@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 {32166, title = {Ten questions on urban building energy modeling}, journal = {Building and Environment}, volume = {168}, year = {2020}, month = {Jan-01-2020}, pages = {106508}, abstract = {

Buildings in cities consume up to 70\% of all primary energy. To achieve cities{\textquoteright} energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the urban scale to provide quantitative insights for stakeholders and inform their decision making on urban energy planning, as well as building energy retrofits at scale, to achieve efficiency, sustainability, and resilience of urban buildings.
Designing and operating urban buildings as a group (from a city block to a district to an entire city) rather than as single individuals requires simulation and optimization to account for interactions among buildings and between buildings and their surrounding urban environment, and for district energy systems serving multiple buildings with diverse thermal loads across space and time. When hundreds or more buildings are involved in typical urban building energy modeling (UBEM) to estimate annual energy demand, evaluate design or retrofit options, and quantify impacts of extreme weather events or climate change, it is crucial to integrate urban datasets and UBEM tools in a seamless automatic workflow with cloud or high-performance computing for users including urban planners, designers and researchers.
This paper presents ten questions that highlight significant UBEM research and applications. The proposed answers aim to stimulate discussion and provide insights into the current and future research on UBEM, and more importantly, to inspire new and important questions from young researchers in the field.

}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.106508}, author = {Tianzhen Hong and Chen, Yixing and Luo, Xuan and Luo, Na and Lee, Sang Hoon} } @article {31987, title = {Assessing the Potential to Reduce U.S. Building CO2 Emissions 80\% by 2050}, journal = {Joule}, year = {2019}, month = {08/2019}, abstract = {

Buildings are responsible for 36\% of CO2 emissions in the United States and will thus be integral to climate change mitigation; yet, no studies have comprehensively assessed the potential long-term CO2 emissions reductions from the U.S. buildings sector against national goals in a way that can be regularly updated in the future. We use Scout, a reproducible and granular model of U.S. building energy use, to investigate the potential for the U.S. buildings sector to reduce CO2 emissions 80\% by 2050, consistent with the U.S. Mid-Century Strategy. We find that a combination of aggressive efficiency measures, electrification, and high renewable energy penetration can reduce CO2 emissions by 72\%{\textendash}78\% relative to 2005 levels, just short of the target. Results are sufficiently disaggregated by technology and end use to inform targeted building energy policy approaches and establish a foundation for continual reassessment of technology development pathways that drive significant long-term emissions reductions.

}, keywords = {Building energy efficiency, decarbonization, electrification, emissions, energy models, energy policy analysis, national climate goals, pathways building stock}, doi = {10.1016/j.joule.2019.07.013}, author = {Jared Langevin and Chioke B. Harris and Janet L. Reyna} } @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 {31312, title = {Development of city buildings dataset for urban building energy modeling}, journal = {Energy and Buildings}, volume = {183}, year = {2019}, month = {11/2018}, pages = {252 - 265}, abstract = {

Urban building energy modeling (UBEM) is becoming a proven tool to support energy efficiency programs for buildings in cities. Development of a city-scale dataset of the existing building stock is a critical step of UBEM to automatically generate energy models of urban buildings and simulate their performance. This study introduces data needs, data standards, and data sources to develop city building datasets for UBEM. First, a literature review of data needs for UBEM was conducted. Then, the capabilities of the current data standards for city building datasets were reviewed. Moreover, the existing public data sources from several pioneer cites were studied to evaluate whether they are adequate to support UBEM. The results show that most cities have adequate public data to support UBEM; however, the data are represented in different formats without standardization, and there is a lack of common keys to make the data mapping easier. Finally, a case study is presented to integrate the diverse data sources from multiple city departments of San Francisco. The data mapping process is introduced and discussed. It is recommended to use the unique building identifiers as the common keys in the data sources to simplify the data mapping process. The integration methods and workflow are applied to other U.S. cities for developing the city-scale datasets of their existing building stock, including San Jose, Los Angeles, and Boston.

}, keywords = {City building dataset, CityGML, Data mapping, Data standards, Urban Building Energy Modeling}, issn = {03787788}, doi = {10.1016/j.enbuild.2018.11.008}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0378778818316852https://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/plain}, author = {Yixing Chen and Tianzhen Hong and Xuan Luo and Barry Hooper} } @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 {31668, title = {Integrating physics-based models with sensor data: An inverse modeling approach}, journal = {Building and Environment}, volume = {154}, year = {2019}, month = {05/2019}, pages = {23 - 31}, abstract = {

Physics-based building energy models (e.g., EnergyPlus) rely on some unknown input parameters (e.g., zone air infiltration) that are hard to measure, leading to uncertainty in simulation results especially for existing buildings with varying operating conditions. With the increasing deployment of smart thermostats, zone air temperature data are readily available, posing a new opportunity for building energy modeling if such data can be harnessed. This study presents a novel inverse modeling approach which inverses the zone air heat balance equation and uses the measured zone air temperature to analytically calculate the zone air infiltration rate and zone internal thermal mass (e.g., furniture, interior partitions), which are two important model parameters with great variability and difficult to measure. This paper introduces the technical concept and algorithms of the inverse models, their implementation in EnergyPlus, and verification using EnergyPlus simulated building performance data. The inverse modeling approach provides new opportunities for integrating data from massive IoT sensors and devices to enhance the accuracy of simulation results which are used to inform decision making on energy retrofits and efficiency improvements of existing buildings.

}, keywords = {building performance simulation, energyplus, infiltration, internal thermal mass, inverse model, sensor data}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.03.006}, url = {https://linkinghub.elsevier.com/retrieve/pii/S036013231930160X}, author = {Tianzhen Hong and Sang Hoon Lee} } @article {32156, title = {An inverse approach to solving zone air infiltration rate and people count using indoor environmental sensor data}, journal = {Energy and Buildings}, volume = {198}, year = {2019}, month = {Jan-09-2019}, pages = {228 - 242}, abstract = {

Physics-based simulation of energy use in buildings is widely used in building design and performance rating, controls design and operations. However, various challenges exist in the modeling process. Model parameters such as people count and air infiltration rate are usually highly uncertain, yet they have significant impacts on the simulation accuracy. With the increasing availability and affordability of sensors and meters in buildings, a large amount of measured data has been collected including indoor environmental parameters, such as room air dry-bulb temperature, humidity ratio, and CO2 concentration levels. Fusing these sensor data with traditional energy modeling poses new opportunities to improve simulation accuracy. This study develops a set of physics-based inverse algorithms which can solve the highly uncertain and hard-to-measure building parameters such as zone-level people count and air infiltration rate. A simulation-based case study is conducted to verify the inverse algorithms implemented in EnergyPlus covering various sensor measurement scenarios and different modeling use cases. The developed inverse models can solve the zone people count and air infiltration at sub-hourly resolution using the measured zone air temperature, humidity and/or CO2 concentration given other easy-to-measure model parameters are known.

}, keywords = {energyplus, infiltration, Inverse problems, people count, sensor data, zone air parameters}, issn = {03787788}, doi = {10.1016/j.enbuild.2019.06.008}, author = {Li, Han and Hong, Tianzhen and Sofos, Marina} } @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} } @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 {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 {32158, title = {Validation of an inverse model of zone air heat balance}, journal = {Building and Environment}, volume = {161}, year = {2019}, month = {Jan-08-2019}, pages = {106232}, abstract = {

This paper presents the validation method and results of an inverse model of zone air heat balance. The inverse model, implemented in EnergyPlus and published in a previous article [1], calculates highly uncertain model parameters such as internal thermal mass and infiltration airflow by inversely solving the zone air heat balance equation using the easy-to-measure zone air temperature data. The paper provides technical details of validation from the experiments using LBNL{\textquoteright}s Facility for Low Energy eXperiment in Buildings (FLEXLAB) that measures zone air temperature under the controlled experiment of two levels of internal mass and four levels of infiltration airflow. The simulation results of the zone infiltration airflow and internal thermal mass from the inverse model agree well with the measured data from the FLEXLAB experiments. The validated inverse model in EnergyPlus can be used to enhance the energy modeling of existing buildings that enables energy performance assessments for energy efficiency improvements.

