discussed. Results of the validation of daylighting performance are applicable to solar heat gain performance. Since exterior shading can also significantly reduce peak demand, these models enable stakeholders to more accurately assess HVAC and lighting impacts in support of grid management and resiliency goals.

}, keywords = {bidirectional scattering distribution function (BSDF), daylighting, exterior shading, solar heat gains, validation; building energy simulation tools, windows.}, issn = {03787788}, doi = {10.1016/j.enbuild.2018.06.022}, url = {https://www.sciencedirect.com/science/article/pii/S0378778818302457?via\%3Dihub}, author = {Taoning Wang and Gregory Ward and Eleanor S. Lee} } @article {30488, title = {Modeling occupancy distribution in large spaces with multi-feature classification algorithm}, journal = {Building and Environment}, volume = {137}, year = {2018}, abstract = {

Occupancy information enables robust and flexible control of heating, ventilation, and air-conditioning (HVAC) systems in buildings. In large spaces, multiple HVAC terminals are typically installed to provide cooperative services for different thermal zones, and the occupancy information determines the cooperation among terminals. However, a person count at room-level does not adequately optimize HVAC system operation due to the movement of occupants within the room that creates uneven load distribution. Without accurate knowledge of the occupants{\textquoteright} spatial distribution, the uneven distribution of occupants often results in under-cooling/heating or over-cooling/heating in some thermal zones. Therefore, the lack of high-resolution occupancy distribution is often perceived as a bottleneck for future improvements to HVAC operation efficiency. To fill this gap, this study proposes a multi-feature k-Nearest-Neighbors (k-NN) classification algorithm to extract occupancy distribution through reliable, low-cost Bluetooth Low Energy (BLE) networks. An on-site experiment was conducted in a typical office of an institutional building to demonstrate the proposed methods, and the experiment outcomes of three case studies were examined to validate detection accuracy. One method based on City Block Distance (CBD) was used to measure the distance between detected occupancy distribution and ground truth and assess the results of occupancy distribution. The results show the accuracy when CBD = 1 is over 71.4\% and the accuracy when CBD = 2 can reach up to 92.9\%.

}, keywords = {energy efficiency, HVAC loads, multi-feature classification algorithm, occupancy distribution, occupancy-based control}, doi = {10.1016/j.buildenv.2018.04.002}, author = {Wei Wang and Jiayu Chen and Tianzhen Hong} } @article {31309, title = {Occupancy prediction through machine learning and data fusion of environmental sensing and Wi-Fi sensing in buildings}, journal = {Automation in Construction}, volume = {94}, year = {2018}, month = {10/2018}, pages = {233 - 243}, abstract = {

Occupancy information is crucial to building facility design, operation, and energy efficiency. Many studies propose the use of environmental sensors (such as carbon dioxide, air temperature, and relative humidity sensors) and radio-frequency sensors (Wi-Fi networks) to monitor, assess, and predict occupancy information for buildings. As many methods have been developed and a variety of sensory data sources are available, establishing a proper selection of model and data source is critical to the successful implementation of occupancy prediction systems. This study compared three popular machine learning algorithms, including k-nearest neighbors (kNN), support vector machine (SVM), and artificial neural network (ANN), combined with three data sources, including environmental data, Wi-Fi data, and fused data, to optimize the occupancy models{\textquoteright} performance in various scenarios. Three error measurement metrics, the mean average error (MAE), mean average percentage error (MAPE), and root mean squared error (RMSE), have been employed to compare the models{\textquoteright} accuracies. Examined with an on-site experiment, the results suggest that the ANN-based model with fused data has the best performance, while the SVM model is more suitable with Wi-Fi data. The results also indicate that, comparing with independent data sources, the fused data set does not necessarily improve model accuracy but shows a better robustness for occupancy prediction.

}, keywords = {data fusion, environmental sensing, Machine learning, occupancy prediction, Wi-Fi sensing}, issn = {09265805}, doi = {10.1016/j.autcon.2018.07.007}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0926580518302656https://api.elsevier.com/content/article/PII:S0926580518302656?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0926580518302656?httpAccept=text/plain}, author = {Wei Wang and Jiayu Chen and Tianzhen Hong} } @article {31304, title = {Occupancy prediction through Markov based feedback recurrent neural network (M-FRNN) algorithm with WiFi probe technology}, journal = {Building and Environment}, volume = {138}, year = {2018}, month = {06/2018}, pages = {160 - 170}, abstract = {

Accurate occupancy prediction can improve facility control and energy efficiency of buildings. In recent years, buildings{\textquoteright} exiting WiFi infrastructures have been widely studied in the research of occupancy and energy conservation. However, using WiFi to assess occupancy is challenging due to that occupancy information is often characterized stochastically and varies with time and easily disturbed by building components. To overcome such limitations, this study utilizes WiFi probe technology to actively scan WiFi connection requests and responses between access points and network devices of building occupants. With captured signals, this study proposed a Markov based feedback recurrent neural network (M-FRNN) algorithm to model and predict the occupancy profiles. One on-site experiment was conducted to collect ground truth data using camera-based video analysis and the results were used to validate the M-FRNN occupancy prediction model over a 9-day measurement period. From the results, the M-FRNN based occupancy model using WiFi probes shows best accuracies can reach 80.9\%, 89.6\%, and 93.9\% with a tolerance of 2, 3, and 4 occupants respectively. This study demonstrated that WiFi data coupled with stochastic machine learning system can provide a viable alternative to determine a building{\textquoteright}s occupancy profile.

}, issn = {03601323}, doi = {10.1016/j.buildenv.2018.04.034}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0360132318302464https://api.elsevier.com/content/article/PII:S0360132318302464?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0360132318302464?httpAccept=text/plain}, author = {Wei Wang and Jiayu Chen and Tianzhen Hong and Na Zhu} } @conference {31688, title = {OpenBuildingControl: Modeling Feedback Control as a Step Towards Formal Design, Specification, Deployment and Verification of Building Control Sequences}, booktitle = {2018 Building Performance Modeling Conference and SimBuild co-organized by ASHRAE and IBPSA-USA}, year = {2018}, month = {09/2018}, address = {Chicago, IL}, abstract = {

This paper presents ongoing work to develop tools and a process that will allow building designers to instantiate control sequences, configure them for their project, assess their performance in closed loop building energy simulation, and then export these sequences (i) for the control provider to bid on the project and to implement the sequences through machine-to-machine translation, and (ii) for the commissioning agent to verify their correct implementation.

The paper reports on the following: (i) The specification of a Control Description Language, (ii) its use to implement a subset of the ASHRAE Guideline 36 sequences, released as part of the Modelica Buildings library, (iii) its use in annual closed-loop simulations of a variable air- volume flow system, and (iv) lessons learned regarding simulation of closed-loop control.

In our case study, the Guideline 36 sequences yield 30\% lower annual site HYAC energy use, under comparable comfort, than sequences published earlier by ASHRAE. The 30\% differences in annual HYAC energy consumption due to changes in the control sequences raises the question of whether the idealization of control sequences that is common practice in today{\textquoteright}s building energy simulation leads to trustworthy energy use predictions.

}, url = {https://www.ashrae.org/File\%20Library/Conferences/Specialty\%20Conferences/2018\%20Building\%20Performance\%20Analysis\%20Conference\%20and\%20SimBuild/Papers/C107.pdf}, author = {Michael Wetter and Jianjun Hu and Milica Grahovac and Brent Eubanks and Philip Haves} } @article {31311, title = {Performance-Based Evaluation of Courtyard Design in China{\textquoteright}s Cold-Winter Hot-Summer Climate Regions}, journal = {Sustainability}, volume = {10}, year = {2018}, month = {10/2018}, pages = {3950}, abstract = {

Evaluates the performance of the traditional courtyard design of the Jiangnan Museum, located in Jiangsu Province. In the evaluation, the spatial layout of courtyards is adjusted, the aspect ratio is changed, and an ecological buffer space is created. To model and evaluate the performance of the courtyard design, this study applied the Computational fluid dynamics (CFD) software, Parabolic Hyperbolic Or Elliptic Numerical Integration Code Series (PHOENICS), for wind environment simulation, and the EnergyPlus-based software, DesignBuilder, for energy simulation. Results show that a good combination of courtyard layout and aspect ratio can improve the use of natural ventilation by increasing free cooling during hot summers and reducing cold wind in winters. The results also show that ecological buffer areas of a courtyard can reduce cooling loads in summer by approximately 19.6\% and heating loads in winter by approximately 22.3\%. The study provides insights into the optimal design of a courtyard to maximize its benefit in regulating the microclimate during both winter and summer.

}, keywords = {aspect ratio, courtyard design, ecological buffer area, ecological effect, layout}, doi = {10.3390/su10113950}, url = {http://www.mdpi.com/2071-1050/10/11/3950http://www.mdpi.com/2071-1050/10/11/3950/pdf}, author = {Xiaodong Xu and Fenlan Luo and Wei Wang and Tianzhen Hong and Xiuzhang Fu} } @article {30726, title = {Simplifications for hydronic system models in Modelica}, journal = {Journal of Building Performance Simulation}, year = {2018}, abstract = {

Building systems and their heating, ventilation and air conditioning ow networks, are becoming increasingly complex. Some building energy simulation tools simulate these ow networks using pressure drop equations. These ow network models typically generate coupled algebraic nonlinear systems of equations, which become increasingly more difficult to solve as their sizes increase. This leads to longer computation times and can cause the solver to fail. These problems also arise when using the equation-based modelling language Modelica and Annex 60 based libraries. This may limit the applicability of the library to relatively small problems unless problems are restructured. This paper discusses two algebraic loop types and presents an approach that decouples algebraic loops into smaller parts, or removes them completely. The approach is applied to a case study model where an algebraic loop of 86 iteration variables is decoupled into smaller parts with a maximum of 5 iteration variables.

}, doi = {10.1080/19401493.2017.1421263}, author = {Filip Jorissen and Michael Wetter and Lieve Helsen} } @article {31305, title = {Translating climate change and heating system electrification impacts on building energy use to future greenhouse gas emissions and electric grid capacity requirements in California}, journal = {Applied Energy}, volume = {225}, year = {2018}, month = {09/2018}, pages = {522 - 534}, abstract = {

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

}, keywords = {Building Energy Demand, Climate Change Impacts, electric grid, Heating Electrification Effects}, issn = {03062619}, doi = {10.1016/j.apenergy.2018.05.003}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261918306962https://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/plain}, author = {Brian Tarroja and Felicia Chiang and Amir AghaKouchak and Scott Samuelsen and Shuba V. Raghavan and Max Wei and Kaiyu Sun and Tianzhen Hong} } @article {30314, title = {Analysis of heating load diversity in German residential districts and implications for the application in district heating systems}, journal = {Energy and Buildings}, volume = {139}, year = {2017}, month = {01/2017}, pages = {302-313}, chapter = {302}, abstract = {

In recent years, the application of district heating systems for the heat supply of residential districts has been increasing in Germany. Central supply systems can be very efficient due to diverse energy demand profiles which may lead to reduced installed equipment capacity. Load diversity in buildings has been investigated in former studies, especially for the electricity demand. However, little is known about the influence of single building characteristics (such as building envelope or hot water demand) on the overall heating peak load of a residential district. For measuring the diversity, the peak load ratio (PLR) index is used to represent the percentage reduction of peak load of a district system from a simple sum of individual peak loads of buildings. A total of 144 residential building load profiles have been created with the dynamic building simulation software IDA ICE for a theoretical analysis in which the PLR reaches 15\%. Within this study, certain district features are identified which lead to higher diversity. Furthermore, these results are used in a district heating simulation model which confronts the possible advantage of reduced installed capacity with the practical disadvantage of heat distribution losses.\  Likewise, the influence of load density and the district{\textasciiacute}s building structure can be analyzed. This study shows that especially in districts with high load density, which consist of newly constructed buildings with low supply temperature and high influence of the hot water demand, the advantages of load diversity can be exploited.

