@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} } @conference {31839, title = {Comparison of MPC Formulations for Building Control under Commercial Time-of-Use Tariffs}, booktitle = {IEEE PowerTech Milan 2019}, year = {2019}, month = {2019}, abstract = {

Most medium and large commercial buildings in\ the U.S. are subject to complex electricity tariffs that combine\ both Time-of-Use (TOU) energy and demand charges. This study\ analyses the performances of different economic Model Predictive\ Control (MPC) formulations, from the standpoints of monthly bill\ reduction, load shifting, and peak demand reduction. Simulations\ are performed on many simplified commercial building models,\ with multiple TOU demand charges, and under various summer\ conditions. Results show that compared to energy-only MPC, the\ traditional method for dealing with demand charges significantly
reduces peak demand and owner bill, however, highlight a lack\ of load shifting capability. A proposed incremental approach
is presented, which better balances the bill components in the\ objective function. In the case study presented, this method
can improve monthly bill savings and increase load shifting\ during demand response events, while keeping a similarly low
peak demand, compared to traditional MPC methods taking into\ account demand charges.

}, keywords = {commercial building, demand charge, Model predictive control (MPC), peak demand, time-of-use tarrif}, author = {Olivier Van Cutsem and Maher Kayal and David Blum and Marco Pritoni} } @article {31667, title = {Data fusion in predicting internal heat gains for office buildings through a deep learning approach}, journal = {Applied Energy}, volume = {240}, year = {2019}, month = {02/2019}, pages = {386 - 398}, abstract = {

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

}, keywords = {data fusion, deep learning, Internal heat gains, Miscellaneous electric loads, Occupant count, Predictive control}, issn = {03062619}, doi = {10.1016/j.apenergy.2019.02.066}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261919303630}, author = {Zhe Wang and Tianzhen Hong and Mary Ann Piette} } @article {31671, title = {Inferring occupant counts from Wi-Fi data in buildings through machine learning}, journal = {Building and Environment}, volume = {158}, year = {2019}, month = {05/2019}, pages = {281 - 294}, abstract = {

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

}, keywords = {Building control, Machine learning, Occupancy estimation, Occupant count, Random forest, Wi-Fi data}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.05.015}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0360132319303336}, author = {Zhe Wang and Tianzhen Hong and Mary Ann Piette and Marco Pritoni} } @article {31362, title = {Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems}, journal = {Applied Energy}, volume = {236}, year = {2019}, month = {02/2019}, pages = {410 - 425}, abstract = {

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

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

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

}, keywords = {deep learning, Long short term memory network, Occupant count, Plug loads, prediction, Predictive control}, issn = {03605442}, doi = {10.1016/j.energy.2019.05.138}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0360544219310205}, author = {Zhe Wang and Tianzhen Hong and Mary Ann Piette} } @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 {30484, title = {Human-building interaction at work: Findings from an interdisciplinary cross-country survey in Italy}, journal = {Building and Environment}, volume = {132}, year = {2018}, abstract = {

This study presents results from an interdisciplinary survey assessing contextual and behavioral factors driving occupants{\textquoteright} interaction with building and systems in offices located across three different Mediterranean climates in Turin (Northern), Perugia (Central), and Rende (Southern) Italy. The survey instrument is grounded in an interdisciplinary framework that bridges the gap between building physics and social science environments on the energy- and comfort-related human-building interaction in the workspace. Outcomes of the survey questionnaire provide insights into four key learning objectives: (1) individual occupant{\textquoteright}s motivational drivers regarding interaction with shared building environmental controls (such as adjustable thermostats, operable windows, blinds and shades, and artificial lighting), (2) group dynamics such as perceived social norms, attitudes, and intention to share controls, (3) occupant perception of the ease of use and knowledge of how to operate control systems, and (4) occupant-perceived comfort, satisfaction, and productivity. This study attempts to identify climatic, cultural, and socio-demographic influencing factors, as well as to establish the validity of the survey instrument and robustness of outcomes for future studies. Also, the paper aims at illustrating why and how social science insights can bring innovative knowledge into the adoption of building technologies in shared contexts, thus enhancing perceived environmental satisfaction and effectiveness of personal indoor climate control in office settings and impacting office workers{\textquoteright} productivity and reduced operational energy costs.