}, keywords = {Energy simulation, energyplus, infiltration, internal thermal mass, inverse model, sensor data}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.106232}, author = {Lee, Sang Hoon and Hong, Tianzhen} } @article {30487, title = {Building Simulation: Ten Challenges}, journal = {Building Simulation}, volume = {11}, year = {2018}, abstract = {

Buildings consume more than one-third of the world{\textquoteright}s primary energy. Reducing energy use and greenhouse-gas emissions in the buildings sector through energy conservation and efficiency improvements constitutes a key strategy for achieving global energy and environmental goals. Building performance simulation has been increasingly used as a tool for designing, operating and retrofitting buildings to save energy and utility costs. However, opportunities remain for researchers, software developers, practitioners and policymakers to maximize the value of building performance simulation in the design and operation of low energy buildings and communities that leverage interdisciplinary approaches to integrate humans, buildings, and the power grid at a large scale. This paper presents ten challenges that highlight some of the most important issues in building performance simulation, covering the full building life cycle and a wide range of modeling scales. The formulation and discussion of each challenge aims to provide insights into the state-of-the-art and future research opportunities for each topic, and to inspire new questions from young researchers in this field.

}, keywords = {building energy use, building life cycle, building performance simulation, energy efficiency, energy modeling, zero-net-energy buildings}, doi = {10.1007/s12273-018-0444-x}, author = {Tianzhen Hong and Jared Langevin and Kaiyu Sun} } @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 {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 {31310, title = {Representation and evolution of urban weather boundary conditions in downtown Chicago}, journal = {Journal of Building Performance Simulation}, year = {2018}, month = {11/2018}, pages = {1 - 14}, abstract = {

This study presents a novel computing technique for data exchange and coupling between a high-resolution weather simulation model and a building energy model, with a goal of evaluating the impact of urban weather boundary conditions on energy performance of urban buildings. The Weather Research and Forecasting (WRF) model is initialized with the operational High-Resolution Rapid Refresh (HRRR) dataset to provide hourly weather conditions over the Chicago region. We utilize the building footprint, land use, and building stock datasets to generate building energy models using EnergyPlus. We mapped the building exterior surfaces to local air nodes to import simulated microclimate data and to export buildings{\textquoteright} heat emissions to their local environment. Preliminary experiments for a test area in Chicago show that predicted building cooling energy use differs by about 4.7\% for the selected date when compared with simulations using TMY weather data and without considering the urban microclimate boundary conditions.

}, keywords = {coupling, energy modeling, energyplus, Urban climate modeling, WRF}, issn = {1940-1493}, doi = {10.1080/19401493.2018.1534275}, url = {https://www.tandfonline.com/doi/full/10.1080/19401493.2018.1534275https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.1534275}, author = {Rajeev Jain and Xuan Luo and G{\"o}khan Sever and Tianzhen Hong and Charlie Catlett} } @conference {31355, title = {When Data Analytics Meet Site Operation: Benefits and Challenges}, booktitle = {2018 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2018}, month = {08/2018}, abstract = {

Demand for using data analytics for energy management in buildings is rising. Such analytics are required for advanced measurement and verification, commissioning, automated fault-detection and diagnosis, and optimal control. While novel analytics algorithms continue to be developed, bottlenecks and challenges arise when deploying them for demonstration, for a number of reasons that do not necessarily have to do with the algorithms themselves. It is important for developers of new technologies to be aware of the challenges and potential solutions during demonstration. Therefore, this paper describes a recent deployment of an automated, physical model-based, FDD and optimal control tool, highlighting its design and as-operated benefits that the tool provides. Furthermore, the paper presents challenges faced during deployment and testing along with solutions used to overcome these challenges. The challenges have been grouped into four categories: Data Management, Physical Model Development and Integration, Software Development and Deployment, and Operator Use. The paper concludes by discussing how challenges with this project generalize to common cases, how they could compare to other projects in their severity, and how they may be addressed.

}, author = {David Blum and Guanjing Lin and Michael Spears and Janie Page and Jessica Granderson} } @article {29894, title = {An Agent-Based Stochastic Occupancy Simulator}, year = {2017}, abstract = {

Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This paper presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with Reinhart{\textquoteright}s LIGHTSWITCH-2002 model, (2) the random moving events (e.g., from one office to another) simulated with Wang{\textquoteright}s homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building. The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.

}, author = {Yixing Chen and Tianzhen Hong and Xuan Luo} } @article {30301, title = {Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China}, journal = {Applied Energy}, volume = {195}, year = {2017}, month = {06/2017}, pages = {890-904}, abstract = {

Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.

}, keywords = {Actual weather data, building simulation, energy use, Multiyear simulation, Peak load , Typical year}, doi = {10.1016/j.apenergy.2017.03.113}, author = {Ying Cui and Da Yan and Tianzhen Hong and Chan Xiao and Xuan Luo and Qi Zhang} } @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 {30027, title = {Electric Load Shape Benchmarking for Small- and Medium-Sized Commercial Buildings}, year = {2017}, abstract = {

Small- and medium-sized commercial buildings owners and utility managers often look for opportunities for energy cost savings through energy efficiency and energy waste minimization. However, they currently lack easy access to low-cost tools that help interpret the massive amount of data needed to improve understanding of their energy use behaviors. Benchmarking is one of the techniques used in energy audits to identify which buildings are priorities for an energy analysis. Traditional energy performance indicators, such as the energy use intensity (annual energy per unit of floor area), consider only the total annual energy consumption, lacking consideration of the fluctuation of energy use behavior over time, which reveals the time of use information and represents distinct energy use behaviors during different time spans. To fill the gap, this study developed a general statistical method using 24-hour electric load shape benchmarking to compare a building or business/tenant space against peers. Specifically, the study developed new forms of benchmarking metrics and data analysis methods to infer the energy performance of a building based on its load shape. We first performed a data experiment with collected smart meter data using over 2,000 small- and medium-sized businesses in California. We then conducted a cluster analysis of the source data, and determined and interpreted the load shape features and parameters with peer group analysis. Finally, we implemented the load shape benchmarking feature in an open-access web-based toolkit (the Commercial Building Energy Saver) to provide straightforward and practical recommendations to users. The analysis techniques were generic and flexible for future datasets of other building types and in other utility territories.

}, keywords = {benchmarking, Building energy, cluster analysis, load profile, load shape, representative load pattern}, author = {Xuan Luo and Tianzhen Hong and Yixing Chen and Mary Ann Piette} } @article {29898, title = {The Human Dimensions of Energy Use in Buildings: A Review}, year = {2017}, abstract = {

The "human dimensions" of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplified by stakeholders. This paper presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building{\textquoteright}s lifecycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights. Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners;enhanced comfort conditions and productivity for building occupants;more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors.

}, author = {Simona D{\textquoteright}Oca and Tianzhen Hong and Jared Langevin} } @article {30313, title = {Performance Evaluation of an Agent-based Occupancy Simulation Model}, journal = {Building and Environment}, volume = {115}, year = {2017}, month = {04/2017}, abstract = {

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types were first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.