}, keywords = {district heating, domestic hot water, dynamic building simulation, heat supply, Load diversity, peak load, residential district, space heating}, doi = {10.1016/j.enbuild.2016.12.096}, author = {Claudia Weissmann and Tianzhen Hong and Carl-Alexander Graubner} } @article {30028, title = {Data Analytics and Optimization of an Ice-Based Energy Storage System for Commercial Buildings}, year = {2017}, abstract = {

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice{\textendash}based TES system in a shopping mall, calculating the system{\textquoteright}s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential when the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system{\textquoteright}s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3\% per day and 9.3\% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.

}, keywords = {Data Analytics, energy cost saving, heuristic strategy, Machine learning, optimization, Thermal energy storage}, author = {Na Luo and Tianzhen Hong and Hui Li and Rouxi Jia and Wenguo Weng} } @article {30728, title = {Dynamic equation-based thermo-hydraulic pipe model for district heating and cooling systems}, journal = {Energy Conversion and Management}, volume = {151}, year = {2017}, abstract = {

Simulation and optimisation of district heating and cooling networks requires efficient and realistic models of the individual network elements in order to correctly represent heat losses or gains, temperature propagation and pressure drops. Due to more recent thermal networks incorporating meshing decentralised heat and cold sources, the system often has to deal with variable temperatures and mass flow rates, with flow reversal occurring more frequently. This paper presents the mathematical derivation and software implementation in Modelica of a thermo-hydraulic model for thermal networks that meets the above requirements and compares it to both experimental data and a commonly used model. Good correspondence between experimental data from a controlled test set-up and simulations using the presented model was found. Compared to measurement data from a real district heating network, the simulation results led to a larger error than in the controlled test set-up, but the general trend is still approximated closely and the model yields results similar to a pipe model from the Modelica Standard Library. However, the presented model simulates 1.7 (for low number of volumes) to 68 (for highly discretized pipes) times faster than a conventional model for a realistic test case. A working implementation of the presented model is made openly available within the IBPSA Modelica Library. The model is robust in the sense that grid size and time step do not need to be adapted to the flow rate, as is the case in finite volume models.

}, doi = {10.1016/j.enconman.2017.08.072}, author = {Brahm van der Heijde and Marcus Fuchs and Carles Ribas Tugores and Gerald Schweiger and Kevin Sartor and Daniele Basciotti and Dirk Muller and Christoph Nytsch-Geusen and Michael Wetter and Lieve Helsen} } @article {62077, title = {Energy saving potential of a two-pipe system for simultaneous heating and cooling of office buildings}, journal = {Energy and Buildings}, volume = {134}, year = {2017}, month = {01/2017}, pages = {234 - 247}, abstract = {

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

}, keywords = {active beams, energy saving, HVAC systems, low-exergy, modelica, simulation}, issn = {03787788}, doi = {10.1016/j.enbuild.2016.10.051}, author = {Alessandro Maccarini and Michael Wetter and Alireza Afshari and Goran Hultmark and Niels Bergsoe and Anders Vorre} } @conference {31830, title = {MPCPy: An Open-Source Software Platform for Model Predictive Control in Buildings}, booktitle = {Proceedings of the 15th IBPSA Conference: Building Simulation 2017}, year = {2017}, month = {08/2017}, address = {San Francisco}, abstract = {

Within the last decade, needs for building control systems that reduce cost, energy, or peak demand, and that facilitate building-grid integration, district-energy system optimization, and occupant interaction, while maintaining thermal comfort and indoor air quality, have come about.\  Current PID and schedule-based control systems are not capable of fulfilling these needs, while Model Predictive Control (MPC) could.\  Despite the critical role MPC-enabled buildings can play in future energy infrastructures, widespread adoption of MPC within the building industry has yet to occur.\  To address barriers associated with system setup and configuration, this paper introduces an open-source software platform that emphasizes use of self-tuning adaptive models, usability by non-experts of MPC, and a flexible architecture that enables application across projects.

}, keywords = {Model predictive control (MPC)}, url = {http://www.ibpsa.org/proceedings/BS2017/BS2017_351.pdf}, author = {David Blum and Michael Wetter} } @conference {30147, title = {A Tale of Three District Energy Systems: Metrics and Future Opportunities}, booktitle = {2016 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2016}, month = {08/2017}, abstract = {

Improving the sustainability of cities is crucial for meeting climate goals in the next several decades. One way this is being tackled is through innovation in district energy systems, which can take advantage of local resources and economies of scale to improve the performance of whole neighborhoods in ways infeasible for individual buildings. These systems vary in physical size, end use services, primary energy resources, and sophistication of control. They also vary enormously in their choice of optimization metrics while all under the umbrella-goal of improved sustainability.

This paper explores the implications of choice of metric on district energy systems using three case studies: Stanford University, the University of California at Merced, and the Richmond Bay campus of the University of California at Berkeley. They each have a centralized authority to implement large-scale projects quickly, while maintaining data records, which makes them relatively effective at achieving their respective goals. Comparing the systems using several common energy metrics reveals significant differences in relative system merit. Additionally, a novel bidirectional heating and cooling system is presented. This system is highly energy-efficient, and while more analysis is required, may be the basis of the next generation of district energy systems

}, author = {Rebecca Zarin Pass and Michael Wetter and Mary Ann Piette} } @article {60350, title = {Design choices for thermofluid flow components and systems that are exported as Functional Mockup Units}, year = {2015}, abstract = {

This paper discusses design decisions for exporting Modelica thermofluid flow components as Functional Mockup Units. The purpose is to provide guidelines that will allow building energy simulation programs and HVAC equipment manufacturers to effectively use FMUs for modeling of HVAC components and systems. We provide an analysis for direct input-output dependencies of such components and discuss how these dependencies can lead to algebraic loops that are formed when connecting thermofluid flow components. Based on this analysis, we provide recommendations that increase the computing efficiency of such components and systems that are formed by connecting multiple components. We explain what code optimizations are lost when providing thermofluid flow components as FMUs rather than Modelica code. We present an implementation of a package for FMU export of such components, explain the rationale for selecting the connector variables of the FMUs and finally provide computing benchmarks for different design choices. It turns out that selecting temperature rather than specific enthalpy as input and output signals does not lead to a measurable increase in computing time, but selecting nine small FMUs rather than a large FMU increases computing time by 70\%

}, author = {Michael Wetter and Marcus Fuchs and Thierry Stephane Nouidui} } @article {60342, title = {Equation-based languages {\textendash} A new paradigm for building energy modeling, simulation and optimization}, journal = {Energy and Buildings}, volume = {117}, year = {2015}, month = {04/2016}, pages = {290-300}, abstract = {

Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization.

We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller that adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. Exploiting the equation-based language led to 2200 times faster solution.

}, keywords = {Equation-based modeling, modelica, Multi-physics simulation, Optimal control, smart grid}, doi = {10.1016/j.enbuild.2015.10.017}, author = {Michael Wetter and Marco Bonvini and Thierry Stephane Nouidui} } @article {60352, title = {Modelica Buildings Library}, year = {2015}, author = {Michael Wetter and Wangda Zuo and Thierry Stephane Nouidui and Xiufeng Pang} } @article {60351, title = {Simulation Speed Analysis and Improvements of Modelica Models for Building Energy Simulation}, year = {2015}, abstract = {

This paper presents an approach for speeding up Modelica models. Insight is provided into how Modelica models are solved and what determines the tool{\textquoteright}s computational speed. Aspects such as algebraic loops, code efficiency and integrator choice are discussed. This is illustrated using simple building simulation examples and Dymola. The generality of the work is in some cases verified using OpenModelica. Using this approach, a medium sized office building including building envelope, heating ventilation and air conditioning (HVAC) systems and control strategy can be simulated at a speed five hundred times faster than real time.

}, author = {Filip Jorissen and Michael Wetter and Lieve Helsen} } @article {60154, title = {Development of Diagnostic and Measurement and Verification Tools for Commercial Buildings}, year = {2014}, month = {09/2014}, institution = {California Energy Commission}, abstract = {

This research developed new measurement and verification tools and new automated fault detection and diagnosis tools, and deployed them in the Universal Translator. The Universal Translator is a tool, developed by Pacific Gas and Electric, that manages large sets of measured data from building control systems and enables off-line analysis of building performance. There were four technical projects following the program administration tasks identified as Project 1:

  1. Program Administration
  2. Methods and Tools to Reduce the Cost of Measurement and Verification.
  3. Fault Detection and Diagnostics for Commercial Heating, Ventilating, and Air- Conditioning Systems.
  4. Test Procedures and Tools to Characterize Fan and Duct System Performance in Large Commercial Buildings.
  5. Universal Translator Development: Integration of Application Programming Interface.

Project 1 consisted of administrative tasks related to the project.

Project 2 addressed the need for less expensive measurement and verification tools to determine the costs and benefits of retrofits and retro-commissioning at both the individual building level and the utility program level.

Project 3 extended previous work on fault detection and diagnosis to additional systems and subsystems, including dual duct heating, ventilating and air-conditioning systems and fan-coil terminal units.

Project 4 combined previous work on duct leakage and fan modeling to develop a performance assessment method for existing fan/duct systems that could also be used in the analysis of retrofit measures identified by the tools in Projects 2 and 3 using the EnergyPlus simulation program to help select the most cost-effective package of improvements.

Some of the diagnostic methods and tools developed in projects 2 through 4 were incorporated in the Universal Translator via a new application programming interface that was specified, developed and tested in Project 5. Combined, these tools support analyses of energy savings produced by new construction commissioning, retro-commissioning, improved routine operations and code compliance. The new application programming interface could also facilitate future development, testing and deployment of new diagnostic tools.