}, keywords = {Human-building interaction, indoor environmental comfort, interdisciplinary framework, occupant behavior, office buildings, questionnaire survey}, doi = {10.1016/j.buildenv.2018.01.039}, author = {Simona D{\textquoteright}Oca and Anna Laura Pisello and Marilena De Simone and Verena M. Barthelmes and Tianzhen Hong and Stefano P. Corgnati} } @article {30483, title = {Quantifying the benefits of a building retrofit using an integrated system approach: A case study}, journal = {Energy and Buildings}, volume = {159}, year = {2018}, abstract = {

Building retrofits provide a large opportunity to significantly reduce energy consumption in the buildings sector. Traditional building retrofits focus on equipment upgrades, often at the end of equipment life or failure, and result in replacement with marginally improved similar technology and limited energy savings. The Integrated System (IS) retrofit approach enables much greater energy savings by leveraging interactive effects between end use systems, enabling downsized or lower energy technologies. This paper presents a case study in Hawaii quantifying the benefits of an IS retrofit approach compared to two traditional retrofit approaches: a Standard Practice of upgrading equipment to meet minimum code requirements, and an Improved Practice of upgrading equipment to a higher efficiency. The IS approach showed an energy savings of 84\% over existing building energy use, much higher than the traditional approaches of 13\% and 33\%. The IS retrofit also demonstrated the greatest energy cost savings potential. While the degree of savings realized from the IS approach will vary by building and climate, these findings indicate that savings on the order of 50\% and greater are not possible without an IS approach. It is therefore recommended that the IS approach be universally adopted to achieve deep energy savings.

}, keywords = {Building retrofit, building simulation, Energy conservation measures, energy savings, integrated design, integrated system}, doi = {10.1016/j.enbuild.2017.10.090}, author = {Cynthia Regnier and Kaiyu Sun and Tianzhen Hong and Mary Ann Piette} } @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 {30026, title = {Automatic Generation and Simulation of Urban Building Energy Models Based on City Datasets for City-Scale Building Retrofit Analysis}, year = {2017}, abstract = {

Buildings in cities consume 30\% to 70\% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities{\textquoteright} building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23\%-38\% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Franciso due to the city{\textquoteright}s mild climate and minimal cooling and heating loads. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or technologies for the generation and simulation of building energy models, which helps overcome major technical barriers for city managers and their consultants to adopt UBEM.

}, keywords = {Building Energy Modeling, CityBES, Energy conservation measures, energyplus, Retrofit Analysis, Urban Scale}, author = {Yixing Chen and Tianzhen Hong and Mary Ann Piette} } @conference {29803, title = {Development of Automated Procedures to Generate Reference Building Models for ASHRAE Standard 90.1 and India{\textquoteright}s Building Energy Code and Implementation in OpenStudio}, booktitle = {Building Simulation 2017}, year = {2017}, month = {08/2017}, address = {San Francisco, CA}, abstract = {

This paper describes a software system for automatically generating a reference (baseline) building energy model from the proposed (as-designed) building energy model. This system is built using the OpenStudio Software Development Kit (SDK) and is designed to operate on building energy models in the OpenStudio file format.\ 

}, author = {Andrew Parker and Philip Haves and Subhash Jegi and Vishal Garg and Baptiste Ravache} } @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 {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 {60963, title = {Introduction to an occupant behavior motivation survey framework}, year = {2016}, abstract = {

An increasing body of research is underlying the need to foster energy behaviors and interaction with technology as a way to achieve energy savings in office buildings. However, engaging office users into more {\textquotedblleft}forgiving{\textquotedblright} comfort-adaptive behavior is not a trivial task, since neither consequences nor benefits for changing behavior have visible or tangible effects on them personally. Since the 70{\textquoteright}s, survey studies in the field of building science have been used to gain better understanding of multidisciplinary drivers of occupant behavior with respect to comfort and energy requirements in buildings. Rather than focusing on individual behaviors {\textendash} and influencing factors {\textendash} purpose of this survey research is to provide quantitative descriptions on the collective and social motivations within the complexity of different social groups in working environment, under different geographical context, culture and norms. The resultant questionnaire survey emerges as a combination of traditional and adaptive comfort theories, merged with social science theory. The questionnaire explores to what extent the occupant energy-related behavior in working spaces is driven by a motivational sphere influenced by i) comfort requirements, ii) habits, iii) intentions and iv) actual control of building systems. The key elements of the proposed occupant behavior motivational framework are grounded on the Driver Need Action System framework for energy-related behaviors in buildings. Goal of the study is to construct an additional layer of standardized knowledge to enrich the state-of-the-art on energy-related behavior in office buildings.

}, keywords = {DNAs framework, energy-related occupant behavior, motivation, office buildings, questionnaire survey}, author = {Simona D{\textquoteright}Oca and Stefano P. Corgnati and Anna Laura Pisello and Tianzhen Hong} } @conference {30147, title = {A Tale of Three District Energy Systems: Metrics and Future Opportunities}, booktitle = {2016 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2016}, month = {08/2017}, abstract = {

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

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

}, author = {Rebecca Zarin Pass and Michael Wetter and Mary Ann Piette} } @article {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 {60932, title = {Green, Clean, \& Mean: Pushing the Energy Envelope in Tech Industry Buildings}, year = {2015}, month = {05/2015}, publisher = {Lawrence Berkeley National Laboratory}, abstract = {

When it comes to innovation in energy and building performance, one can expect leading-edge activity from the technology sector. As front-line innovators in design, materials science, and information management, developing and operating high-performance buildings is a natural extension of their core business.