}, keywords = {model performance evaluation, occupancy pattern, Occupancy simulation, occupant behavior, occupant presence and movement, verification}, doi = {10.1016/j.buildenv.2017.01.015}, author = {Xuan Luo and Khee Poh Lam and Yixing Chen and Tianzhen Hong} } @article {30311, title = {Simulation and visualization of energy-related occupant behavior in office buildings}, journal = {Building Simulation}, volume = {10}, year = {2017}, month = {03/2017}, pages = {785{\textendash}798}, abstract = {

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using those charts, it is difficult to visualize and communicate the importance of occupants{\textquoteright} behavior to building energy performance. This study introduced a new approach to simulating and visualizing energy-related occupant behavior in office buildings. First, the Occupancy Simulator was used to simulate the occupant presence and movement and generate occupant schedules for each space as well as for each occupant. Then an occupant behavior functional mockup unit (obFMU) was used to model occupant behavior and analyze their impact on building energy use through co-simulation with EnergyPlus. Finally, an agent-based model built upon AnyLogic was applied to visualize the simulation results of the occupant movement and interactions with building systems, as well as the related energy performance. A case study using a small office building in Miami, FL was presented to demonstrate the process and application of the Occupancy Simulator, the obFMU and EnergyPlus, and the AnyLogic module in simulation and visualization of energy-related occupant behaviors in office buildings. The presented approach provides a new detailed and visual way for policy makers, architects, engineers and building operators to better understand occupant energy behavior and their impact on energy use in buildings, which can improve the design and operation of low energy buildings.

}, keywords = {Behavior Modeling, building performance, building simulation, energyplus, occupant behavior, visualization}, doi = {10.1007/s12273-017-0355-2}, author = {Yixing Chen and Xin Liang and Tianzhen Hong and Xuan Luo} } @article {29854, title = {Small and Medium Building Efficiency Toolkit and Community Demonstration Program}, year = {2017}, month = {03/2017}, abstract = {

Small commercial buildings in the United States consume 47 percent of all primary energy consumed in the building sector. Retrofitting small and medium commercial buildings may pose a steep challenge for owners, as many lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. To address this problem, this project developed the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit that calculates the energy use of a building, identifies and evaluates retrofit measures based on energy savings, energy cost savings, and payback. The CBES Toolkit includes a web app for end users and the CBES Application Programming Interface for integrating CBES with other energy software tools. The toolkit provides a rich feature set, including the following:

  1. Energy Benchmarking providing an Energy Star score
  2. Load Shape Analysis to identify potential building operation improvements
  3. Preliminary Retrofit Analysis which uses a custom developed pre-simulated database
  4. Detailed Retrofit Analysis which utilizes real time EnergyPlus simulations

In a parallel effort the project team developed technologies to measure outdoor airflow rate; commercialization and use would avoid both excess energy use from over ventilation and poor indoor air quality resulting from under ventilation.

If CBES is adopted by California{\textquoteright}s statewide small office and retail buildings, by 2030 the state can anticipate 1,587 gigawatt hours of electricity savings, 356 megawatts of non-coincident peak demand savings, 30.2 megatherms of natural gas savings, $227 million of energy-related cost savings, and reduction of emissions by 757,866 metric tons of carbon dioxide equivalent. In addition, consultant costs will be reduced in the retrofit analysis process.

CBES contributes to the energy savings retrofit field by enabling a straightforward and uncomplicated decision-making process for small and medium business owners and leveraging different levels of assessment to match user background, preference, and data availability.

}, keywords = {CBES, commercial buildings, energy efficiency, energy modeling, energy savings, indoor air quality, indoor environmental quality, outdoor air measurement technology, outdoor airflow intake rate, retrofit, ventilation rate}, doi = {10.7941/S93P70}, author = {Mary Ann Piette and Tianzhen Hong and William J. Fisk and Norman Bourassa and Wanyu R. Chan and Yixing Chen and H.Y. Iris Cheung and Toshifumi Hotchi and Margarita Kloss and Sang Hoon Lee and Phillip N. Price and Oren Schetrit and Kaiyu Sun and Sarah C. Taylor-Lange and Rongpeng Zhang} } @article {30303, title = {A Thorough Assessment of China{\textquoteright}s Standard for Energy Consumption of Buildings}, journal = {Energy and Buildings}, year = {2017}, month = {03/2017}, abstract = {

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

}, keywords = {China, code and standard, energy consumption, energy efficiency, Energy Use Intensity, outcome-based code}, doi = {10.1016/j.enbuild.2017.03.019}, author = {Da Yan and Tianzhen Hong and Cheng Li and Qi Zhang and Jingjing An and shan Hu} } @conference {60968, title = {An Agent-Based Occupancy Simulator for Building Performance Simulation}, year = {2016}, abstract = {

Traditionally, in building energy modeling (BEM) programs, occupancy inputs are deterministic and less indicative of real world scenarios, contributing to discrepancies between simulated and actual energy use in buildings. This paper presents an agent-based occupancy simulator, which models each occupant as an agent with specified movement events and statistics of space uses. To reduce the amount of data inputs, the simulator allows users to group occupants with similar behaviors as an occupant type, and spaces with similar function as a space type. It is a web-based application with friendly graphical user interface, cloud computing, and data storage. A case study is presented to demonstrate the usage of the occupancy simulator and its integration with EnergyPlus and obFMU. It first shows the required data inputs and the results from the occupancy simulator. Then, the generated occupant schedules are used in the EnergyPlus and obFMU simulation to evaluate the impacts of occupant behavior on building energy performance. The simulation results indicate that the occupancy simulator can capture the diversity of space{\textquoteright}s occupancy behavior rather than the static weekly profiles, and can generate realistic occupancy schedules to support building performance simulation.

}, author = {Yixing Chen and Xuan Luo and Tianzhen Hong} } @article {30317, title = {Improving the accuracy of energy baseline models for commercial buildings with occupancy data}, journal = {Applied Energy}, year = {2016}, abstract = {

More than 80\% of energy is consumed during operation phase of a building{\textquoteright}s life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by {\textquotedblleft}measurement and verification{\textquotedblright} (M\&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the {\textquotedblleft}baseline{\textquotedblright} of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. The results from this study can help us understand the influence of occupancy on energy use, improve energy baseline prediction by including the occupancy factor, reduce risks of M\&V and facilitate investment strategies of energy efficiency retrofit.

}, keywords = {baseline model, building energy use, Energy Efficiency Retrofit, Measurement and verification, occupancy}, author = {Xin Liang and Tianzhen Hong and Geoffrey Qiping Shen} } @article {30316, title = {Occupancy data analytics and prediction: a case study}, year = {2016}, abstract = {

Occupants are a critical impact factor of building energy consumption. Numerous previous studies emphasized the role of occupants and investigated the interactions between occupants and buildings. However, a fundamental problem, how to learn occupancy patterns and predict occupancy schedule, has not been well addressed due to highly stochastic activities of occupants and insufficient data. This study proposes a data mining based approach for occupancy schedule learning and prediction in office buildings. The proposed approach first recognizes the patterns of occupant presence by cluster analysis, then learns the schedule rules by decision tree, and finally predicts the occupancy schedules based on the inducted rules. A case study was conducted in an office building in Philadelphia, U.S. Based on one-year observed data, the validation results indicate that the proposed approach significantly improves the accuracy of occupancy schedule prediction. The proposed approach only requires simple input data (i.e., the time series data of occupant number entering and exiting a building), which is available in most office buildings. Therefore, this approach is practical to facilitate occupancy schedule prediction, building energy simulation and facility operation.