}, keywords = {application programming interface, fault detection and diagnosis, M\&V, Measurement and verification, Universal Translator}, author = {Philip Haves and Craig P. Wray and David A. Jump and Daniel Veronica and Christopher Farley} } @article {59969, title = {Integrated Design for High Performance Buildings}, year = {2014}, author = {Tianzhen Hong and Cheng Li and Richard C. Diamond and Da Yan and Qi Zhang and Xin Zhou and Siyue Guo and Kaiyu Sun and Jingyi Wang} } @conference {59967, title = {A New Model to Simulate Energy Performance of VRF Systems}, year = {2014}, abstract = {

This paper presents a new model to simulate energy performance of variable refrigerant flow (VRF) systems in heat pump operation mode (either cooling or heating is provided but not simultaneously). The main improvement of the new model is the introduction of the evaporating and condensing temperature in the indoor and outdoor unit capacity modifier functions. The independent variables in the capacity modifier functions of the existing VRF model in EnergyPlus are mainly room wet-bulb temperature and outdoor dry-bulb temperature in cooling mode and room dry-bulb temperature and outdoor wet-bulb temperature in heating mode. The new approach allows compliance with different specifications of each indoor unit so that the modeling accuracy is improved. The new VRF model was implemented in a custom version of EnergyPlus 7.2. This paper first describes the algorithm for the new VRF model, which is then used to simulate the energy performance of a VRF system in a Prototype House in California that complies with the requirements of Title 24 {\textendash} the California Building Energy Efficiency Standards. The VRF system performance is then compared with three other types of HVAC systems: the Title 24-2005 Baseline system, the traditional High Efficiency system, and the EnergyStar Heat Pump system in three typical California climates: Sunnyvale, Pasadena and Fresno. Calculated energy savings from the VRF systems are significant. The HVAC site energy savings range from 51 to 85\%, while the TDV (Time Dependent Valuation) energy savings range from 31 to 66\% compared to the Title 24 Baseline Systems across the three climates. The largest energy savings are in Fresno climate followed by Sunnyvale and Pasadena. The paper discusses various characteristics of the VRF systems contributing to the energy savings. It should be noted that these savings are calculated using the Title 24 prototype House D under standard operating conditions. Actual performance of the VRF systems for real houses under real operating conditions will vary.

}, author = {Tianzhen Hong and Xiufeng Pang and Oren Schetrit and Liping Wang and Shinichi Kasahara and Yoshinori Yura and Ryohei Hinokuma} } @article {56245, title = {A Detailed Loads Comparison of Three Building Energy Modeling Programs: EnergyPlus, DeST and DOE-2.1E}, journal = {Building Simulation}, volume = {6}, year = {2013}, month = {09/2013}, pages = {323-335}, publisher = {Tsinghua University Press}, chapter = {323}, abstract = {

Building energy simulation is widely used to help design energy efficient building envelopes and HVAC systems, develop and demonstrate compliance of building energy codes, and implement building energy rating programs. However, large discrepancies exist between simulation results from different building energy modeling programs (BEMPs). This leads many users and stakeholders to lack confidence in the results from BEMPs and building simulation methods. This paper compared the building thermal load modeling capabilities and simulation results of three BEMPs: EnergyPlus, DeST and DOE-2.1E. Test cases, based upon the ASHRAE Standard 140 tests, were designed to isolate and evaluate the key influencing factors responsible for the discrepancies in results between EnergyPlus and DeST. This included the load algorithms and some of the default input parameters. It was concluded that there is little difference between the results from EnergyPlus and DeST if the input values are the same or equivalent despite there being many discrepancies between the heat balance algorithms. DOE-2.1E can produce large errors for cases when adjacent zones have very different conditions, or if a zone is conditioned part-time while adjacent zones are unconditioned. This was due to the lack of a strict zonal heat balance routine in DOE-2.1E, and the steady state handling of heat flow through interior walls and partitions. This comparison study did not produce another test suite, but rather a methodology to design tests that can be used to identify and isolate key influencing factors that drive the building thermal loads, and a process with which to carry them out.

}, keywords = {building energy modeling program, building thermal loads, comparison, dest, DOE-2.1E, energyplus}, issn = {Print: 1996-3599; Online 1996-8744}, doi = {10.1007/s12273-013-0126-7}, author = {Dandan Zhu and Tianzhen Hong and Da Yan and Chuang Wang} } @proceedings {57000, title = {Functional Mock-Up Unit Import in EnergyPlus For Co-Simulation}, year = {2013}, month = {08/2013}, address = {Chambery, France}, abstract = {

This paper describes how to use the recently implemented Functional Mock-up Unit (FMU) for co-simulation import interface in EnergyPlus to link EnergyPlus with simulation tools packaged as FMUs. The interface complies with the Functional Mock-up Interface (FMI) for co-simulation standard version 1.0, which is an open standard designed to enable links between different simulation tools that are packaged as FMUs. This article starts with an introduction of the FMI and FMU concepts. We then discuss the implementation of the FMU import interface in EnergyPlus. After that, we present two use cases. The first use case is to model a HVAC system in Modelica, export it as an FMU, and link it to a room model in EnergyPlus. The second use case is an extension of the first case where a shading controller is modeled in Modelica, exported as an FMU, and used in the EnergyPlus room model to control the shading device of one of its windows. In both cases, the FMUs are imported into EnergyPlus which models the building envelope and manages the data-exchange between the envelope and the systems in the FMUs during run-time.

}, author = {Thierry Stephane Nouidui and Michael Wetter and Wangda Zuo} } @conference {2673, title = {Comparative research in building energy modeling programs}, booktitle = {China Annual HVACR Conference}, year = {2012}, month = {06/2011}, address = {China (in Chinese)}, keywords = {advanced building software: energyplus, building energy modeling program, building simulation, comparison, dest, doe-2, energyplus, simulation research group, test}, author = {Dandan Zhu and Tianzhen Hong and Da Yan and Chuang Wang} } @article {3445, title = {Comparison of Building Energy Modeling Programs: Building Loads}, year = {2012}, month = {06/2012}, author = {Dandan Zhu and Tianzhen Hong and Chuang Wang} } @conference {3444, title = {The Energy Saving Potential of Membrane-Based Enthalpy Recovery in Vav Systems for Commercial Office Buildings}, booktitle = {SimBuild 2012 IBPSA Conference}, year = {2012}, abstract = {

A design tool to evaluate the heat and mass transfer effectiveness and pressure drop of a membrane-based enthalpy exchanger was developed and then used to optimize the configuration of an enthalpy exchanger for minimum pressure drop and maximum heat recovery effectiveness. Simulation was used in a parametric study to investigate the energy saving potential of the enthalpy recovery system. The case without energy recovery and air side economizer was used as a baseline. Two comparison cases for the implementation of enthalpy recovery with and without air side economizer were simulated in EnergyPlus. A case using a desiccant wheel for energy recovery was also investigated for comparison purposes. The simulation results show significant energy saving benefits from applying a low pressure drop, high effectiveness enthalpy exchanger in two US cities representing a range of humid climates. The sensitivity of the energy savings potential to pressure drop and heat and mass transfer effectivenesses is also presented.

}, author = {Liping Wang and Philip Haves and John Breshears} } @conference {3407, title = {The Energy Saving Potential of Membrane-Based Enthalpy Recovery in VAV System for Commercial Office Buildings}, booktitle = {SimBuild 2012}, year = {2012}, month = {08/2012}, address = {Madison, Wisconsin}, author = {Liping Wang and Philip Haves and John Breshears} } @article {2591, title = {A framework for simulation-based real-time whole building performance assessment}, journal = {Building and Environment}, volume = {54}, year = {2012}, month = {08/2012}, pages = {100-108}, chapter = {100}, abstract = {

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures. One approach to addressing this problems is to compare the predictions of an energy simulation model of the building to the measured performance and analyze significant differences to infer the presence and location of faults. This paper presents a framework that allows a comparison of building actual performance and expected performance in real time. The realization of the framework utilized the EnergyPlus, the Building Controls Virtual Test Bed (BCVTB) and the Energy Management and Control System (EMCS) was developed. An EnergyPlus model that represents expected performance of a building runs in real time and reports the predicted building performance at each time step. The BCVTB is used as the software platform to acquire relevant inputs from the EMCS through a BACnet interface and send them to the EnergyPlus and to a database for archiving. A proof-of-concept demonstration is also presented.

}, keywords = {building controls virtual test bed, building performance, energy modeling, energyplus, real-time building simulation}, issn = {0360-1323}, author = {Xiufeng Pang and Michael Wetter and Prajesh Bhattacharya and Philip Haves} } @conference {3442, title = {An Improved Simple Chilled Water Cooling Coil Model}, booktitle = {SimBuild 2012 IBPSA Conference}, year = {2012}, month = {08/2012}, abstract = {

The accurate prediction of cooling and dehumidification coil performance is important in model-based fault detection and in the prediction of HVAC system energy consumption for support of both design and operations. It is frequently desirable to use a simple cooling coil model that does not require detailed specification of coil geometry and material properties. The approach adopted is to match the overall UA of the coil to the rating conditions and to estimate the air-side and water-side components of the UA using correlations developed by Holmes (1982). This approach requires some geometrical information about the coil and the paper investigates the sensitivity of the overall performance prediction to uncertainties in this information, including assuming a fixed ratio of air-side to water-side UA at the rating condition. Finally, simulation results from different coil models are compared, and experimental data are used to validate the improved cooling coil model.

}, author = {Liping Wang and Philip Haves and Walter F. Buhl} } @article {3414, title = {Monitoring-based HVAC Commissioning of an Existing Office Building for Energy Efficiency}, year = {2012}, month = {10/2012}, abstract = {

The performance of Heating, Ventilation and Air Conditioning (HVAC) systems may fail to satisfy design expectations due to improper equipment installation, equipment degradation, sensor failures, or incorrect control sequences. Commissioning identifies and implements cost-effective operational and maintenance measures in buildings to bring them up to the design intent or optimum operation. An existing office building is used as a case study to demonstrate the process of commissioning. Building energy benchmarking tools are applied to evaluate the energy performance for screening opportunities at the whole building level. A large natural gas saving potential was indicated by the building benchmarking results. Faulty operations in the HVAC systems, such as improper operations of air-side economizers, simultaneous heating and cooling, and ineffective optimal start, were identified through trend data analyses and functional testing. The energy saving potential for each commissioning measure is quantified with a calibrated building simulation model. An actual energy saving of 10\% was realized after the implementations of cost-effective measures.

}, keywords = {benchmarking, commissioning, energyplus, fault detection and diagnostics, functional testing, trend data}, author = {Shankar Earni and Spencer Woodworth and Xiufeng Pang and Jorge Hernandez-Maldonado and Rongxin Yin and Liping Wang and Steve E. Greenberg and John Fiegel and Alma Rubalcava} } @article {57517, title = {Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building}, journal = {Energy and Buildings}, volume = {53}, year = {2012}, month = {10/2012}, pages = {152 - 158}, keywords = {Building Operations, energyplus, Monte Carlo Analysis, Uncertainties}, issn = {03787788}, doi = {10.1016/j.enbuild.2012.06.017}, author = {Liping Wang and Paul A. Mathew and Xiufeng Pang} } @proceedings {3408, title = {Validation and Application of the Room Model of the Modelica Buildings Library}, year = {2012}, month = {09/2012}, address = {Munich, Germany}, abstract = {

The Modelica Buildings library contains a package with a model for a thermal zone that computes heat transfer through the building envelope and within a room. It considers various heat transfer phenomena of a room, including conduction, convection, short-wave and long-wave radiation. The first part of this paper describes the physical phenomena considered in the room model. The second part validates the room model by using a standard test suite provided by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). The third part focuses on an application where the room model is used for simulation-based controls of a window shading device to reduce building energy consumption.

}, author = {Thierry Stephane Nouidui and Phalak, Kaustubh and Wangda Zuo and Michael Wetter} } @article {3182, title = {Validation of the Window Model of the Modelica Buildings Library}, year = {2012}, month = {07/2012}, abstract = {

This paper describes the validation of the window model of the free open-source Modelica Buildings library. This paper starts by describing the physical modeling assumptions of the window model. The window model can be used to calculate the thermal and angular properties of glazing systems. It can also be used for steady-state simulation of heat transfer mechanism in glazing systems. We present simulation results obtained by comparing the window model with WINDOW 6 the well established simulation tool for steady-state heat transfer in glazing systems. We also present results obtained by comparing the window model with measurements carried out in a test cell at the Lawrence Berkeley National Laboratory.