The energy choices made by technology companies have broad importance given their influence on society at large as well as the extent of their own energy footprint. Microsoft, for example, has approximately 250 facilities around the world (30 million square feet of floor area), with significant aggregate energy use of approximately 4 million kilowatt-hours per day.

There is a degree of existing documentation of efforts to design, build, and operate facilities in the technology sector. However, the material is fragmented and typically looks only at a single company, or discrete projects within a company.Yet, there is no single resource for corporate planners and decision makers that takes stock of the opportunities and documents sector-specific case studies in a structured manner. This report seeks to fill that gap, doing so through a combination of generalized technology assessments ({\textquotedblleft}Key Strategies{\textquotedblright}) and case studies ({\textquotedblleft}Flagship Projects{\textquotedblright}).

}, author = {Evan Mills and Jessica Granderson and Wanyu R. Chan and Richard C. Diamond and Philip Haves and Bruce Nordman and Paul A. Mathew and Mary Ann Piette and Gerald Robinson and Stephen E. Selkowitz} } @article {60352, title = {Modelica Buildings Library}, year = {2015}, author = {Michael Wetter and Wangda Zuo and Thierry Stephane Nouidui and Xiufeng Pang} } @article {60964, title = {A pattern-based automated approach to building energy model calibration}, year = {2015}, abstract = {

Building model calibration is critical in bringing simulated energy use closer to the actual consumption. This paper presents a novel, automated model calibration approach that uses logic linking parameter tuning with bias pattern recognition to overcome some of the disadvantages associated with traditional calibration processes. The pattern-based process contains four key steps: (1) running the original precalibrated energy model to obtain monthly simulated electricity and gas use; (2) establishing a pattern bias, either Universal or Seasonal Bias, by comparing load shape patterns of simulated and actual monthly energy use; (3) using programmed logic to select which parameter to tune first based on bias pattern, weather and input parameter interactions; and (4) automatically tuning the calibration parameters and checking the progress using pattern-fit criteria. The automated calibration algorithm was implemented in the Commercial Building Energy Saver, a web-based building energy retrofit analysis toolkit. The proof of success of the methodology was demonstrated using a case study of an office building located in San Francisco. The case study inputs included the monthly electricity bill, monthly gas bill, original building model and weather data with outputs resulting in a calibrated model that more closely matched that of the actual building energy use profile. The novelty of the developed calibration methodology lies in linking parameter tuning with the underlying logic associated with bias pattern identification. Although there are some limitations to this approach, the pattern-based automated calibration methodology can be universally adopted as an alternative to manual or hierarchical calibration approaches.

}, author = {Kaiyu Sun and Tianzhen Hong and Sarah C. Taylor-Lange and Mary Ann Piette} } @conference {59967, title = {A New Model to Simulate Energy Performance of VRF Systems}, year = {2014}, abstract = {

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

}, author = {Tianzhen Hong and Xiufeng Pang and Oren Schetrit and Liping Wang and Shinichi Kasahara and Yoshinori Yura and Ryohei Hinokuma} } @article {58863, title = {Review of Existing Energy Retrofit Tools}, year = {2014}, author = {Sang Hoon Lee and Tianzhen Hong and Mary Ann Piette} } @article {31985, title = {The Role of International Partnerships in Delivering Low- Energy Building Design: A Case Study of the Singapore Scientific Planning Process}, journal = {Sustainable Cities and Society}, volume = {14}, year = {2014}, month = {05/2014}, abstract = {

This paper explores the role of international partnerships to facilitate low-energy building
design, construction, and operations. We briefly discuss multiple collaboration models
and the levels of impact they support. We present a case study of one collaborative
partnership model, the Scientific Planning Support (SPS) team. Staff from the Lawrence
Berkeley National Laboratory, the Austrian Institute of Technology, and Nanyang
Technological University formed the SPS team to provide design assistance and process
support during the design phase of a low-energy building project. Specifically, the SPS
team worked on the Clean Tech Two project, a tenanted laboratory and office building
that seeks Green Mark Platinum, the highest green building certification in Singapore.
The SPS team hosted design charrettes, helped to develop design alternatives, and
provided suggestions on the design process in support of this aggressive energy target.
This paper describes these efforts and discusses how teams like the SPS team and other\ partnership schemes can be leveraged to achieve high performance, low-energy buildingsat an international scale.