}, keywords = {data mining, Machine learning, occupancy prediction, occupant presence}, author = {Xin Liang and Tianzhen Hong and Geoffrey Qiping Shen} } @article {60965, title = {Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance}, journal = {Energy}, year = {2015}, month = {07/2015}, chapter = {738}, abstract = {

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use, however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailed on-site energy audit to identify and evaluate cost-effective energy technologies. This study presents a DEEP (database of energy efficiency performance) that provides a direct resource for quick retrofit analysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlus simulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. The simulations utilize prototype models representative of small and mid-size offices and retails in California climates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performance computing clusters to evaluate hundreds of individual and packaged ECMs covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture and simulation environment to create DEEP is flexible and can expand to cover additional building types, additional climates, and new ECMs. In this study DEEP is integrated into a web-based retrofit toolkit, the Commercial Building Energy Saver, which provides a platform for energy retrofit decision making by querying DEEP and unearthing recommended ECMs, their estimated energy savings and financial payback.

}, keywords = {building simulation, Energy conservation measure, energy modeling, energyplus, High Performance computing, retrofit}, doi = {10.1016/j.energy.2015.07.107}, author = {Sang Hoon Lee and Tianzhen Hong and Mary Ann Piette and Geof Sawaya and Yixing Chen and Sarah C. Taylor-Lange} } @article {60092, title = {Assessment of the Potential to Achieve Very Low Energy Use in Public Buildings in China with Advanced Window and Shading Systems}, journal = {Buildings}, volume = {5}, year = {2015}, month = {05/2015}, pages = {668-699}, chapter = {668}, abstract = {

As rapid growth in the construction industry continues to occur in China, the increased demand for a higher standard living is driving significant growth in energy use and demand across the country. Building codes and standards have been implemented to head off this trend, tightening prescriptive requirements for fenestration component measures using methods similar to the US model energy code American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1. The objective of this study is to (a) provide an overview of applicable code requirements and current efforts within China to enable characterization and comparison of window and shading products, and (b) quantify the load reduction and energy savings potential of several key advanced window and shading systems, given the divergent views on how space conditioning requirements will be met in the future.

System-level heating and cooling loads and energy use performance were evaluated for a code-compliant large office building using the EnergyPlus building energy simulation program. Commercially-available, highly-insulating, low-emittance windows were found to produce 24-66\% lower perimeter zone HVAC electricity use compared to the mandated energy-efficiency standard in force (GB 50189-2005) in cold climates like Beijing. Low-e windows with operable exterior shading produced up to 30-80\% reductions in perimeter zone HVAC electricity use in Beijing and 18-38\% reductions in Shanghai compared to the standard. The economic context of China is unique since the cost of labor and materials for the building industry is so low. Broad deployment of these commercially available technologies with the proper supporting infrastructure for design, specification, and verification in the field would enable significant reductions in energy use and greenhouse gas emissions in the near term.

}, keywords = {building, China, energy efficiency, shading, windows}, doi = {10.3390/buildings5020668}, author = {Eleanor S. Lee and Xiufeng Pang and Andrew McNeil and Sabine Hoffmann and Anothai Thanachareonkit and Zhengrong Li and Yong Ding} } @article {61107, title = {Commercial Building Energy Saver: An energy retrofit analysis toolkit}, journal = {Applied Energy}, volume = {159}, year = {2015}, month = {9/2015}, chapter = {298}, abstract = {

Small commercial buildings in the United States consume 47\% of the total primary energy of the buildings sector. Retrofitting small and medium commercial buildings poses a huge challenge for owners because they usually lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. This paper presents the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit, which calculates the energy use of a building, identifies and evaluates retrofit measures in terms of energy savings, energy cost savings and payback. The CBES Toolkit includes a web app (APP) for end users and the CBES Application Programming Interface (API) for integrating CBES with other energy software tools. The toolkit provides a rich set of features including: (1) Energy Benchmarking providing an Energy Star score, (2) Load Shape Analysis to identify potential building operation improvements, (3) Preliminary Retrofit Analysis which uses a custom developed pre-simulated database and, (4) Detailed Retrofit Analysis which utilizes real-time EnergyPlus simulations. CBES includes 100 configurable energy conservation measures (ECMs) that encompass IAQ, technical performance and cost data, for assessing 7 different prototype buildings in 16 climate zones in California and 6 vintages. A case study of a small office building demonstrates the use of the toolkit for retrofit analysis. The development of CBES provides a new contribution to the field by providing a straightforward and uncomplicated decision making process for small and medium business owners, leveraging different levels of assessment dependent upon user background, preference and data availability.

}, keywords = {Building Technologies Department, Building Technology and Urban Systems Division, buildings, buildings energy efficiency, Commercial Building Systems, conservation measures, energy efficiency, energy use, energyplus, External, Retrofit Energy, simulation research}, doi = {10.1016/j.apenergy.2015.09.002}, author = {Tianzhen Hong and Mary Ann Piette and Yixing Chen and Sang Hoon Lee and Sarah C. Taylor-Lange and Rongpeng Zhang and Kaiyu Sun and Phillip N. Price} } @article {59986, title = {DEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings}, year = {2015}, abstract = {

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and domestic hot water. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of an on-going project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users{\textquoteright} decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit. DEEP will be migrated into the DEnCity - DOE{\textquoteright}s Energy City, which integrates large-scale energy data for multi-purpose, open, and dynamic database leveraging diverse source of existing simulation data.

}, author = {Sang Hoon Lee and Tianzhen Hong and Geof Sawaya and Yixing Chen and Mary Ann Piette} } @article {60955, title = {Energy retrofit analysis toolkit for commercial buildings: A review}, volume = {89}, year = {2015}, month = {09/2015}, pages = {1087-1100}, publisher = {Elsevier Ltd.}, chapter = {1087}, abstract = {

Retrofit analysis toolkits can be used to optimize energy or cost savings from retrofit strategies, accelerating the adoption of ECMs (energy conservation measures) in buildings. This paper provides an up-todate review of the features and capabilities of 18 energy retrofit toolkits, including ECMs and the calculation engines. The fidelity of the calculation techniques, a driving component of retrofit toolkits, were evaluated. An evaluation of the issues that hinder effective retrofit analysis in terms of accessibility, usability, data requirement, and the application of efficiency measures, provides valuable insights into advancing the field forward. Following this review the general concepts were determined: (1) toolkits developed primarily in the private sector use empirically data-driven methods or benchmarking to provide ease of use, (2) almost all of the toolkits which used EnergyPlus or DOE-2 were freely accessible, but suffered from complexity, longer data input and simulation run time, (3) in general, there appeared to be a fine line between having too much detail resulting in a long analysis time or too little detail which sacrificed modeling fidelity. These insights provide an opportunity to enhance the design and development of existing and new retrofit toolkits in the future.

}, keywords = {Building energy retrofit, Energy conservation measures, Energy efficiency, Energy simulation, Retrofit analysis tools, Web-based applications}, doi = {10.1016/j.energy.2015.06.112}, author = {Sang Hoon Lee and Tianzhen Hong and Mary Ann Piette and Sarah C. Taylor-Lange} } @article {59957, title = {An Insight into Actual Energy Use and Its Drivers in High-Performance Buildings}, year = {2015}, abstract = {

Using portfolio analysis and individual detailed case studies, we studied the energy performance and drivers of energy use in 51 high-performance office buildings in the U.S., Europe, China, and other parts of Asia. Portfolio analyses revealed that actual site energy use intensity (EUI) of the study buildings varied by a factor of as much as 11, indicating significant variation in real energy use in HPBs worldwide. Nearly half of the buildings did not meet the American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) Standard 90.1-2004 energy target, raising questions about whether a building{\textquoteright}s certification as high performing accurately indicates that a building is energy efficient and suggesting that improvement in the design and operation of HPBs is needed to realize their energy-saving potential. We studied the influence of climate, building size, and building technologies on building energy performance and found that although all are important, none are decisive factors in building energy use. EUIs were widely scattered in all climate zones. There was a trend toward low energy use in small buildings, but the correlation was not absolute; some small HPBs exhibited high energy use, and some large HPBs exhibited low energy use. We were unable to identify a set of efficient technologies that correlated directly to low EUIs. In two case studies, we investigated the influence of occupant behavior as well as operation and maintenance on energy performance and found that both play significant roles in realizing energy savings. We conclude that no single factor determines the actual energy performance of HPBs, and adding multiple efficient technologies does not necessarily improve building energy performance; therefore, an integrated design approach that takes account of climate, technology, occupant behavior, and operations and maintenance practices should be implemented to maximize energy savings in HPBs. These findings are intended to help architects, engineers, operators, and policy makers improve the design and operation of HPBs.