}, author = {Thierry Stephane Nouidui and Michael Wetter and Wangda Zuo} } @proceedings {2783, title = {Advanced simulations of building energy and control systems with an example of chilled water plant modeling}, year = {2011}, address = {Nanjing, China}, author = {Wangda Zuo and Michael Wetter} } @conference {2631, title = {An Assessment of the use of Building Energy Performance Simulation in Early Design}, booktitle = {IBPSA Building Simulation 2011}, year = {2011}, month = {11/2011}, address = {Sydney, Australia}, author = {Vladimir Bazjanac and Tobias Maile and Cody Rose and James O{\textquoteright}Donnell and Natasa Mrazovic and Elmer Morrissey and Welle, Benjamin} } @article {3181, title = {BacNet and Analog/Digital Interfaces of the Building Controls Virtual Testbed}, year = {2011}, month = {11/2011}, abstract = {

This paper gives an overview of recent developments in the Building Controls Virtual Test Bed (BCVTB), a framework for co-simulation and hardware-in-the-loop.

First, a general overview of the BCVTB is presented. Second, we describe the BACnet interface, a link which has been implemented to couple BACnet devices to the BCVTB. We present a case study where the interface was used to couple a whole building simulation program to a building control system to assess in real-time the performance of a real building. Third, we present the ADInterfaceMCC, an analog/digital interface that allows a USB-based analog/digital converter to be linked to the BCVTB. In a case study, we show how the link was used to couple the analog/digital converter to a building simulation model for local loop control.

}, author = {Philip Haves and Prajesh Bhattacharya and Thierry Stephane Nouidui and Michael Wetter and Zhengwei Li and Xiufeng Pang} } @proceedings {2785, title = {BACnet and Analog/Digital Interfaces of the Building Controls Virtual Test Bed}, year = {2011}, month = {11/2011}, pages = {p. 294-301}, address = {Sydney, Australia}, author = {Thierry Stephane Nouidui and Michael Wetter and Zhengwei Li and Xiufeng Pang and Prajesh Bhattacharya and Philip Haves} } @conference {3404, title = {A Comparison of DeST and EnergyPlus}, booktitle = {China HVAC Simulation Conference}, year = {2011}, month = {2011}, address = {Beijing}, keywords = {building simulation, comparison, dest, energy modeling, energyplus, simulation research, simulation research group, test cases}, author = {Dandan Zhu and Chuang Wang and Da Yan and Tianzhen Hong} } @article {2578, title = {Co-simulation of building energy and control systems with the Building Controls Virtual Test Bed}, journal = {Journal of Building Performance Simulation}, volume = {3}, year = {2011}, month = {11/2010}, abstract = {

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.

}, keywords = {building simulation, co-simulation, integrated analysis, modular modelling}, doi = {10.1080/19401493.2010.518631}, author = {Michael Wetter} } @conference {2672, title = {Modeling and simulation of HVAC faults in EnergyPlus}, booktitle = {Building Simulation 2011}, year = {2011}, month = {11/2011}, address = {Australia}, keywords = {advanced building software: energyplus, building simulation, energyplus, faults, fouling, modeling, sensor offset, simulation research group}, author = {Mangesh Basarkar and Philip Haves and Xiufeng Pang and Liping Wang and Tianzhen Hong} } @article {3179, title = {Modeling and simulation of HVAC Results in EnergyPlus}, year = {2011}, month = {11/2011}, author = {Mangesh Basarkar and Xiufeng Pang and Liping Wang and Tianzhen Hong} } @proceedings {2786, title = {Modeling of Heat Transfer in Rooms in the Modelica "Buildings" Library}, year = {2011}, month = {11/2011}, pages = {1096-1103}, address = {Sydney, Australia}, author = {Michael Wetter and Wangda Zuo and Thierry Stephane Nouidui} } @proceedings {2787, title = {Real-time Building Energy Simulation using EnergyPlus and the Building Controls Virtual Test Bed}, year = {2011}, month = {11/2011}, pages = {p. 2890-2896}, address = {Sydney, Australia}, abstract = {

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures (Haves et al., 2001, Lee et al., 2007). To address this problem, the paper presents a simulation-based whole building performance monitoring tool that allows a comparison of building actual performance and expected performance in real time. The tool continuously acquires relevant building model input variables from existing Energy Management and Control System (EMCS). It then reports expected energy consumption as simulated of EnergyPlus. The Building Control Virtual Test Bed (BCVTB) is used as the software platform to provide data linkage between the EMCS, an EnergyPlus model, and a database. This paper describes the integrated real-time simulation environment. A proof-of-concept demonstration is also presented in the paper.

}, author = {Xiufeng Pang and Prajesh Bhattacharya and Zheng O{\textquoteright}Neill and Philip Haves and Michael Wetter and Trevor Bailey} } @proceedings {2782, title = {Recent developments of the Modelica Buildings library for building energy and control systems}, year = {2011}, address = {Dresden, Germany}, abstract = {

At the Modelica 2009 conference, we introduced the Buildings library, a freely available Modelica library for building energy and control systems [16]. This paper reports the updates of the library and presents example applications for a range of heating, ventilation and air conditioning (HVAC) systems. Over the past two years, the library has been further developed. The number of HVAC components models has been doubled and various components have been revised to increase numerical robustness. The paper starts with an overview of the library architecture and a description of the main packages. To demonstrate the features of the Buildings library, applications that include multizone airow simulation as well as supervisory and local loop control of a variable air volume (VAV) system are briey described. The paper closes with a discussion of the current development.

}, keywords = {building energy systems, heating}, url = {https://www.modelica.org/events/modelica2011/Proceedings/pages/papers/12_1_ID_113_a_fv.pdf}, author = {Michael Wetter and Wangda Zuo and Thierry Stephane Nouidui} } @article {67, title = {A comparison of global optimization algorithms with standard benchmark functions and real-world applications using EnergyPlus}, journal = {Journal of Building Performance Simulation}, volume = {3}, year = {2010}, pages = {103-120}, abstract = {

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.

}, keywords = {algorithm, application using energyplus, building energy minimization, covariance matrix adaptation evolution strategy algorithm and hybrid differential evolution, optimization, particle swarm optimization and hooke-jeeves}, doi = {10.1080/19401490903494597}, author = {J{\'e}r{\^o}me Henri K{\"a}mpf and Michael Wetter and Darren Robinson} } @article {75, title = {Co-simulation for performance prediction of integrated building and HVAC systems - An analysis of solution characteristics using a two-body system}, journal = {Simulation Modelling Practice and Theory}, volume = {18}, year = {2010}, month = {08/2010}, pages = {957-970}, chapter = {957}, abstract = {

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.

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.

}, doi = {10.1016/j.simpat.2010.02.011}, author = {Marija Trcka and Jan Hensen and Michael Wetter} } @conference {244, title = {Development and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage}, booktitle = {2010 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2010}, publisher = {Omnipress}, organization = {Omnipress}, address = {Asilomar, California, USA}, abstract = {

A Model Predictive Control (MPC) implementation was developed for a university campus chilled water plant. The plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. A detailed model of the chilled water plant and simplified models of the campus buildings were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers{\textquoteright} performance data, and calibrated using measured data collected and archived by the control system. A dynamic model of the chilled water storage tank was also developed and calibrated. A semi-empirical model was developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a MPC algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The paper describes the development and testing of the MPC implementation and discusses lessons learned and next steps in further research.

}, issn = {0-918249-60-0}, author = {Brian E. Coffey and Philip Haves and Michael Wetter and Brandon Hencey and Francesco Borrelli and Yudong Ma and Sorin Bengea} } @article {249, title = {Impacts of Static Pressure Reset on VAV System Air Leakage, Fan Power, and Thermal Energy}, journal = {ASHRAE Transactions}, volume = {116}, year = {2010}, pages = {428-436}, author = {Mingsheng Liu and Jingjuan Feng and Zhan Wang and Keke Zheng and Xiufeng Pang} } @article {237, title = {Case study of zero energy house design in UK}, journal = {Energy and Buildings}, volume = {41}, year = {2009}, month = {11/2009}, pages = {1215-1222}, author = {Liping Wang and Julie Gwilliam and Phillip Jones} } @article {250, title = {CCLEP Reduces Energy Consumption by More than 50\% for a Luxury Shopping Mall}, journal = {ASHRAE Transactions}, volume = {115}, year = {2009}, pages = {492-501}, abstract = {

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).

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\%.

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

}, author = {Lixia Wu and Mingsheng Liu and Xiufeng Pang and Gang Wang and Thomas G. Lewis} } @article {68, title = {Co-simulation of innovative integrated HVAC systems in buildings}, journal = {Journal of Building Performance Simulation}, volume = {2}, year = {2009}, pages = {209-230}, chapter = {209}, abstract = {

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.

}, keywords = {building performance simulation, co-simulation, hvac simulation, innovative building system modelling and simulation}, doi = {10.1080/19401490903051959}, url = {http://www.informaworld.com/smpp/section?content=a913244253\&fulltext=713240928}, author = {Marija Trcka and Jan Hensen and Michael Wetter} } @article {274, title = {Coupled simulations for naturally ventilated rooms between building simulation (BS) and computational fluid dynamics (CFD) for better prediction of indoor thermal environment}, journal = {Building and Environment}, volume = {44}, year = {2009}, month = {01/2009}, pages = {95-112}, author = {Liping Wang and Nyuk Hien Wong} } @article {1445, title = {Generic Optimization Program User Manual Version 3.0.0}, volume = {113}, number = {Part 1}, year = {2009}, pages = {380-391}, abstract = {

A software tool that automates the analysis of functional tests for air-handling units is described. The tool compares the performance observed during manual tests with the performance predicted by simple models of the components under test that are configured using design information and catalog data. Significant differences between observed and expected performance indicate the presence of faults. Fault diagnosis is performed by analyzing the variation of these differences with operating point using expert rules and fuzzy inferencing.

The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display compares the measured and expected performance, highlighting significant differences that indicate the presence of faults. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as by building owners and operators conducting routine tests to check the performance of their HVAC systems. The paper describes the input data requirements of the tool, the software structure, the graphical interface, and summarizes the development and testing process used.