}, doi = {10.1016/j.scs.2014.05.007}, author = {Kristen Parrish and Reshma Singh and Szu-Cheng Chien} } @article {3443, title = {Transforming BIM to BEM: Generation of Building Geometry for the NASA Ames Sustainability Base BIM}, year = {2013}, month = {01/2013}, author = {James O{\textquoteright}Donnell and Tobias Maile and Cody Rose and Natasa Mrazovic and Elmer Morrissey and Cynthia Regnier and Kristen Parrish and Vladimir Bazjanac} } @article {2591, title = {A framework for simulation-based real-time whole building performance assessment}, journal = {Building and Environment}, volume = {54}, year = {2012}, month = {08/2012}, pages = {100-108}, chapter = {100}, abstract = {

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

}, keywords = {building controls virtual test bed, building performance, energy modeling, energyplus, real-time building simulation}, issn = {0360-1323}, author = {Xiufeng Pang and Michael Wetter and Prajesh Bhattacharya and Philip Haves} } @article {3414, title = {Monitoring-based HVAC Commissioning of an Existing Office Building for Energy Efficiency}, year = {2012}, month = {10/2012}, abstract = {

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

}, keywords = {benchmarking, commissioning, energyplus, fault detection and diagnostics, functional testing, trend data}, author = {Shankar Earni and Spencer Woodworth and Xiufeng Pang and Jorge Hernandez-Maldonado and Rongxin Yin and Liping Wang and Steve E. Greenberg and John Fiegel and Alma Rubalcava} } @article {57517, title = {Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building}, journal = {Energy and Buildings}, volume = {53}, year = {2012}, month = {10/2012}, pages = {152 - 158}, keywords = {Building Operations, energyplus, Monte Carlo Analysis, Uncertainties}, issn = {03787788}, doi = {10.1016/j.enbuild.2012.06.017}, author = {Liping Wang and Paul A. Mathew and Xiufeng Pang} } @proceedings {3408, title = {Validation and Application of the Room Model of the Modelica Buildings Library}, journal = {Proc. of the 9th International Modelica Conference}, year = {2012}, month = {09/2012}, address = {Munich, Germany}, abstract = {

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

}, author = {Thierry Stephane Nouidui and Phalak, Kaustubh and Wangda Zuo and Michael Wetter} } @article {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}, journal = {Proc. of the 12th IBPSA Conference}, year = {2011}, month = {11/2011}, pages = {p. 294-301}, address = {Sydney, Australia}, author = {Thierry Stephane Nouidui and Michael Wetter and Zhengwei Li and Xiufeng Pang and Prajesh Bhattacharya and Philip Haves} } @conference {2672, title = {Modeling and simulation of HVAC faults in EnergyPlus}, booktitle = {Building Simulation 2011}, year = {2011}, month = {11/2011}, address = {Australia}, keywords = {advanced building software: energyplus, building simulation, energyplus, faults, fouling, modeling, sensor offset, simulation research group}, author = {Mangesh Basarkar and Philip Haves and Xiufeng Pang and Liping Wang and Tianzhen Hong} } @article {3179, title = {Modeling and simulation of HVAC Results in EnergyPlus}, year = {2011}, month = {11/2011}, author = {Mangesh Basarkar and Xiufeng Pang and Liping Wang and Tianzhen Hong} } @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} } @proceedings {2787, title = {Real-time Building Energy Simulation using EnergyPlus and the Building Controls Virtual Test Bed}, journal = {Proc. of the 12th IBPSA Conference}, year = {2011}, month = {11/2011}, pages = {p. 2890-2896}, address = {Sydney, Australia}, abstract = {

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

}, author = {Xiufeng Pang and Prajesh Bhattacharya and Zheng O{\textquoteright}Neill and Philip Haves and Michael Wetter and Trevor Bailey} } @proceedings {393, title = {Automated Continuous Commissioning of Commercial Buildings}, journal = {DoD SERDP-ESTCP Partners in Environmental Technology Technical Symposium and Workshop}, year = {2010}, month = {11/2010}, address = {Washington, D.C.}, author = {Trevor Bailey and Zheng O{\textquoteright}Neill and Madhusudana Shashanka and Prajesh Bhattacharya and Philip Haves and Xiufeng Pang} } @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} } @proceedings {243, title = {Systems Approach to Energy Efficient Building Operation: Case Studies and Lessons Learned in a University Campus}, journal = {2010 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2010}, publisher = {Omnipress}, address = {Asilomar, California, USA}, abstract = {

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

}, isbn = {0-918249-60-0}, author = {Satish Narayanan and Michael G. Apte and Philip Haves and Mary Ann Piette and John Elliott} } @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 {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} } @proceedings {58, title = {Standardization of thermo-fluid modeling in Modelica.Fluid 1.0}, journal = {Proc. of the 7th International Modelica Conference}, volume = {43}, year = {2009}, month = {09/2009}, publisher = {Link{\"o}ping University Electronic Press}, edition = {13}, address = {Como, Italy}, abstract = {