}, keywords = {actual energy use, building technologies, driving factors, high-performance buildings, integrated design, performance rating}, author = {Cheng Li and Tianzhen Hong and Da Yan} } @article {60966, title = {Updates to the China Design Standard for Energy Efficiency in Public Buildings}, journal = {Energy Policy}, volume = {87}, year = {2015}, month = {12/2015}, pages = {187-198}, abstract = {

The China Design Standard for Energy Efficiency in public buildings (GB 50189) debuted in 2005 when China completed the 10th Five-Year Plan. GB 50189-2005 played a crucial role in regulating the energy efficiency in Chinese commercial buildings. The standard was recently updated in 2014 to increase energy savings targets by 30\% compared with the 2005 standard. This paper reviews the major changes to the standard, including expansion of energy efficiency coverage and more stringent efficiency requirements. The paper also discusses the interrelationship of the design standard with China{\textquoteright}s other building energy standards. Furthermore, comparisons are made with ASHRAE Standard 90.1-2013 to provide contrasting differences in efficiency requirements. Finally recommendations are provided to guide the future standard revision, focusing on three areas: (1) increasing efficiency requirements of building envelope and HVAC systems, (2) adding a whole-building performance compliance pathway and implementing a ruleset based automatic code baseline model generation in an effort to reduce the discrepancies of baseline models created by different tools and users, and (3) adding inspection and commissioning requirements to ensure building equipment and systems are installed correctly and operate as designed.

}, keywords = {building design, building energy standard, China, energy efficiency, GB 50189, Public buildings}, doi = {10.1016/j.enpol.2015.09.013}, author = {Tianzhen Hong and Cheng Li and Da Yan} } @article {59965, title = {Comparison of Building Energy Use Data Between the United States and China}, journal = {Energy and Buildings}, volume = {78}, year = {2014}, month = {08/2014}, pages = {165-175}, abstract = {

Buildings in the United States and China consumed 41\% and 28\% of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.{\textendash}China Clean Energy Research Center for Building Energy Efficiency. The goal is to decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply.

}, keywords = {buildings, comparison, data analysis, data model, Energy benchmarking, energy monitoring system, energy use, retrofit}, doi = {10.1016/j.enbuild.2014.04.031}, author = {Jianjun Xia and Tianzhen Hong and Qi Shen and Wei Feng and Le Yang and Piljae Im and Alison Lu and Mahabir Bhandari} } @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} } @article {58863, title = {Review of Existing Energy Retrofit Tools}, year = {2014}, author = {Sang Hoon Lee and Tianzhen Hong and Mary Ann Piette} } @conference {59966, title = {Revisit of Energy Use and Technologies of High Performance Buildings}, booktitle = {2014 ASHRAE Annual Conference}, year = {2014}, month = {06/2014}, publisher = {ASHRAE}, organization = {ASHRAE}, address = {Seattle, WA}, abstract = {

Energy consumed by buildings accounts for one third of the world{\textquoteright}s total primary energy use. Associated with the conscious of energy savings in buildings, High Performance Buildings (HPBs) has surged across the world, with wide promotion and adoption of various performance rating and certification systems. It is valuable to look into the actual energy performance of HPBs and to understand their influencing factors.

To shed some light on this topic, this paper conducted a series of portfolio analysis based on a database of 51 high performance office buildings across the world. Analyses showed that the actual site Energy Use Intensity (EUI) of the 51 buildings varied by a factor of up to 11, indicating a large scale of variation of the actual energy performance of the current HPBs. Further analysis of the correlation between EUI and climate elucidated ubiquitous phenomenon of EUI scatter throughout all climate zones, implying that the weather is not a decisive factor, although important, for the actual energy consumption of an individual building. On the building size via EUI, analysis disclosed that smaller buildings have a tendency to achieving lower energy use. Even so, the correlation is not absolute since some large buildings demonstrated low energy use while some small buildings performed opposite. Concerning the technologies, statistics indicated that the application of some technologies had correlations with some specific building size and climate characteristic. However, it was still hard to pinpoint a set of technologies which was directly correlative with a group of low EUI buildings.

It is concluded that no a single factor essentially determines the actual energy performance of HPBs. To deliver energy-efficient buildings, an integrated design taking account of climate, technology, occupant behavior as well as operation and maintenance should be implemented.

}, url = {https://www.techstreet.com/ashrae/standards/se-14-c033-revisit-of-energy-use-and-technologies-of-high-performance-buildings}, author = {Cheng Li and Tianzhen Hong} } @article {59968, title = {Building Energy Monitoring and Analysis}, year = {2013}, month = {06/2013}, abstract = {

U.S. and China are the world{\textquoteright}s top two economics. Together they consumed one-third of the world{\textquoteright}s primary energy. It is an unprecedented opportunity and challenge for governments, researchers and industries in both countries to join together to address energy issues and global climate change. Such joint collaboration has huge potential in creating new jobs in energy technologies and services.

Buildings in the US and China consumed about 40\% and 25\% of the primary energy in both countries in 2010 respectively. Worldwide, the building sector is the largest contributor to the greenhouse gas emission. Better understanding and improving the energy performance of buildings is a critical step towards sustainable development and mitigation of global climate change.

This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.

Key research findings were summarized as follows:

The research outputs from the project can help better understand energy performance of buildings, improve building operations to reduce energy waste and increase efficiency, identify retrofit opportunities for existing buildings, and provide guideline to improve the design of new buildings. The standardized energy monitoring and analysis platform as well as the collected real building data can also be used for other CERC projects that need building energy measurements, and be further linked to building energy benchmarking and rating/labeling systems.

}, author = {Tianzhen Hong and Wei Feng and Alison Lu and Jianjun Xia and Le Yang and Qi Shen and Piljae Im and Mahabir Bhandari} } @article {56236, title = {A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data}, journal = {Applied Energy}, volume = {111}, year = {2013}, month = {11/2013}, pages = {333-350}, publisher = {Lawrence Berkeley National Laboratory}, abstract = {

Buildings consume more than one third of the world{\textquoteright}s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980{\textendash}2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: (1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; (2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; (3) the weather impact is greater for buildings in colder climates than warmer climates; (4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and (5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.

}, keywords = {Actual meteorological year, building simulation, energy use, Peak electricity demand, Typical meteorological year, weather data}, doi = {10.1016/j.apenergy.2013.05.019}, author = {Tianzhen Hong and Wen-Kuei Chang and Hung-Wen Lin} } @article {56946, title = {The Two-Day CERC-BEE Forum on Building Integrated Design and Occupant Behavior: Presentations and Summary}, year = {2013}, author = {Tianzhen Hong and William J. N. Turner and Cheng Li} } @conference {2670, title = {An In-Depth Analysis of Space Heating Energy Use in Office Buildings}, booktitle = {ACEEE 2012 Summer Study}, year = {2012}, month = {08/2012}, publisher = {ACEEE}, organization = {ACEEE}, address = {Asilomar, CA}, abstract = {

Space heating represents the largest end use in the U.S. buildings and consumes more than 7 trillion Joules of site energy annually [USDOE]. Analyzing building space heating performance and identifying methods for saving energy are quite important. Hence, it is crucial to identify and evaluate key driving factors to space heating energy use to support the design and operation of low energy buildings.