}, author = {Michael Wetter} } @proceedings {60, title = {An implementation of co-simulation for performance prediction of innovative integrated HVAC systems in buildings}, year = {2009}, month = {07/2009}, pages = {724-731}, address = {Glasgow, Scotland}, abstract = {Integrated performance simulation of buildings and heating, ventilation and air-conditioning (HVAC)systems can help reducing energy consumption and increasing level of occupant comfort. However, no singe building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to accommodate the ever-increasing complexity and rapid innovations in building and system technologies. One way to alleviate this problem is to use co-simulation. The 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. This paper elaborates on issues important for co-simulation realization and discusses multiple possibilities to justify the particular approach implemented in a co-simulation prototype. The prototype is verified and validated against the results obtained from the traditional simulation approach. It is further used in a case study for the proof-of-concept, 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 frequency. The paper concludes by defining requirements and recommendations for generic co-simulation implementations.}, url = {http://www.ibpsa.org/proceedings/BS2009/BS09_0724_731.pdf}, author = {Marija Trcka and Michael Wetter and Jan Hensen} } @proceedings {57, title = {Modelica Library for Building Heating, Ventilation and Air-Conditioning Systems}, volume = {43}, year = {2009}, month = {09/2009}, edition = {44}, address = {Como, Italy}, abstract = {

The Buildings library is a freely available Modelica library that is based on Modelica.Fluid. It contains component models for building heating, ventilation and air conditioning systems. It also contains an interface that allows co-simulation with the Ptolemy software framework for concurrent, real-time, embedded systems developed by the University of California at Berkeley. The primary applications are controls design, energy analysis and model-based operation. The library has been used to model hydronic space heating systems, variable air volume flow systems and it has been linked to the EnergyPlus building energy simulation program for co-simulation using Ptolemy II. The library contains dynamic and steady-state component models that are applicable for analyzing fast transients when designing control algorithms and for conducting annual simulations when assessing energy performance. For most models, dimensional analysis is used to compute the performance for operating points that differ from nominal conditions. This allows parameterizing models in the absence of detailed geometrical information which is often impractical to obtain during the conceptual design phase of building systems.

}, doi = {10.3384/ecp0943}, url = {http://www.ep.liu.se/ecp_article/index.en.aspx?issue=043;article=44}, author = {Michael Wetter} } @conference {59, title = {A Modelica-based model library for building energy and control systems}, booktitle = {Proceedings of the 11th IBPSA Conference}, year = {2009}, month = {07/2009}, pages = {652-659}, address = {Glasgow, Scotland}, abstract = {

This paper describes an open-source library with component models for building energy and control systems that is based on Modelica, an equation-based object oriented language that is well positioned to become the standard for modeling of dynamic systems in various industrial sectors. The library is currently developed to support computational science and engineering for innovative building energy and control systems. Early applications will include controls design and analysis, rapid prototyping to support innovation of new building systems and the use of models during operation for controls, fault detection and diagnostics. This paper discusses the motivation for selecting an equation-based object-oriented language. It presents the architecture of the library and explains how base model scan be used to rapidly implement new models. To demonstrate the capability of analyzing novel energy and control systems, the paper closes with an example where we compare the dynamic performance of a conventional hydronic heating system with thermostatic radiator valves to an innovative heating system. In the new system, instead of a centralized circulation pump, each of the 18 radiators has a pump whose speed is controlled using a room temperature feedback loop, and the temperature of the boiler is controlled based on the speed of the radiator pump. All flows are computed by solving for the pressure distribution in the piping network, and the controls include continuous and discrete time controls.

}, keywords = {modelica}, url = {http://www.ibpsa.org/proceedings/BS2009/BS09_0652_659.pdf}, author = {Michael Wetter} } @article {69, title = {Modelica-based Modeling and Simulation to Support Research and Development in Building Energy and Control Systems}, journal = {Journal of Building Performance Simulation}, volume = {2}, year = {2009}, pages = {143-161}, abstract = {Traditional building simulation programs possess attributes that make them difficult to use for the design and analysis of building energy and control systems and for the support of model-based research and development of systems that may not already be implemented in these programs. This paper presents characteristic features of such applications, and it shows how equation-based object-oriented modeling can meet requirements that arise in such applications. Next, the implementation of an open-source component model library for building energy systems is presented. The library has been developed using the equation-based object-oriented Modelica modeling language. Technical challenges of modeling and simulating such systems are discussed. Research needs are presented to make this technology accessible to user groups that have more stringent requirements with respect to the numerical robustness of simulation than a research community may have. Two examples are presented in which models from the here described library were used. The first example describes the design of a controller for a nonlinear model of a heating coil using model reduction and frequency domain analysis. The second example describes the tuning of control parameters for a static pressure reset controller of a variable air volume flow system. The tuning has been done by solving a non-convex optimization problem that minimizes fan energy subject to state constraints.}, keywords = {modelica}, doi = {10.1080/19401490902818259}, url = {http://www.informaworld.com/smpp/section?content=a911401852\&fulltext=713240928}, author = {Michael Wetter} } @proceedings {58, title = {Standardization of thermo-fluid modeling in Modelica.Fluid 1.0}, volume = {43}, year = {2009}, month = {09/2009}, publisher = {Link{\"o}ping University Electronic Press}, edition = {13}, address = {Como, Italy}, abstract = {

This article discusses the Modelica.Fluid library that has been included in the Modelica Standard Library 3.1. Modelica.Fluid provides interfaces and basic components for the device-oriented modeling of one dimensional thermo-fluid flow in networks containing vessels; pipes; fluid machines; valves and fittings.

A unique feature of Modelica.Fluid is that the component equations and the media models as well as pressure loss and heat transfer correlations are decoupled from each other. All components are implemented such that they can be used for media from the Modelica.Media library. This means that an incompressible or compressible medium; a single or a multiple substance medium with one or more phases might be used with one and the same model as long as the modeling assumptions made hold. Furthermore;

trace substances are supported. Modeling assumptions can be configured globally in an outer System object. This covers in particular the initialization; uni- or bi-directional flow; and dynamic or steady-state formulation of mass; energy; and momentum balance. All assumptions can be locally refined for every component.

While Modelica.Fluid contains a reasonable set of component models; the goal of the library is not to provide a comprehensive set of models; but rather to provide interfaces and best practices for the treatment of issues such as connector design and implementation of energy; mass and momentum balances. Applications from various domains are presented.

}, keywords = {modelica}, isbn = {978-91-7393-513-5}, doi = {10.3384/ecp0943}, url = {http://www.ep.liu.se/ecp_article/index.en.aspx?issue=043;article=13}, author = {R{\"u}diger Franke and Francesco Casella and Martin Otter and Katrin Proelss and Michael Sielemann and Michael Wetter} } @article {421, title = {Technical Assistance to Beichuan Reconstruction: Creating and Designing Low- to Zero-carbon Communities in New Beichuan}, year = {2009}, month = {2009}, institution = {LBNL}, issn = {LBNL-2819E}, url = {http://www.escholarship.org/uc/item/0vv4m1gb}, author = {Tengfang T. Xu and Chuang Wang and Tianzhen Hong and Mark D. Levine} } @proceedings {263, title = {Benchmarking and Equipment and Controls Assessment for a {\textquoteleft}Big Box{\textquoteright} Retail Chain}, year = {2008}, month = {2008}, address = {Asilomar, California, USA}, abstract = {

The paper describes work to enable improved energy performance of existing and new retail stores belonging to a national chain and thereby also identify measures and tools that would improve the performance of {\textquoteleft}big box{\textquoteright} stores generally. A detailed energy simulation model of a standard store design was developed and used to:

The core enabling task of the project was to develop an energy model of the current standard design using the EnergyPlus simulation program. For the purpose of verification of the model against actual utility bills, the model was reconfigured to represent twelve existing stores (seven relatively new stores and five older stores) in different US climates and simulations were performed using weather data obtained from the National Weather Service. The results of this exercise, which showed generally good agreement between predicted and measured total energy use, suggest that dynamic benchmarking based on energy simulation would be an effective tool for identifying operational problems that affect whole building energy use. The models of the seven newer stores were then configured with manufacturers{\textquoteright} performance data for the equipment specified in the current design and used to assess the energy and cost benefits of increasing the efficiency of selected HVAC, lighting and envelope components. The greatest potential for cost-effective energy savings appears to be a substantial increase in the efficiency of the blowers in the roof top units and improvements in the efficiency of the lighting. The energy benefits of economizers on the roof-top units were analyzed and found to be very sensitive to the operation of the exhaust fans used to control building pressurization.

}, author = {Philip Haves and Brian E. Coffey and Scott Williams} } @article {413, title = {Comparing computer run time of building simulation programs}, journal = {Building Simulation}, volume = {1}, year = {2008}, month = {2008}, pages = {210-213}, abstract = {

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.

}, keywords = {computer run time, doe-2, energyplus, simulation program}, doi = {10.1007/s12273-008-8123-y}, author = {Tianzhen Hong and Walter F. Buhl and Philip Haves and Stephen E. Selkowitz and Michael Wetter} } @article {262, title = {Coupled simulations for naturally ventilated residential buildings}, journal = {Automation in Construction}, volume = {17}, year = {2008}, month = {05/2008}, pages = {386-398}, author = {Liping Wang and Nyuk Hien Wong} } @conference {3386, title = {A Modelica-Based Model Library for Building Energy and Control Systems}, booktitle = {Building Simulation {\textquoteright}09}, year = {2008}, month = {07/2008}, address = {Glasgow, Scotland}, author = {Michael Wetter} } @conference {61, title = {A Modular Building Controls Virtual Test Bed for the Integration of Heterogeneous Systems}, booktitle = {SimBuild 2008, July 30-August 1}, year = {2008}, month = {08/2008}, address = {Berkeley, CA}, abstract = {

This paper describes the Building Controls Virtual Test Bed (BCVTB) that is currently under development at Lawrence Berkeley National Laboratory. An earlier prototype linked EnergyPlus with controls hardware through embedded SPARK models and demonstrated its value in more cost-effective envelope design and improved controls sequences for the San Francisco Federal Building. The BCVTB presented here is a more modular design based on a middleware that we built using Ptolemy II, a modular 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. Our additions to Ptolemy II allow users to couple to Ptolemy II a prototype version of EnergyPlus, MATLAB/Simulink or other simulation programs for data exchange during run-time. In future work we will also implement a BACnet interface that allows coupling BACnet compliant building automation systems to Ptolemy II. We will present the architecture of the BCVTB and explain how users can add their own simulation programs to the BCVTB. We will then present an example application in which the building envelope and the HVAC system was simulated in EnergyPlus, the supervisory control logic was simulated in MATLAB/Simulink and Ptolemy II was used to exchange data during run-time and to provide real-time visualization as the simulation progresses.

}, author = {Michael Wetter and Philip Haves} } @conference {3388, title = {Using SPARK as a Solver for Modelica}, booktitle = {SimBuild 2008}, year = {2008}, month = {07/2008}, address = {Berkeley, CA, USA}, author = {Michael Wetter and Philip Haves and Michael A. Moshier and Edward F. Sowell} } @proceedings {62, title = {Using SPARK as a solver for Modelica}, year = {2008}, month = {08/2008}, address = {Berkeley, CA, USA}, abstract = {

Modelica is an object-oriented acausal modeling language that is well positioned to become a de-facto standard for expressing models of complex physical systems. To simulate a model expressed in Modelica, it needs to be translated into executable code. For generating run-time efficient code, such a translation needs to employ algebraic formula manipulations. As the SPARK solver has been shown to be competitive for generating such code but currently cannot be used with the Modelica language, we report in this paper how SPARK{\textquoteright}s symbolic and numerical algorithms can be implemented in OpenModelica, an open-source implementation of a Modelica modeling and simulation environment. We also report benchmark results that show that for our air flow network simulation benchmark, the SPARK solver is competitive with Dymola, which is believed to provide the best solver for Modelica.