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

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

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

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

}, keywords = {modelica}, isbn = {978-91-7393-513-5}, doi = {10.3384/ecp0943}, url = {http://www.ep.liu.se/ecp_article/index.en.aspx?issue=043;article=13}, author = {R{\"u}diger Franke and Francesco Casella and Martin Otter and Katrin Proelss and Michael Sielemann and Michael Wetter} } @conference {2657, title = {Advanced Zone Simulation in EnergyPlus: Incorporation of Variable Properties and Phase Change Material (PCM) Capability}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Curtis O. Pedersen} } @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} } @conference {2655, title = {Energy Index Evaluation of Buildings in Function of the External Temperature}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Papa, Renata Pietra and Patricia Romeiro da Silva Jota and Assis, Eleonora} } @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 {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 {2813, title = {The Application of Building Energy Simulation and Calibration in Two High-Rise Commercial Buildings in Shanghai}, journal = {SimBuild 2006}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Yiqun Pan and Zhizhong Huang and Gang Wu and Chen Chen} } @article {379, title = {Brownian Motion Based Convective- Conductive Model for the Effective Thermal Conductivity of Nanofluids}, journal = {Journal of Heat Transfer}, volume = {128}, year = {2006}, pages = {588-595}, chapter = {588}, author = {Ravi S. Prasher and Prajesh Bhattacharya and Patrick E. Phelan} } @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 {3392, title = {Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Case Study in New York}, journal = {2006 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2006}, month = {08/2006}, address = {Pacific Grove, CA, USA}, author = {Sila Kiliccote and Mary Ann Piette and David S. Watson and Glenn D. Hughes} } @article {381, title = {Effect of Aggregation Kinetics on the Thermal Conductivity of Nanoscale Colloidal Solutions (Nanofluids)}, journal = {Nanoletters}, volume = {6}, year = {2006}, pages = {1529-1534}, chapter = {1529}, author = {Ravi S. Prasher and Prajesh Bhattacharya and Patrick E. Phelan} } @conference {382, title = {Effect of Coloidal Chemistry on the Thermal Conductivity of Nanofluids}, booktitle = {International Mechanical Engineering Congress \& Exposition}, year = {2006}, month = {11/2006}, address = {Chicago, IL}, author = {Ravi S. Prasher and Prajesh Bhattacharya and Patrick E. Phelan} } @proceedings {2803, title = {The Energy Performance of the Cold-Formed Steel-Frame and Wood-Frame Houses Developed for Thailand}, journal = {SimBuild 2006}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Prechaya Mahattanataw and Charunpat Puvanant and Darunee Mongkolsawat} } @article {383, title = {Enhanced Mass Transport in Nanofluids}, journal = {Nanoletters}, volume = {6}, year = {2006}, month = {03/2006}, pages = {419-423}, chapter = {419}, abstract = {

Thermal conductivity enhancement in nanofluids, which are liquids containing suspended nanoparticles, has been attributed to localized convection arising from the nanoparticles{\textquoteright} Brownian motion. Because convection and mass transfer are similar processes, the objective here is to visualize dye diffusion in nanofluids. It is observed that dye diffuses faster in nanofluids compared to that in water, with a peak enhancement at a nanoparticle volume fraction, φ, of 0.5\%. A possible change in the slope of thermal conductivity enhancement at that same φ signifies that convection becomes less important at higher φ. The enhanced mass transfer in nanofluids can be utilized to improve diffusion in microfluidic devices.

}, doi = {10.1021/nl0522532}, author = {S. Krishnamurthy and Prajesh Bhattacharya and Patrick E. Phelan and Ravi S. Prasher} } @article {71, title = {Precision control for generalized pattern search algorithms with adaptive precision function evaluations}, journal = {SIAM Journal on Optimization}, volume = {16}, year = {2006}, pages = {650-669
}, abstract = {

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

}, issn = {1052-6234}, doi = {10.1137/040605527}, author = {Elijah Polak and Michael Wetter} } @proceedings {2790, title = {Zero Energy Buildings: A Critical Look at the Definition}, journal = {2006 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2006}, month = {08/2006}, address = {Pacific Grove, CA, USA}, author = {Paul A. Torcellini and Shanti Pless and Michael Deru and Drury B. Crawley} } @article {73, title = {Building design optimization using a convergent pattern search algorithm with adaptive precision simulations}, journal = {Energy and Buildings}, volume = {37}, year = {2005}, pages = {603-612}, abstract = {