In this study, the prototypical small and large-size office buildings of the USDOE commercial reference buildings, which comply with ASHRAE Standard 90.1-2004, are selected. Key design and operation factors were identified to evaluate their degrees of impact for space heating energy use. Simulation results demonstrate that some of the selected building design and operation parameters have more significant impacts on space heating energy use than others, on the other hand, good operation practice can save more space heating energy than raising design efficiency levels of an office building. Influence of weather data used in simulations on space heating energy is found to be significant. The simulated space heating energy use is further benchmarked against those from similar office buildings in two U.S. commercial buildings databases to better understand the discrepancies.

Simulated results from this study and space heating energy use collected from building databases can both vary in two potentially well overlapped wide ranges depending on details of building design and operation, not necessarily that simulation always under-predicts the reality.

}, keywords = {building energy performance, building simulation, simulation research, simulation research group, space heating}, author = {Hung-Wen Lin and Tianzhen Hong} } @conference {2671, title = {A Retrofit Tool for Improving Energy Efficiency of Commercial Buildings}, booktitle = {ACEEE 2012 Summer Study}, year = {2012}, month = {08/2012}, address = {Asilomar, CA}, abstract = {

Existing buildings will dominate energy use in commercial buildings in the United States for three decades or longer and even in China for the about two decades. Retrofitting these buildings to improve energy efficiency and reduce energy use is thus critical to achieving the target of reducing energy use in the buildings sector. However there are few evaluation tools that can quickly identify and evaluate energy savings and cost effectiveness of energy conservation measures (ECMs) for retrofits, especially for buildings in China. This paper discusses methods used to develop such a tool and demonstrates an application of the tool for a retrofit analysis. The tool builds on a building performance database with pre-calculated energy consumption of ECMs for selected commercial prototype buildings using the EnergyPlus program. The tool allows users to evaluate individual ECMs or a package of ECMs. It covers building envelope, lighting and daylighting, HVAC, plug loads, service hot water, and renewable energy. The prototype building can be customized to represent an actual building with some limitations. Energy consumption from utility bills can be entered into the tool to compare and calibrate the energy use of the prototype building. The tool currently can evaluate energy savings and payback of ECMs for shopping malls in China. We have used the tool to assess energy and cost savings for retrofit of the prototype shopping mall in Shanghai. Future work on the tool will simplify its use and expand it to cover other commercial building types and other countries.\ 

}, keywords = {building simulation, buildings, China, commercial building, energy efficiency measures, retrofit tool, simulation research group}, url = {http://aceee.org/files/proceedings/2012/data/papers/0193-000098.pdf$\#$page=1}, author = {Mark D. Levine and Wei Feng and Jing Ke and Tianzhen Hong and Nan Zhou} } @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} } @article {2579, title = {Prevention of Compressor Short Cycling in Direct-Expansion (DX) Rooftop Units, Part 1: Theoretical Analysis and Simulation}, journal = {ASHRAE Transactions}, volume = {117}, year = {2011}, pages = {666-676}, author = {Xiufeng Pang and Mingsheng Liu} } @article {2580, title = {Prevention of Compressor Short Cycling in Direct-Expansion (DX) Rooftop Units{\textemdash} Part 2: Field Investigation}, journal = {ASHRAE Transactions}, volume = {117}, year = {2011}, pages = {677-685}, author = {Xiufeng Pang and Mingsheng Liu} } @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 {214, title = {Anisotropy invariant Reynolds stress model of turbulence (AIRSM) and its application on attached and separated wall-bounded flows}, journal = {Flow, Turbulence and Combustion}, volume = {83}, year = {2009}, month = {07/2009}, pages = {81-103}, chapter = {81}, abstract = {

Numerical predictions with a differential Reynolds stress closure, which in its original formulation explicitly takes into account possible states of turbulence on the anisotropy-invariant map, are presented. Thus the influence of anisotropy of turbulence on the modeled terms in the governing equations for the Reynolds stresses is accounted for directly. The anisotropy invariant Reynolds stress model (AIRSM) is implemented and validated in different finite-volume codes. The standard wall-function approach is employed as initial step in order to predict simple and complex wall-bounded flows undergoing large separation. Despite the use of simple wall functions, the model performed satisfactory in predicting these flows. The predictions of the AIRSM were also compared with existing Reynolds stress models and it was found that the present model results in improved convergence compared with other models. Numerical issues involved in the implementation and application of the model are also addressed.

}, keywords = {Anisotrpoy, Invariant map, Reynolds stress model, Reynolds-averaged Navier-Stokes, Separated wall-bounded flow, Turbulence, Turbulence modeling}, issn = {1573-1987}, doi = {10.1007/s10494-008-9190-y}, author = {V. Kumar and Bettina Frohnapfel and Jovan Jovanovi{\'c} and Michael Breuer and Wangda Zuo and Ibrahim Hadzi{\'c} and Richard Lechner} } @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 {408, title = {Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems}, journal = {Energy and Buildings}, volume = {42}, year = {2009}, month = {2009}, pages = {584-589}, type = {Research Article}, abstract = {

With the current movement towards net zero energy buildings, many technologies are promoted with emphasis on their superior energy efficiency. The variable refrigerant flow (VRF) and ground source heat pump (GSHP) systems are probably the most competitive technologies among these. However, there are few studies reporting the energy efficiency of VRF systems compared with GSHP systems. In this article, a preliminary comparison of energy efficiency between the air-source VRF and GSHP systems is presented. The computer simulation results show that GSHP system is more energy efficient than the air-source VRF system for conditioning a small office building in two selected US climates. In general, GSHP system is more energy efficient than the air-source VRV system, especially when the building has significant heating loads. For buildings with less heating loads, the GSHP system could still perform better than the air-source VRF system in terms of energy efficiency, but the resulting energy savings may be marginal.

}, keywords = {building simulation, doe-2, energy efficiency, gshp, vrf}, doi = {10.1016/j.enbuild.2009.10.028}, author = {Xiaobing Liu and Tianzhen Hong} } @article {251, title = {Improving Control and Operation of a Single Duct VAV System through CCLEP}, journal = {ASHRAE Transactions}, volume = {115}, year = {2009}, month = {07/2009}, pages = {760-768}, abstract = {

With the energy crisis of the early 1970s came the realization that buildings could be made much more efficient without sacrificing comfort. Over the last 30 years, use of variable air volume systems has become common practice. Many variable air volume (VAV) systems with pneumatic controls were installed in the 1980s and are still in use. However, these systems often have outdated control strategies and deficient mechanical systems are deficient, which may cause occupant discomfort and excess energy consumption.

An ASHRAE committee proposed building commissioning in 1988 to ensure that system performance met design specifications. Continuous Commissioning (CC[R]) technology was developed and implemented in 1992. CC is an ongoing process to resolve operating problems, improve comfort, optimize energy use and identify retrofits for existing commercial and institutional buildings and central plant facilities [1-5]. Since 1999, the Energy Systems Laboratory (ESL) at the University of Nebraska has conducted extensive research to implement optimal system control during the design phase and finalize the optimal setpoints after system installation. ESL researchers have developed and implemented the Continuous Commissioning Leading Energy Project (CCLEP) process with federal and industry support. The CCLEP process has two stages: the contracting stage and the implementation stage. During the contracting stage, a comprehensive technical evaluation is performed. The CCLEP implementation stage involves planning, retrofit and trouble shooting, and optimization and follow-up. The CCLEP process, procedures and seven case study results are presented in [6].