}, url = {http://www.ibpsa.us/simbuild2008/technical_sessions/SB08-DOC-TS03-1-Wetter.pdf}, author = {Michael Wetter and Philip Haves and Michael A. Moshier and Edward F. Sowell} } @conference {3390, title = {Comparison of Co-Simulation Approaches for Building and HVAC/R System Simulation}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Marija Trcka and Michael Wetter and Jan Hensen} } @proceedings {63, title = {Comparison of co-simulation approaches for building and HVAC/R system simulation.
}, year = {2007}, month = {09/2007}, pages = {1418-1425}, address = {Beijing, China}, abstract = {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.}, url = {http://www.ibpsa.org/proceedings/BS2007/p503_final.pdf}, author = {Marija Trcka and Michael Wetter and Jan Hensen} } @conference {284, title = {A convenient coupled simulation method for thermal environment prediction in naturally ventilated buildings}, booktitle = {2nd PALENC conference and 28th AIVC conference, 27-29 September}, year = {2007}, month = {09/2007}, author = {Liping Wang and Nyuk Hien Wong} } @conference {283, title = {Discussion of strategies for UK zero energy building design}, booktitle = {2nd PALENC conference and 28th AIVC conference, 27-29 September}, year = {2007}, month = {09/2007}, author = {Liping Wang and Julie Gwilliam} } @article {3389, title = {Energy Performance of Underfloor Air Distribution Systems}, year = {2007}, institution = {California Energy Commission - Public Interest Energy Research Program}, author = {Fred S. Bauman and Thomas L. Webster and Hui Jin and Wolfgang Lukaschek and Corinne Benedek and Edward A. Arens and Paul F. Linden and Anna Lui and Walter F. Buhl and Darryl J. Dickerhoff} } @article {238, title = {Facade design optimization for naturally ventilated residential buildings in Singapore}, journal = {Energy and Buildings}, volume = {39}, year = {2007}, month = {08/2007}, pages = {954-961}, author = {Liping Wang and Nyuk Hien Wong and Shuo Li} } @conference {2663, title = {Global Efficiency of Direct Flow Vacuum Collectors in Autonomous Solar Desiccant Cooling: Simulation and Experimental Results}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Paul Bourdoukan and Etienne Wurtz and Maurice Sp{\'e}randio and Patrice Joubert} } @article {261, title = {The impacts of facade and ventilation strategies on indoor thermal environment for a naturally ventilated residential building in Singapore}, journal = {Building and Environment}, volume = {42}, year = {2007}, month = {12/2007}, pages = {4006-4015}, author = {Liping Wang and Nyuk Hien Wong} } @conference {254, title = {Integrated Static Pressure Reset with Fan Air Flow Station in Dual-duct VAV System Control}, booktitle = {ASME Energy Sustainability}, year = {2007}, month = {2007}, address = {Long Beach, CA}, author = {Lixia Wu and Mingsheng Liu and Gang Wang and Xiufeng Pang} } @article {275, title = {Investigation of the possibility of applying natural ventilation for thermal comfort in residential buildings in Singapore}, journal = {Architectural Science Review}, volume = {50}, year = {2007}, month = {2007}, pages = {190-199}, author = {Liping Wang and Nyuk Hien Wong} } @conference {2656, title = {Potential of Buried Pipes Systems and Derived Techniques for Passive Cooling of Buildings in Brazilian Climates}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Pierre Hollmuller and Joyce Carlo and Martin Ordenes and Fernando Westphal and Roberto Lamberts} } @proceedings {229, title = {Advanced modeling and simulation techniques in MOSILAB: A system development case study}, year = {2006}, pages = {pp.63-72}, author = {Christoph Nytsch-Geusen and Thilo Ernst and Peter Schwarz and Mathias Vetter and Andreas Holm and Juergen Leopold and Alexander Mattes and Andre Nordwig and Peter Schneider and Christoph Wittwer and Thierry Stephane Nouidui and Gerhardt Schmidt} } @proceedings {2813, title = {The Application of Building Energy Simulation and Calibration in Two High-Rise Commercial Buildings in Shanghai}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Yiqun Pan and Zhizhong Huang and Gang Wu and Chen Chen} } @proceedings {396, title = {Carbon Nanotube (CNT)-Centric Thermal Management of Future High Power Microprocessors}, year = {2006}, month = {03/2006}, address = {Atlanta, GA}, author = {Prajesh Bhattacharya and Wei, X. and Andrei G. Fedorov and Yogendra K. Joshi and Navdeep Bajwa and Anyuan Cao and Pulickel Ajayan} } @proceedings {2809, title = {A Case Study Demonstrating the Utility of Inter-Program Comparative Testing for Diagnosing Errors in Building Simulation Programs}, year = {2006}, month = {05/2006}, address = {Toronto, Canada}, author = {Andreas Weber and Ian Beausoleil-Morrison and Brent T. Griffith and Teemu Vesanen and S{\'e}bastien Lerson} } @article {378, title = {Characterization of the Temperature Oscillation Technique to Measure the Thermal Conductivity of Fluids}, journal = {International Journal of Heat and Mass Transfer}, volume = {49}, year = {2006}, month = {08/2006}, pages = {2950-2956}, chapter = {2950}, abstract = {

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{\textquoteright}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.

}, keywords = {Temperature oscillation technique, Thermal conductivity, thermal diffusivity}, url = {http://www.sciencedirect.com/science/article/pii/S001793100600144X}, author = {Prajesh Bhattacharya and S. Nara and P. Vijayan and Tang, T. and W. Lai and Patrick E. Phelan and Ravi S. Prasher and David W. Song and J. Wang} } @article {378, title = {Characterization of the Temperature Oscillation Technique to Measure the Thermal Conductivity of Fluids}, journal = {International Journal of Heat and Mass Transfer}, volume = {49}, year = {2006}, month = {08/2006}, pages = {2950-2956}, chapter = {2950}, abstract = {

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{\textquoteright}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.

}, keywords = {Temperature oscillation technique, Thermal conductivity, thermal diffusivity}, url = {http://www.sciencedirect.com/science/article/pii/S001793100600144X}, author = {Prajesh Bhattacharya and S. Nara and P. Vijayan and Tang, T. and W. Lai and Patrick E. Phelan and Ravi S. Prasher and David W. Song and J. Wang} } @conference {290, title = {Coupling between the CFD simulation and building simulation for better prediction of natural ventilation}, booktitle = {the 2nd International conference on sustainable architecture and urban design in tropical regions, Jogjakarta}, year = {2006}, month = {04/2006}, author = {Liping Wang and Nyuk Hien Wong} } @conference {291, title = {A coupling method to increase the accuracy of natural ventilation prediction in thermal simulation program}, booktitle = {the 2nd International conference on sustainable architecture and urban design in tropical regions, Jogjakarta}, year = {2006}, month = {04/2006}, author = {Liping Wang and Nyuk Hien Wong} } @proceedings {3392, title = {Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Case Study in New York}, year = {2006}, month = {08/2006}, address = {Pacific Grove, CA, USA}, author = {Sila Kiliccote and Mary Ann Piette and David S. Watson and Glenn D. Hughes} } @proceedings {2804, title = {Experience Testing EnergyPlus With the IEA HVAC Bestest E300-E545 Series and IEA HVAC Bestest Fuel-Fired Furnace Series}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Michael J. Witte and Robert H. Henninger and Drury B. Crawley} } @conference {286, title = {The impacts of facade designs: orientations, window to wall ratios and shading devices on indoor environment for naturally ventilated residential buildings in Singapore}, booktitle = {the 23st International conference on Passive and Low energy architecture, Geneva}, year = {2006}, month = {09/2006}, author = {Liping Wang and Nyuk Hien Wong} } @proceedings {47, title = {Modelica versus TRNSYS {\textemdash} A Comparison Between an Equation-Based and a Procedural Modeling Language for Building Energy Simulation}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, abstract = {

The EnergyPlus building energy simulation software has been tested using the IEA HVAC BESTEST E300-E545 series of tests and the IEA HVAC BESTEST Fuel-Fired test series. The first is a series of comparative tests for a single-zone DX cooling system which tests a program{\textquoteright}s ability to model hourly loads over an expanded range of performance conditions for various air mixing, infiltration, thermostat set-up, overload conditions, and various economizer control schemes. The second is a series of analytical/semianalytical comparative tests for a single-zone fuel-fired furnace which tests a program{\textquoteright}s ability to model steady state performance, varying outdoor and indoor conditions, and circulating and draft fan operation. Each of these HVAC BESTEST series were used to test EnergyPlus prior to new public releases. The application of these tests proved to be very useful in several ways: a) revealed algorithmic errors which were fixed, b) revealed algorithmic shortcomings which were improved or eliminated through the use of more rigorous calculations for certain components, and c) caught newly introduced bugs before public release of updates.

}, url = {http://www.ibpsa.us/pub/simbuild2006/papers/SB06_001_008.pdf}, author = {Michael Wetter and Christoph Haugstetter} } @conference {230, title = {MOSILAB: Ein Modelica-Simulationswerkzeug zur energetischen Geb{\"a}ude- und Anlagensimulation}, booktitle = {16. Symposium Thermische Solarenergie}, year = {2006}, address = {Bad Staffelstein, Germany}, isbn = {3-934681-45-X}, author = {Christoph Nytsch-Geusen and Andre Nordwig and Mathias Vetter and Christoph Wittwer and Thierry Stephane Nouidui and Peter Schneider} } @proceedings {64, title = {Multizone Airflow Model in Modelica}, year = {2006}, month = {09/2006}, pages = {431-440}, address = {Vienna, Austria}, abstract = {

We present the implementation of a library of multi-zone airflow models in Modelica and a comparative model validation with CONTAM. Our models have a similar level of detail as the models in CONTAM and COMIS. The multizone airflow models allow modeling the flow between rooms through doors, staircases or construction cracks. The flow can be caused by buoyancy effects, such as stack effects in high rise buildings or air temperature imbalance between adjoining rooms, by flow imbalance of a ventilation system, or by wind pressure on the building envelope. The here presented library can be used with a Modelica library for thermal building and HVAC system simulation to compute interzonal air flow rates. The combined use facilitates the integrated design of building systems, which is typically required for analyzing the interaction of room control loops in variable air volume flow systems through open doors, the flow in naturally ventilated buildings and the pressure in elevator shafts caused by stacked effects.