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

}, doi = {10.1016/j.enbuild.2004.09.005}, author = {Michael Wetter and Elijah Polak} } @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} } @proceedings {397, title = {Computational Analysis of the Colloidal Stability of Nanofluids}, journal = {International Mechanical Engineering Congress \& Exposition}, year = {2005}, month = {11/2005}, address = {Orlando, FL}, author = {Prajesh Bhattacharya and Patrick E. Phelan and Ravi S. Prasher} } @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 {388, title = {Effect of Particle Material on the Static Thermal Conductivity of Nanofluids}, booktitle = {Heat Transfer Conference}, year = {2005}, month = {07/2005}, address = {San Francisco, CA}, author = {P. Vijayan and Prajesh Bhattacharya and S. Nara and W. Lai and Patrick E. Phelan and Ravi S. Prasher and David W. Song and J. Wang} } @article {277, title = {Effects of double glazed fa{\c c}ade on energy consumption, thermal comfort and condensation for a typical office building in Singapore}, journal = {Energy and Buildings}, volume = {37}, year = {2005}, month = {06/2005}, author = {Nyuk Hien Wong and Liping Wang and Aida Noplie Chandra and Anupama Rana Pandey and Xiaolin Wei} } @conference {385, title = {Experimental Determination of the Effect of Varying Base Fluid and Temperature on the Static Thermal Conductivity of Nanofluids}, booktitle = {ASME International Mechanical Engineering Congress and Exposition, November 5-11, 2005}, year = {2005}, month = {11/2005}, publisher = {ASME}, organization = {ASME}, address = {Orlando, FL}, abstract = {

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

}, isbn = {0-7918-4221-5}, doi = {10.1115/IMECE2005-81494}, author = {S. Nara and Prajesh Bhattacharya and P. Vijayan and W. Lai and W. Rosenthal and Patrick E. Phelan and Ravi S. Prasher and David W. Song and Jinlin Wang} } @article {387, title = {Thermal Conductivity of Nanoscale Colloidal Solutions (Nanofluids)}, journal = {Physical Review Letters}, volume = {94}, year = {2005}, chapter = {025901-1}, author = {Ravi S. Prasher and Prajesh Bhattacharya and Patrick E. Phelan} } @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 {259, title = {ANN Modeling and Self-tuning Control of the Oil Field Heating Furnace}, journal = {Computer Measurement and Control (Chinese)}, volume = {12}, year = {2004}, pages = {338-240}, author = {Yongcheng Jiang and Xiufeng Pang} } @article {386, title = {Brownian Dynamics Simulation to Determine the Effective Thermal Conductivity of Nanofluids}, journal = {Journal of Applied Physics}, volume = {95}, year = {2004}, month = {06/2004}, pages = {6492{\textendash}6494}, chapter = {6492}, abstract = {

A nanofluid is a fluid containing suspended solid particles, with sizes on the order of nanometers. Normally, nanofluids have higher thermal conductivities than their base fluids. Therefore, it is of interest to predict the effective thermal conductivity of such a nanofluid under different conditions, especially since only limited experimental data are available. We have developed a technique to compute the effective thermal conductivity of a nanofluid using Brownian dynamics simulation, which has the advantage of being computationally less expensive than molecular dynamics, and have coupled that with the equilibrium Green-Kubo method. By comparing the results of our calculation with the available experimental data, we show that our technique predicts the thermal conductivity of nanofluids to a good level of accuracy.

}, keywords = {complex fluids, Disperse systems, Thermal conduction in nonmetallic liquids}, doi = {10.1063/1.1736319}, author = {Prajesh Bhattacharya and Saha, S.K. and Ajay K. Yadav and Patrick E. Phelan and Ravi S. Prasher} } @article {3398, title = {Building Design Optimization Using a Convergent Pattern Search Algorithm with Adaptive Precision Simulations}, journal = {Energy and Buildings}, volume = {37}, year = {2004}, month = {09/2004}, pages = {603-612}, chapter = {603}, author = {Michael Wetter and Elijah Polak} } @article {52, title = {BuildOpt 1.0.1 validation}, year = {2004}, issn = {LBNL-54658}, author = {Michael Wetter and Elijah Polak and Van P. Carey} } @article {74, title = {A convergent optimization method using pattern search algorithms with adaptive precision simulation}, journal = {Building Services Engineering Research and Technology}, volume = {25}, year = {2004}, month = {11/2004}, pages = {327-338}, abstract = {

Thermal building simulation programs, such as EnergyPlus, compute numerical approximations to solutions of systems of differential algebraic equations. We show that the exact solutions of these systems are usually smooth in the building design parameters, but that the numerical approximations are usually discontinuous due to adaptive solvers and finite precision computations. If such approximate solutions are used in conjunction with optimization algorithms that depend on smoothness of the cost function, one needs to compute high precision solutions, which can be prohibitively expensive if used for all iterations. For such situations, we have developed an adaptive simulation{\textendash}precision control algorithm that can be used in conjunction with a family of derivative free optimization algorithms. We present the main ingredients of the composite algorithms, we prove that the resulting composite algorithms construct sequences with stationary accumulation points, and we show by numerical experiments that using coarse approximations in the early iterations can significantly reduce computation time.