This paper presents information on the case study facility, existing and improved control sequences, and building performance improvement and energy consumption measures before and after CCLEP implementation

}, author = {Young-Hum Cho and Mingsheng Liu and Xiufeng Pang} } @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} } @conference {2661, title = {Computer Model of a University Building Using the EnergyPlus Program}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Danielle Monfet and Radu Zmeureanu and Roland Charneux and Nicolas Lemire} } @conference {252, title = {Economizer Control Using Mixed Air Enthalpy}, booktitle = {the 7th International Conference of Enhanced Building Operations}, series = {7th}, year = {2007}, month = {2007}, address = {San Francisco, CA}, author = {Jingjuan Feng and Mingsheng Liu and Xiufeng Pang} } @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 {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} } @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} } @conference {2653, title = {The Study of a Simple HVAC Interface of EnergyPlus in the Chinese Language}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Junjie Liu and Wenshen Li and Xiaojie Zhou} } @conference {253, title = {VAV System Optimization through Continuous Commissioning in an Office Building}, booktitle = {the 7th International Conference of Enhanced Building Operations}, year = {2007}, month = {2007}, address = {San Francisco, CA}, author = {Young-Hum Cho and Xiufeng Pang and Mingsheng Liu} } @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 {2795, title = {Automated Multivariate Optimization Tool for Energy Analysis}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Peter G. Ellis and Brent T. Griffith and Nicholas Long and Paul A. Torcellini} } @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} } @conference {255, title = {Case Study of Continuous Commissioning in an Office Building}, booktitle = {the 6th International Conference of Enhanced Building Operations}, year = {2006}, month = {2006}, address = {Shenzhen, China}, author = {Xiufeng Pang and Zheng, B and Mingsheng Liu} } @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} } @proceedings {3393, title = {Evaluation of Methods for Determining Demand-Limiting Setpoint Trajectories in Commercial Buildings Using Short-Term Data Analysis}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Kyoung-ho Lee and James E. Braun} } @proceedings {2797, title = {Implementation of an Earth Tube System Into EnergyPlus Program}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Kwang Ho Lee and Richard K. Strand} } @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} } @proceedings {2801, title = {Radiant Slab Cooling: A Case Study of Building Energy Performance}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Zhen Tian and James A. Love} } @proceedings {2812, title = {Simulation Strategies for Healthcare Design to Achieve Comfort and Optimize Building Energy Use}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Shruti Narayan and Isabelle Lavedrine and Maurya McClintock} } @conference {257, title = {Building Pressure Control in VAV System with Relief Air Fan}, booktitle = {the 5th International Conference of Enhanced Building Operations}, year = {2005}, month = {2005}, address = {Pittsburgh, PA}, author = {Xiufeng Pang and Zheng, B and Mingsheng Liu} } @conference {258, title = {Continuous Commissioning of an Office Building}, booktitle = {the 5th International Conference of Enhanced Building Operations}, year = {2005}, month = {2005}, address = {Pittsburgh, PA}, author = {Zheng, B and Mingsheng Liu and Xiufeng Pang} } @conference {2665, title = {Design of the Natural Ventilation System for the New San Diego Children{\textquoteright}s Museum}, booktitle = {IBPSA Building Simulation 2005}, year = {2005}, month = {08/2005}, address = {Montreal, Canada}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Martha Brook} } @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} } @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 {2667, title = {Improving the Data Available to Simulation Programs}, booktitle = {IBPSA Building Simulation 2005}, year = {2005}, month = {08/2005}, address = {Montreal, Canada}, abstract = {

Building performance simulation tools have significantly improved in quality and depth of analysis capability over the past thirty-five years. Yet despite these increased capabilities, simulation programs still depend on user entry for significant data about building components, loads, and other typically scheduled inputs. This often forces users to estimate values or find previously compiled sets of data for these inputs. Often there is little information about how the data were derived, what purposes it is fit for, which standards apply, uncertainty associated with each data field as well as a general description of the data.

A similar problem bedeviled access to weather data and Crawley, Hand, and Lawrie (1999) described a generalized weather data format developed for use with two energy simulation programs which has subsequently lead to a repository which is accessed by thousands of practitioners each year.

This paper describes a generalized format and data documentation for user input{\textemdash}whether it is building envelope components, scheduled loads, or environmental emissions{\textemdash}the widgets upon which all models are dependant. We present several examples of the new input data format including building envelope component, a scheduled occupant load, and environmental emissions.

}, author = {Jon W. Hand and Drury B. Crawley and Michael Donn and Linda K. Lawrie} } @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 {256, title = {Using a Fan Air Flow Station to Control Building Static Pressure in a VAV System}, booktitle = {the 2005 International Solar Energy Conference}, year = {2005}, month = {2005}, address = {Orlando, FL}, author = {Zheng, B and Xiufeng Pang and Mingsheng Liu} } @article {11714, title = {Design and Testing of a Control Strategy for a Large Naturally Ventilated Office Building}, journal = {Building Services Engineering Research \& Technology}, volume = {25}, number = {3}, year = {2004}, pages = {211-221}, abstract = {

The design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. Each floor is designed to be cross-ventilated, through upper windows that are controlled by the building management system. Users have control over lower level windows, which can be as much as 50\% of the total openable area. There are significant differences in the performance and the control of the windward and leeward sides of the building, and separate monitoring and control strategies are determined for each side. The performance and control of the building has been designed and tested using a modified version of EnergyPlus. Results from studies with EnergyPlus and computational fluid dynamics are used in designing the control strategy. Wind-driven cross-ventilation produces a main jet through the upper openings of the building, across the ceiling from the windward to the leeward side. Below this jet, the occupied regions are subject to a recirculating airflow. Results show that temperatures within the building are predicted to be satisfactory, provided a suitable control strategy is implemented that uses night cooling in periods of hot weather. The control strategy has 10 window opening modes. EnergyPlus was extended to simulate the effects of these modes, and to assess the effects of different forms of user behaviour. The results show how user behaviour can significantly influence the building performance.

(Note: PDF contains both LBNL-56010 \& LBNL-56010 Conf.)