}, keywords = {contaminant transport, multizone airflow}, url = {https://www.modelica.org/events/modelica2006/Proceedings/sessions/Session413.pdf}, author = {Michael Wetter} } @proceedings {56, title = {Multizone Building Model for Thermal Building Simulation in Modelica}, year = {2006}, month = {9/2006}, pages = {517-526}, address = {Vienna, Austria}, abstract = {We present a room model for thermal building simu- lation that we implemented in Modelica. The room model can be used for controls analysis and energy analysis of one or several rooms that are connected through airflow or heat conduction. The room model can assess energy storage in the air and in the build- ing construction materials, heat transfer between the room and the outside environment and the humidity and CO2 release to the room air. The humidity storage in the building construction materials is not modeled. We also describe a novel separation of heat transfer mechanisms on which our room model is built on. The separation allowed a significant reduction in model de- velopment time, and it allows using state-of-the-art programs for computing prior to the thermal building simulation certain energy flows, such as solar heat gain of an active facade without breaking feedback loops between the HVAC system and the room.}, url = {https://www.modelica.org/events/modelica2006/Proceedings/sessions/Session5b4.pdf}, author = {Michael Wetter} } @conference {287, title = {Natural ventilation simulation by using coupling building simulation and CFD simulation program for accurate prediction of indoor thermal environment}, booktitle = {the 23st International conference on Passive and Low energy architecture , Geneva}, year = {2006}, month = {09/2006}, author = {Liping Wang and Nyuk Hien Wong} } @conference {289, title = {A numerical study of Trombe wall for enhancing stack ventilation in buildings}, booktitle = {The 23rd International Conference on Passive and Low Energy Architecture, Geneva}, year = {2006}, month = {09/2006}, author = {Liping Wang and Angui Li} } @article {71, title = {Precision control for generalized pattern search algorithms with adaptive precision function evaluations}, journal = {SIAM Journal on Optimization}, volume = {16}, year = {2006}, pages = {650-669
}, abstract = {

In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evaluated exactly. However, there is a large class of engineering problems where the numerical evaluation of the cost function involves the solution of systems of differential algebraic equations. Since the termination criteria of the numerical solvers often depend on the design parameters, computer code for solving these systems usually defines a numerical approximation to the cost function that is discontinuous with respect to the design parameters. Standard generalized pattern search algorithms have been applied heuristically to such problems, but no convergence properties have been stated. In this paper we extend a class of generalized pattern search algorithms to include a subprocedure that adaptively controls the precision of the approximating cost functions. The numerical approximations to the cost function need not define a continuous function. Our algorithms can be used for solving linearly constrained problems with cost functions that are at least locally Lipschitz continuous. Assuming that the cost function is smooth, we prove that our algorithms converge to a stationary point. Under the weaker assumption that the cost function is only locally Lipschitz continuous, we show that our algorithms converge to points at which the Clarke generalized directional derivatives are nonnegative in predefined directions. An important feature of our adaptive precision scheme is the use of coarse approximations in the early iterations, with the approximation precision controlled by a test. We show by numerical experiments that such an approach leads to substantial time savings in minimizing computationally expensive functions.

}, issn = {1052-6234}, doi = {10.1137/040605527}, author = {Elijah Polak and Michael Wetter} } @article {73, title = {Building design optimization using a convergent pattern search algorithm with adaptive precision simulations}, journal = {Energy and Buildings}, volume = {37}, year = {2005}, pages = {603-612}, abstract = {

We propose a simulation{\textendash}precision control algorithm that can be used with a family of derivative free optimization algorithms to solve optimization problems in which the cost function is defined through the solutions of a coupled system of differential algebraic equations (DAEs). Our optimization algorithms use coarse precision approximations to the solutions of the DAE system in the early iterations and progressively increase the precision as the optimization approaches a solution. Such schemes often yield a significant reduction in computation time. We assume that the cost function is smooth but that it can only be approximated numerically by approximating cost functions that are discontinuous in the design parameters. We show that this situation is typical for many building energy optimization problems.We present a new building energy and daylighting simulation program, which constructs approximations to the cost function that converge uniformly on bounded sets to a smooth function as precision is increased.We prove that for our simulation program, our optimization algorithms construct sequences of iterates with stationary accumulation points. We present numerical experiments in which we minimize the annual energy consumption of an office building for lighting, cooling and heating. In these examples, our precision control algorithm reduces the computation time up to a factor of four.

}, doi = {10.1016/j.enbuild.2004.09.005}, author = {Michael Wetter and Elijah Polak} } @article {72, title = {BuildOpt - A new building energy simulation program that is built on smooth models}, journal = {Building and Environment}, volume = {40}, year = {2005}, pages = {1085-1092}, chapter = {1085}, abstract = {

Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has a unique once continuously differentiable solution. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with Generalized Pattern Search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today{\textquoteright}s building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt{\textquoteright}s approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.

}, doi = {10.1016/j.buildenv.2004.10.003}, author = {Michael Wetter} } @conference {388, title = {Effect of Particle Material on the Static Thermal Conductivity of Nanofluids}, booktitle = {Heat Transfer Conference}, year = {2005}, month = {07/2005}, address = {San Francisco, CA}, author = {P. Vijayan and Prajesh Bhattacharya and S. Nara and W. Lai and Patrick E. Phelan and Ravi S. Prasher and David W. Song and J. Wang} } @article {277, title = {Effects of double glazed fa{\c c}ade on energy consumption, thermal comfort and condensation for a typical office building in Singapore}, journal = {Energy and Buildings}, volume = {37}, year = {2005}, month = {06/2005}, author = {Nyuk Hien Wong and Liping Wang and Aida Noplie Chandra and Anupama Rana Pandey and Xiaolin Wei} } @conference {385, title = {Experimental Determination of the Effect of Varying Base Fluid and Temperature on the Static Thermal Conductivity of Nanofluids}, booktitle = {ASME International Mechanical Engineering Congress and Exposition, November 5-11, 2005}, year = {2005}, month = {11/2005}, publisher = {ASME}, organization = {ASME}, address = {Orlando, FL}, abstract = {

The heat transfer abilities of fluids can be improved by adding small particles of sizes of the order of nanometers. Recently a lot of research has been done in evaluating the thermal conductivity of nanofluids using various nanoparticles. In our present work we address this issue by conducting a series of experiments to determine the effective thermal conductivity of alumina-nanofluids by varying the base fluid with water and antifreeze liquids like ethylene glycol and propylene glycol. Temperature oscillation method is used to find the thermal conductivity of the nanofluid. The results show the thermal conductivity enhancement of nanofluids depends on viscosity of the base fluid. Finally the results are validated with a recently proposed theoretical model.

}, isbn = {0-7918-4221-5}, doi = {10.1115/IMECE2005-81494}, author = {S. Nara and Prajesh Bhattacharya and P. Vijayan and W. Lai and W. Rosenthal and Patrick E. Phelan and Ravi S. Prasher and David W. Song and Jinlin Wang} } @conference {292, title = {The impacts of facade and ventilation strategies on indoor thermal environment for a naturally ventilated residential building in Singapore}, booktitle = {the 10th International conference on Indoor Air Quality and Climate, Beijing}, year = {2005}, month = {2005}, author = {Liping Wang and Nyuk Hien Wong} } @proceedings {232, title = {MOSILAB: Development of a modelica based generic simulation tool supporting modal structural dynamics}, year = {2005}, pages = {pp.527-534}, address = {Hamburg, Germany}, author = {Christoph Nytsch-Geusen and Thilo Ernst and Peter Schneider and Mathias Vetter and Andreas Holm and Juergen Leopold and Ullrich Doll and Andre Nordwig and Peter Schwarz and Christoph Wittwer and Thierry Stephane Nouidui and Gerhardt Schmidt and Alexander Mattes} } @conference {2668, title = {Parametric Analysis of a Solar Desiccant Cooling System using the SimSPARK Environment}, booktitle = {IBPSA Building Simulation 2005}, year = {2005}, month = {08/2005}, address = {Montreal, Canada}, author = {Etienne Wurtz and Chadi Maalouf and Laurent Mora and Francis Allard} } @conference {295, title = {Thermal analysis of climate environments based on weather data in Singapore for naturally ventilated buildings}, booktitle = {the 10th International conference on Indoor Air Quality and Climate,Beijing}, year = {2005}, month = {2005}, author = {Liping Wang and Nyuk Hien Wong} } @article {3398, title = {Building Design Optimization Using a Convergent Pattern Search Algorithm with Adaptive Precision Simulations}, journal = {Energy and Buildings}, volume = {37}, year = {2004}, month = {09/2004}, pages = {603-612}, chapter = {603}, author = {Michael Wetter and Elijah Polak} } @article {52, title = {BuildOpt 1.0.1 validation}, year = {2004}, issn = {LBNL-54658}, author = {Michael Wetter and Elijah Polak and Van P. Carey} } @article {51, title = {BuildOpt - A new building energy simulation program that is built on smooth models}, journal = {Building and Environment}, volume = {40}, year = {2004}, month = {08/2005}, chapter = {1085-1092}, abstract = {

Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has unique solution that is once continuously differentiable in the building design parameters. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with generalized pattern search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today{\textquoteright}s building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt{\textquoteright}s approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.

}, doi = {10.1016/j.buildenv.2004.10.003}, author = {Michael Wetter} } @article {65, title = {A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization
}, journal = {Building and Environment}, volume = {39}, year = {2004}, month = {08/2004}, pages = {989-999}, chapter = {989}, abstract = {

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.

}, keywords = {coordinate search, direct search, genetic algorithm, hooke{\textendash}jeeves, optimization, particle swarm optimization}, doi = {10.1016/j.buildenv.2004.01.022}, author = {Michael Wetter and Jonathan A. Wright} } @article {74, title = {A convergent optimization method using pattern search algorithms with adaptive precision simulation}, journal = {Building Services Engineering Research and Technology}, volume = {25}, year = {2004}, month = {11/2004}, pages = {327-338}, abstract = {

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{\textendash}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.

}, doi = {10.1191/0143624404bt097oa }, author = {Michael Wetter and Elijah Polak} } @proceedings {2823, title = {EnergyPlus: An Update}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Drury B. Crawley and Linda K. Lawrie and Curtis O. Pedersen and Frederick C. Winkelmann and Michael J. Witte and Richard K. Strand and Richard J. Liesen and Walter F. Buhl and Yu Joe Huang and Robert H. Henninger and Jason Glazer and Daniel E. Fisher and Don B. Shirley and Brent T. Griffith and Peter G. Ellis and Lixing Gu} } @conference {390, title = {Evaluation of the Temperature Oscillation Technique to Calculate Thermal Conductivity of Water and Systematic Measurement of the Thermal Conductivity of Aluminum Oxide {\textendash} Water Nanofluiids}, booktitle = {International Mechanical Engineering Congress \& Exposition,}, year = {2004}, month = {11/2004}, address = {Anaheim, CA}, author = {Prajesh Bhattacharya and P. Vijayan and Tang, T. and S. Nara and Patrick E. Phelan and Ravi S. Prasher and J. Wang and David W. Song} } @proceedings {2832, title = {Experience Testing EnergyPlus With the ASHRAE 1052-RP Building Fabric Analytical Tests}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Michael J. Witte and Robert H. Henninger and Drury B. Crawley} } @article {53, title = {GenOpt 2.0.0 - Generic optimization program}, year = {2004}, abstract = {

GenOpt is an optimization program for the minimization of a cost function that is evaluated by an external simulation program. It has been developed for optimization problems where the cost function is computationally expensive and its derivatives are not available or may not even exist. GenOpt can be coupled to any simulation program that reads its input from text files and writes its output to text files. The independent variables can be continuous variables (possibly with lower and upper bounds), discrete variables, or both, continuous and discrete variables. Constraints on dependent variables can be implemented using penalty or barrier functions.

GenOpt has a library with local and global multi-dimensional and one-dimensional optimization algorithms, and algorithms for doing parametric runs. An algorithm interface allows adding new minimization algorithms without knowing the details of the program structure.

GenOpt is written in Java so that it is platform independent. The platform independence and the general interface make GenOpt applicable to a wide range of optimization problems.

GenOpt has not been designed for linear programming problems, quadratic programming problems, and problems where the gradient of the cost function is available. For such problems, as well as for other problems, special tailored software exists that is more efficient.