}, doi = {10.1191/0143624404bt097oa }, author = {Michael Wetter and Elijah Polak} } @conference {389, title = {Determining the Effective Viscosity of a Nanofluid Using Brownian Dynamics Simulation}, booktitle = {1st International Symposium on Micro \& Nano Technology}, year = {2004}, month = {03/2004}, address = {Honolulu, HI}, author = {Prajesh Bhattacharya and Patrick E. Phelan and Ravi S. Prasher} } @proceedings {2823, title = {EnergyPlus: An Update}, journal = {SimBuild 2004, Building Sustainability and Performance Through Simulation}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Drury B. Crawley and Linda K. Lawrie and Curtis O. Pedersen and Frederick C. Winkelmann and Michael J. Witte and Richard K. Strand and Richard J. Liesen and Walter F. Buhl and Yu Joe Huang and Robert H. Henninger and Jason Glazer and Daniel E. Fisher and Don B. Shirley and Brent T. Griffith and Peter G. Ellis and Lixing Gu} } @conference {390, title = {Evaluation of the Temperature Oscillation Technique to Calculate Thermal Conductivity of Water and Systematic Measurement of the Thermal Conductivity of Aluminum Oxide {\textendash} Water Nanofluiids}, booktitle = {International Mechanical Engineering Congress \& Exposition,}, year = {2004}, month = {11/2004}, address = {Anaheim, CA}, author = {Prajesh Bhattacharya and P. Vijayan and Tang, T. and S. Nara and Patrick E. Phelan and Ravi S. Prasher and J. Wang and David W. Song} } @proceedings {398, title = {Numerical Tools For Particle- Fluid Interactions}, journal = {Pulmonary Research Forum: American Lung Association of Arizona \& New Mexico}, year = {2004}, month = {02/2004}, author = {R. Calhoun and Patrick E. Phelan and Ajay K. Yadav and Prajesh Bhattacharya} } @conference {56064, title = {Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building}, booktitle = {2004 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2004}, month = {08/2004}, address = {Pacific Grove, CA}, abstract = {

The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft2 office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100\% (1 - 2.3 W/ft2) during normal peak hours from 2 - 5 pm, without causing any thermal comfort complaints. The effects on the demand from 2 - 5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

}, keywords = {demand shifting (pre-cooling)}, author = {Peng Xu and Philip Haves and Mary Ann Piette and James E. Braun} } @article {260, title = {Computer Measurement and Automation System for Gas-fired Heating Furnace}, journal = {Journal of Harbin Institute of Technology (Chinese)}, volume = {35}, year = {2003}, pages = {374-378}, author = {Xiufeng Pang and Yongcheng Jiang and Yan-shu Miao and Jun Xiong} } @proceedings {48, title = {A convergent optimization method using pattern search algorithms with adaptive precision simulation}, journal = {Proceedings of the 8th IBPSA Conference}, volume = {III}, year = {2003}, pages = {1393-1400}, address = {Eindhoven, Netherlands}, abstract = {

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

}, keywords = {coordinate search, direct search, genetic algorithm, hooke{\textendash}jeeves, optimization, particle swarm optimization}, author = {Michael Wetter and Elijah Polak}, editor = {Godfried Augenbroe and Jan Hensen} } @conference {391, title = {Determining the Effective Thermal Conductivity of a Nanofluid Using Brownian Dynamics Simulation}, booktitle = {National Heat Transfer Conference}, year = {2003}, month = {07/2003}, address = {Las Vegas, NV}, author = {Prajesh Bhattacharya and Saha, S.K. and Ajay K. Yadav and Patrick E. Phelan and Ravi S. Prasher} } @article {2586, title = {Research of ANN Internal Model Self-tuning Control Applied in Combustion Process Control of Heating Furnace in Oil Field}, journal = {Journal of Central South University, Technology}, volume = {34}, year = {2003}, pages = {108-112}, author = {Yongcheng Jiang and Xiufeng Pang and Fu,Shaobo} } @proceedings {399, title = {Modeling the Behavior of F1-ATPase Biomolecular Motors Using Brownian Dynamics Simulation}, journal = {BioDevice Interface Science and Technology Workshop}, year = {2002}, month = {09/2002}, address = {Scottsdale, AZ}, author = {Prajesh Bhattacharya and Patrick E. Phelan} } @conference {392, title = {Understanding the Behavior of an F1-ATPase Biomolecular Motor Using Brownian Dynamics Simulation}, booktitle = {US-Japan Nanotherm Seminar: Nanoscale Thermal Science and Engineering}, year = {2002}, month = {06/2002}, address = {Berkeley, CA}, author = {Prajesh Bhattacharya and Patrick E. Phelan} } @article {308, title = {Analysis of an Information Monitoring and Diagnostic System to Improve Building Operations}, journal = {Energy and Buildings}, volume = {33}, year = {2001}, month = {10/2001}, pages = {783-792}, chapter = {783}, abstract = {