}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Philip Haves} } @article {280, title = {Design and Testing of a Control Strategy for a Large Naturally Ventilated Office Building}, journal = {Building Services Engineering Research \& Technology}, volume = {25}, year = {2004}, pages = {223-239}, abstract = {The design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. Each floor is designed to be cross-ventilated, through upper windows that are controlled by the building management system. Users have control over lower level windows, which can be as much as 50\% of the total openable area. There are significant differences in the performance and the control of the windward and leeward sides of the building, and separate monitoring and control strategies are determined for each side. The performance and control of the building has been designed and tested using a modified version of EnergyPlus. Results from studies with EnergyPlus and computational fluid dynamics are used in designing the control strategy. Wind-driven cross-ventilation produces a main jet through the upper openings of the building, across the ceiling from the windward to the leeward side. Below this jet, the occupied regions are subject to a recirculating airflow. Results show that temperatures within the building are predicted to be satisfactory, provided a suitable control strategy is implemented that uses night cooling in periods of hot weather. The control strategy has 10 window opening modes. EnergyPlus was extended to simulate the effects of these modes, and to assess the effects of different forms of user behaviour. The results show how user behaviour can significantly influence the building performance.}, doi = {10.1191/0143624404bt107oa}, url = {http://bse.sagepub.com/content/25/3/223}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Philip Haves} } @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} } @proceedings {2826, title = {Flow in an Underfloor Plenum}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Paul F. Linden} } @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} } @proceedings {2829, title = {Improvement of the ASHRAE Secondary HVAC Toolkit Simple Cooling Coil Model for Simulation}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Rahul Chillar and Richard J. Liesen} } @proceedings {2821, title = {Near Real-Time Weather Data Archive}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Nicholas Long} } @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} } @article {279, title = {Use of Simulation in the Design of a Large Naturally Ventilated Office Building}, journal = {Building Services Engineering Research \& Technology}, volume = {25}, year = {2004}, pages = {211-221}, abstract = {The design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. The EnergyPlus thermal simulation program was used to evaluate different ventilation strategies for space cooling and rationalize the design of the fa{\c c}ade. The strategies include ventilation driven by different combinations of wind, internal stack and external stack. The simulation results indicate that wind-driven ventilation can maintain adequate comfort even during hot periods. Computational fluid dynamics was used to study the airflow and temperature distribution in the occupied spaces arising from different combinations of window openings and outside conditions and thereby inform both the design of the windows and the control strategy.}, doi = {10.1191/0143624404bt102oa}, url = {http://bse.sagepub.com/content/25/3/211}, author = {Philip Haves and Paul F. Linden and Guilherme Carrilho da Gra{\c c}a} } @proceedings {2827, title = {Variable Heat Recovery in Double Bundle Electric Chillers}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Richard J. Liesen and Rahul Chillar} } @proceedings {294, title = {Design and Testing of a Control Strategy for a Large Naturally Ventilated Office Building}, year = {2003}, month = {08/2003}, address = {Eindhoven, Netherlands}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Erin McConahey and Philip Haves} } @proceedings {293, title = {Use of Simulation in the Design of a Large Naturally Ventilated Commercial Office Building}, year = {2003}, month = {08/2003}, address = {Eindhoven, Netherlands}, url = {http://www.inive.org/members_area/medias/pdf/Inive/IBPSA/UFSC912.pdf}, author = {Philip Haves and Guilherme Carrilho da Gra{\c c}a and Paul F. Linden} } @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} } @proceedings {304, title = {Use of Whole Building Simulation in On-Line Performance Assessment: Modeling and Implementation Issues}, year = {2001}, month = {08/2001}, address = {Rio de Janeiro}, abstract = {

The application of model-based performance assessment at the whole building level is explored. The information requirements for a simulation to predict the actual performance of a particular real building, as opposed to estimating the impact of design options, are addressed with particular attention to common sources of input error and important deficiencies in most simulation models. The role of calibrated simulations is discussed. The communication requirements for passive monitoring and active testing are identified and the possibilities for using control system communications protocols to link on-line simulation and energy management and control systems are discussed. The potential of simulation programs to act as "plug-and-play" components on building control networks is discussed.

}, author = {Philip Haves and Tim I. Salsbury and David Claridge and Mingsheng Liu} } @proceedings {310, title = {Better IAQ Through Integrating Design Tools For The HVAC Industry}, year = {2000}, month = {08/2000}, address = {Espoo, Finland}, abstract = {

There is currently no effective combination of interoperable design tools to cover all critical aspects of the HVAC design process. Existing design tools are separately available, but require expertise and operating time that is beyond the scope of a normal design project. For example, energy analysis and computational fluid dynamics (CFD) tools are not used in practical design, leading to poor indoor air quality and/or unnecessary energy consumption in buildings.

A prototype integrated software tool for demonstration, process mapping and proof-of-concept purposes was developed under a new international, Finland/USA jointly funded development project BildIT. Individual design tools were simplified and adapted to specific applications and also integrated so that they can be used in a timely and effective manner by the designer. The core of the prototype linked together an architectural CAD system, a 3D space model, a CFD program and a building energy simulation program and it utilises real product data from manufacturer{\textquoteright}s software. Also the complex building design, construction, maintenance and retrofit processes were mapped to get a template for the structure of the integrated design tool.

}, author = {Tuomas Laine and Risto Kosonen and Kim Hagstr{\"o}m and Panu Mustakallio and De-Wei Yin and Philip Haves and Qingyan Chen} } @proceedings {344, title = {Self-tuning Control with Fuzzy Rule-Based Supervision for HVAC Applications}, year = {1991}, address = {Singapore}, author = {Keck-Voon Ling and Arthur L. Dexter and Geng, G. and Philip Haves} } @article {343, title = {Use of a Building Emulator to Develop Techniques for Improved Commissioning and Control of HVAC Systems}, journal = {ASHRAE Transactions}, volume = {97}, year = {1991}, keywords = {air conditioning, automatic, commissioning, computer programs, controls, energy management, heating, ventilation}, author = {Philip Haves and Arthur L. Dexter and Jorgensen, D.R. and Keck-Voon Ling and Geng, G.} } @article {348, title = {Daylight in Dynamic Thermal Modelling Programs: a Case Study}, journal = {Building Services Engineering Research \& Technology}, volume = {9}, year = {1988}, month = {11/1988}, pages = {183-188}, chapter = {183}, abstract = {

Heating, cooling and lighting energy consumptions in buildings are inter-related, and a model which treats thermal performance and lighting simultaneously is required in order to evaluate the full benefits of daylighting in buildings. A lighting facility has been included in a dynamic building simulation program (SERI-RES) used in the Department of Energy{\textquoteright}s passive solar programme. Interior daylight illuminance is calculated using an extension of the daylight factor method. The lighting usage of various lighting systems is predicted from the daylight illuminance, and the thermal consequences of that lighting use included in the thermal simulation of the building. The applicability of the method described in this paper is not limited to SERI-RES. The method could be incorporated in any building energy analysis program intended for the UK or similar climates.

}, doi = {10.1177/014362448800900406}, author = {Philip Haves and Paul J. Littlefair} } @article {352, title = {Performance of Roofpond Cooled Residences in U.S. Climate}, journal = {Passive Solar Journal}, volume = {4}, year = {1987}, month = {01/1987}, pages = {265-292}, chapter = {265}, abstract = {

The thermal advantages of a roofpond as an element of a residential cooling system are described. The authors conducted heat transfer experiments at two roofpond residences (RPRs) at Trinity University; the authors used data from these experiments to validate RPR simulations. Results of measurements of vertical and horizontal temperature differences within roofponds are discussed. Horizontal heat transfer within one water bag was effective. Thermal resistance at the outer surface of a water bag with a deflated glazing can be significant. Simulation shows that an RPR can provide comfort without supplemental sensible cooling during almost all hours of a typical summer in any U.S climate. Ceiling fans are important in most climates. In the most demanding climates, the residence and the pond insulating panels must have high R-value. A map is included that provides RPR design guidance. The simulations indicate that dehumidification will be required to control mold, mildew, and ceiling condensation in an RPR in most climates; energy and power displacement by an RPR is sensitive to the humidity control required and the efficiency of the dehumidifier used.

}, author = {Gene Clark and Fred M. Loxsom and Earl S. Doderer and Philip Haves} } @proceedings {353, title = {Development of SERI-RES within the UK Passive Solar Programme}, year = {1986}, month = {06/1986}, address = {Boulder, CO}, author = {John G.F. Littler and Philip Haves} } @proceedings {357, title = {Results of Validated Simulations of Roof Pond Residences}, year = {1983}, address = {Santa Fe, NM}, author = {Gene Clark and Fred M. Loxsom and Philip Haves and Earl S. Doderer} } @proceedings {359, title = {Dehumidification and Passive Cooling for Retrofit and Conventional Construction}, year = {1982}, month = {07/1982}, address = {Knoxville, TN}, author = {Philip Haves and Fred M. Loxsom and Earl S. Doderer} } @proceedings {362, title = {Measurement of Components of Heat Transfer in Passive Cooling Systems}, year = {1981}, month = {11/1981}, address = {Miami, FL}, author = {Fred M. Loxsom and Gene Clark and Merino, M. and Philip Haves} }