}, issn = {LBNL-54199}, author = {Michael Wetter} } @article {278, title = {Heat transfer and natural ventilation from single-sided heated solar chimney for buildings}, journal = {Journal of Asian Architecture and Building Engineering}, volume = {3}, year = {2004}, author = {Angui Li and Phillip Jones and Pingge Zhao and Liping Wang} } @conference {296, title = {A numerical study of vertical solar chimney for Enhancing stack ventilation in buildings}, booktitle = {The 21st International Conference on Passive and Low Energy Architecture, The Netherlands}, year = {2004}, month = {09/2004}, author = {Liping Wang and Angui Li} } @proceedings {2833, title = {Resources for Teaching Building Energy Simulation}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Richard K. Strand and Richard J. Liesen and Michael J. Witte} } @mastersthesis {3397, title = {Simulation-Based Building Energy Optimization}, volume = {Ph.D.}, year = {2004}, school = {University of California, Berkeley}, type = {Dissertation}, address = {Berkeley, CA, USA}, author = {Michael Wetter} } @booklet {66, title = {Simulation-based building energy optimization}, year = {2004}, type = {Dissertation}, abstract = {

This dissertation presents computational techniques for simulation-based design optimization of buildings and heating, ventilation, air-conditioning and lighting systems in which the cost function is smooth. In such problems, the evaluation of the cost function involves the numerical solution of systems of differential algebraic equations (DAE). Since the termination criteria of the iterative solvers often depend on the design parameters, a computer code for solving such systems usually defines a numerical approximation to the cost function that is discontinuous in the design parameters. The discontinuities can be large in cost functions that are evaluated by commercial building energy simulation programs, and optimization algorithms that require smoothness frequently fail if used with such programs. Furthermore, controlling the numerical approximation error is often not possible with commercial building energy simulation programs.

In this dissertation, we present BuildOpt, a new detailed thermal building and daylighting simulation program. BuildOpt{\textquoteright}s simulation models dene a DAE system that is smooth in the state variables, in time and in the design parameters. This allows proving that the DAE system has a unique solution that is smooth in the design parameters, and it is required to compute high precision approximating cost functions that converge to a cost function that is smooth in the design parameters as the DAE solver tolerance is tightened.

For simulation programs that allow such a precision control, we constructed subprocedures for Generalized Pattern Search (GPS) optimization algorithms that adaptively control the precision of the cost function evaluations: coarse precision for the early iterations,with precision progressively increasing as a stationary point is approached. This scheme significantly reduces the computation time, and it allows to prove that the sequence of iterates contains stationary accumulation points. For optimization problems in which commercial building energy simulation programs are used to evaluate the cost function, we compared by numerical experiment several deterministic and probabilistic optimization algorithms.

}, keywords = {dissertation}, author = {Michael Wetter} } @proceedings {49, title = {Comparison of a generalized pattern search and a genetic algorithm optimization method}, volume = {III}, year = {2003}, pages = {1401-1408}, address = {Eindhoven, Netherlands}, abstract = {

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

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

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

}, url = {http://www.ibpsa.org/proceedings/BS2003/BS03_1401_1408.pdf}, author = {Michael Wetter and Jonathan A. Wright}, editor = {Godfried Augenbroe and Jan Hensen} } @proceedings {48, title = {A convergent optimization method using pattern search algorithms with adaptive precision simulation}, volume = {III}, year = {2003}, pages = {1393-1400}, address = {Eindhoven, Netherlands}, abstract = {

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.

}, keywords = {coordinate search, direct search, genetic algorithm, hooke{\textendash}jeeves, optimization, particle swarm optimization}, author = {Michael Wetter and Elijah Polak}, editor = {Godfried Augenbroe and Jan Hensen} } @article {288, title = {Field Testing Model-Based Condition Monitoring on a HVAC Cooling Coil Sub-System}, journal = {Building Services Engineering Research \& Technology}, volume = {24}, year = {2003}, pages = {103-116}, author = {Richard A. Buswell and Philip Haves and Jonathan A. Wright} } @proceedings {298, title = {Non-Linear Recursive Parameter Estimation Applied to Fault Detection and Diagnosis in Real Buildings}, year = {2002}, month = {12/2002}, address = {Li{\`e}ge, Belgium}, author = {Richard A. Buswell and Philip Haves and Tim I. Salsbury and Jonathan A. Wright} } @proceedings {50, title = {GenOpt - A Generic Optimization Program}, volume = {I}, year = {2001}, pages = {601-608}, address = {Rio de Janeiro}, abstract = {

The potential offered by computer simulation is often not realized: Due to the interaction of system variables, simulation users rarely know how to choose input parameter settings that lead to optimal performance of a given system. Thus, a program called GenOpt{\textregistered} that automatically determines optimal parameter settings has been developed.

GenOpt is a generic optimization program. It minimizes an objective function with respect to multiple parameters. The objective function is evaluated by a simulation program that is iteratively called by GenOpt. In thermal building simulation {\textemdash} which is the main target of GenOpt {\textemdash} the simulation program usually has text-based I/O. The paper shows how GenOpt{\textquoteright}s simulation program interface allows the coupling of any simulation program with text based I/O by simply editing a configuration file, avoiding code modification of the simulation program. By using object-oriented programming, a high-level interface for adding minimization algorithms to GenOpt{\textquoteright}s library has been developed. We show how the algorithm interface separates the minimization algorithms and GenOpt{\textquoteright}s kernel, which allows implementing additional algorithms without being familiar with the kernel or having to recompile it. The algorithms can access utility classes that are commonly used for minimization, such as optimality check, line-search, etc.

GenOpt has successfully solved various optimization problems in thermal building simulation. We show an example of minimizing source energy consumption of an office building using EnergyPlus, and of minimizing auxiliary electric energy of a solar domestic hot water system using TRNSYS. For both examples, the time required to set up the optimization was less than one hour, and the energy savings are about 15\%, together with better daylighting usage or lower investment costs, respectively.

}, url = {http://www.ibpsa.org/proceedings/BS2001/BS01_0601_608.pdf}, author = {Michael Wetter}, editor = {Roberto Lamberts and Cezar O. R. Negr{\~a}o and Jan Hensen} } @article {324, title = {Condition Monitoring in HVAC Subsystems using First Principles Models}, journal = {ASHRAE Transactions}, volume = {102}, year = {1996}, author = {Philip Haves and Tim I. Salsbury and Jonathan A. Wright} } @proceedings {327, title = {A Fault Detection and Diagnosis Method Based on First Principles Models and Expert Rules}, year = {1995}, month = {09/1995}, address = {Bejing, China}, author = {Tim I. Salsbury and Philip Haves and Jonathan A. Wright} } @article {335, title = {Design, Construction and Commissioning of Building Emulators for EMCS Applications}, journal = {ASHRAE Transactions}, volume = {100}, year = {1994}, author = {Shengwei Wang and Philip Haves and Pierre Nusgens} } @article {334, title = {Investigation of the Reliability of Building Emulators for Testing Energy Management and Control Systems}, journal = {ASHRAE Transactions}, volume = {100}, year = {1994}, author = {Henk C. Peitsman and Shengwei Wang and Philip Haves and Satu H. K{\"a}rki and Cheol P. Park} } @proceedings {331, title = {Model-Based Approaches to Fault Detection and Diagnosis in Air-Conditioning System}, year = {1994}, month = {12/1994}, address = {Li{\`e}ge, Belgium}, author = {Mourad Benouarets and Arthur L. Dexter and Richard S. Fargus and Philip Haves and Tim I. Salsbury and Jonathan A. Wright} } @proceedings {341, title = {Use of Building Emulators to Evaluate the Performance of Building Energy Management Systems}, year = {1991}, month = {08/1991}, pages = {209-213}, address = {Nice, France}, abstract = {

Three complementary approaches may be used in the evaluation of the performance of building control systems-simulation, emulation and field testing. In emulation a real-time simulation of the building and HVAC plant is connected to a real building energy management system (BEMS) via a hardware interface. Emulation has the advantage of allowing controlled, repeatable experiments whilst testing real devices that may contain proprietary algorithms. Building emulators have been developed by the authors in the context of lEA Annex 17, which is concerned with the use of simulation to evaluate the performance of BEMS. The paper discusses different approaches to the design of building emulators and describes the different architectures, hardware and software used by the authors. The problem of evaluating the overall performance of BEMS is discussed and results are presented that illustrate the use of emulators to investigate the influence of the tuning of local loop controls on building performance.

}, author = {Hossein Vaezi-Nejad and E. Hutter and Philip Haves and Arthur L. Dexter and George E. Kelly and Pierre Nusgens and Shengwei Wang} } @conference {55643, title = {Thermal Energy Storage System Sizing}, booktitle = {IBPSA Building Simulation {\textquoteright}89}, year = {1989}, month = {01/1989}, address = {Vancouver, BC, Canada}, url = {http://www.ibpsa.org/proceedings/BS1989/BS89_357_362.pdf}, author = {Dominique Dumortier and Ron C. Kammerud and Birdsall, Bruce E. and Brandt Andersson and Joseph H. Eto and William L. Carroll and Frederick C. Winkelmann} } @conference {55797, title = {The DOE-2 Computer Program for Thermal Simulation of Buildings}, booktitle = {American Institute of Physics (AIP)}, volume = {135}, number = {642}, year = {1985}, month = {01/1985}, publisher = {American Institute of Physics}, organization = {American Institute of Physics}, doi = {10.1063/1.35478}, author = {Birdsall, Bruce E. and Walter F. Buhl and Richard B. Curtis and Ender Erdem and Joseph Eto and James J. Hirsch and Karen H. Olson and Frederick C. Winkelmann} } @proceedings {55943, title = {New Features of the DOE-2.1c Energy Analysis Program}, year = {1985}, month = {01/1985}, publisher = {International Building Performance Simulation Association}, url = {http://www.ibpsa.org/proceedings/BS1985/BS85_195_200.pdf}, author = {Walter F. Buhl and Ender Erdem and Joseph H. Eto and James J. Hirsch and Frederick C. Winkelmann} } @conference {55945, title = {The DOE-2 Building Energy Analysis Program}, booktitle = {ASEAN Conference on Energy Conservation in Buildings}, year = {1984}, month = {05/1984}, address = {Singapore}, author = {Richard B. Curtis and Birdsall, Bruce E. and Walter F. Buhl and Ender Erdem and Joseph H. Eto and James J. Hirsch and Karen H. Olson and Frederick C. Winkelmann} } @article {376, title = {The Radio Polarization of Quasars}, journal = {Monthly Notices of the Royal Astronomical Society}, volume = {168}, year = {1974}, month = {07/1974}, pages = {137-162}, chapter = {137}, abstract = {

Observations over a wide range of wavelengths, 2.2 <= λ <= 73 cm, have been combined to define the wavelength variation of the degree of linear polarization m(λ) for 120 quasars with known redshift. For the majority, m(λ) decreases monotonically with increasing wavelength but for 35 sources the polarization curve is inverted at short wavelengths. A classification is given, based on both the polarization curve and the radio spectrum, and the results are interpreted in terms of the presence or absence of opaque components in the source. The depolarization which occurs at long wavelengths is accounted for by a combination of spectral effects and Faraday depolarization. For 46 steep-spectrum sources the depolarization curve appears to be dominated by the Faraday effect, and has been used to deduce the electron density within the radiating components. In this group of sources the correlation between depolarization and redshift noted by Kronberg et al. is confirmed and strengthened. A discussion is given of some theoretical models of radio sources in the light of the depolarization data.

}, author = {Robin G. Conway and Philip Haves and Philipp P. Kronberg and David Stannard and Jacques P. Vall{\'e}e and John F. C. Wardle} }