This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype information monitoring and diagnostic system (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software including a web-based remote access system, that can be used to identify control problems and equipment faults. The information system allowed the operators to make more effective use of the building control system and freeing up time to take care of other tenant needs. They report observing significant improvements in building comfort, potentially improving tenant health and productivity. The reduction in the labor costs to operate the building is about US$ 20,000 per year, which alone could pay for the information system in about 5 years. A control system retrofit based on findings from the information system is expected to reduce energy use by 20\% over the next year, worth over US$ 30,000 per year in energy cost savings. The operators are recommending that similar technology be adopted in other buildings.

}, keywords = {building control system, building operation, imds}, doi = {10.1016/S0378-7788(01)00068-8}, author = {Mary Ann Piette and Satkartar T. Khalsa and Philip Haves} } @proceedings {306, title = {Demand Relief and Weather Sensitivity in Large California Commercial Buildings}, journal = {International Conference for Enhancing Building Operations}, year = {2001}, month = {07/2001}, address = {Austin, TX}, abstract = {

A great deal of research has examined the weather sensitivity of energy consumption in commercial buildings; however, the recent power crisis in California has given greater importance to peak demand. Several new loadshedding programs have been implemented or are under consideration. Historically, the target customers have been large industrial users who can reduce the equivalent load of several large office buildings. While the individual load reduction from an individual office building may be less significant, there is ample opportunity for load reduction in this area. The load reduction programs and incentives for industrial customers may not be suitable for commercial building owners. In particular, industrial customers are likely to have little variation in load from day to day. Thus a robust baseline accounting for weather variability is required to provide building owners with realistic targets that will encourage them to participate in load shedding programs.

}, author = {Satkartar Kinney and Mary Ann Piette and Lixing Gu and Philip Haves} } @proceedings {311, title = {Use of an Information Monitoring and Diagnostic System for Commissioning and Ongoing Operations}, journal = {8th National Conference on Building Commissioning PECI}, year = {2000}, month = {05/2000}, abstract = {This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype Information Monitoring and Diagnostic System (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software, including a web-based remote access system that can be used to identify control problems and equipment faults. The IMDS allowed the operators to make more effective use of the control system, freeing up time to take care of other tenant needs. The operators report observing significant improvements in building comfort, potentially improving tenant health and productivity. Reduction in hours to operate the building are worth about $20,000 per year, which alone could pay for the IMDS in about five years. A control system retrofit based on findings from the IMDS is expected to reduce energy use by 20 percent over the next year, worth over $30,000 per year in energy cost savings. The operators recommend that similar technology be adopted in other buildings. While the current IMDS is oriented toward manual, human-based diagnostic techniques, we also evaluated automated diagnostic techniques. Strategies for utilizing results from this demonstration to influence commercial building performance monitoring for commissioning and operations will be discussed. Background}, url = {http://imds.lbl.gov/pubs/paper383.pdf}, author = {Mary Ann Piette and Satkartar T. Khalsa and Philip Haves} } @article {384, title = {Nanofluids for Heat Transfer Applications}, journal = {Annual Review of Heat Transfer}, volume = {14}, year = {1995}, pages = {255-275}, chapter = {255}, author = {Patrick E. Phelan and Ravi S. Prasher and Prajesh Bhattacharya} } @article {334, title = {Investigation of the Reliability of Building Emulators for Testing Energy Management and Control Systems}, journal = {ASHRAE Transactions}, volume = {100}, year = {1994}, author = {Henk C. Peitsman and Shengwei Wang and Philip Haves and Satu H. K{\"a}rki and Cheol P. Park} } @conference {55942, title = {Implications of Office Building Thermal Mass and Multi-day Temperature Profiles for Cooling Strategies}, booktitle = {ASME/AIChe National Heat Transfer Conference}, year = {1985}, month = {08/1985}, address = {Denver, CO}, abstract = {

This paper describes a study of the cooling energy requirements that result from thermal storage in building mass, and suggests methods for predicting and controlling its energy cost implications. The study relies on computer simulations of energy use for a large office building prototype in El Paso, TX using the DOE-2 building energy analysis program. Increased Monday cooling energy requirements resulting from the weekend shut-down of HVAC systems are documented. Predictors of energy use and peak demands, which account for thermal storage in building mass, are described. Load-shifting, sub-cooling and pre-cooling equipment operating strategies are evaluated with explicit reference to utility rate schedules.

}, keywords = {commercial buildings, cooling energy, energy conservation, peak demand, thermal mass}, author = {Joseph H. Eto and Gay Powell} }