@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 {31312, title = {Development of city buildings dataset for urban building energy modeling}, journal = {Energy and Buildings}, volume = {183}, year = {2019}, month = {11/2018}, pages = {252 - 265}, abstract = {

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

}, keywords = {City building dataset, CityGML, Data mapping, Data standards, Urban Building Energy Modeling}, issn = {03787788}, doi = {10.1016/j.enbuild.2018.11.008}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0378778818316852https://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/plain}, author = {Yixing Chen and Tianzhen Hong and Xuan Luo and Barry Hooper} } @article {30028, title = {Data Analytics and Optimization of an Ice-Based Energy Storage System for Commercial Buildings}, year = {2017}, abstract = {

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

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

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

}, doi = {10.1016/j.enconman.2017.08.072}, author = {Brahm van der Heijde and Marcus Fuchs and Carles Ribas Tugores and Gerald Schweiger and Kevin Sartor and Daniele Basciotti and Dirk Muller and Christoph Nytsch-Geusen and Michael Wetter and Lieve Helsen} } @article {59960, title = {Data Analysis and Stochastic Modeling of Lighting Energy Use in Large Office Buildings in China}, journal = {Energy and Buildings}, volume = {86}, year = {2015}, month = {01/2015}, pages = {275-287}, abstract = {

Lighting consumes about 20\% to 40\% of the total electricity use in large office buildings in China. Commonly in building simulations, static time schedules for typical weekdays, weekends and holidays are assumed to represent the dynamics of lighting energy use in buildings. This approach does not address the stochastic nature of lighting energy use, which can be influenced by occupant behavior in buildings. This study analyzes the main characteristics of lighting energy use over various timescales, based on the statistical analysis of measured lighting energy use data from 15 large office buildings in Beijing and Hong Kong. It was found that in these large office buildings, the 24-hourly variation in lighting energy use was mainly driven by the schedules of the building occupants. Outdoor illuminance levels had little impact on lighting energy use due to the lack of automatic daylighting controls (an effective retrofit measure to reduce lighting energy use) and the relatively small perimeter area exposed to natural daylight. A stochastic lighting energy use model for large office buildings was further developed to represent diverse occupant activities, at six different time periods throughout a day, and also the annual distribution of lighting power across these periods. The model was verified using measured lighting energy use from the 15 buildings. The developed stochastic lighting model can generate more accurate lighting schedules for use in building energy simulations, improving the simulation accuracy of lighting energy use in real buildings.

}, keywords = {building simulation, energy use, Lighting modeling, occupant behavior, office buildings, Poisson distribution, stochastic modeling}, doi = {10.1016/j.enbuild.2014.09.071}, author = {Xin Zhou and Da Yan and Tianzhen Hong and Xiaoxin Ren} } @article {59958, title = {Data Mining of Space Heating System Performance in Affordable Housing}, journal = {Building and Environment}, volume = {89}, year = {2015}, month = {07/2015}, pages = {1-13}, abstract = {

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems in terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. The results from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.

}, keywords = {affordable housing, building simulation, clustering, data mining, decision tree, occupant behavior, space heating}, doi = {10.1016/j.buildenv.2015.02.009}, author = {Xiaoxin Ren and Da Yan and Tianzhen Hong} } @article {59988, title = {A Data-mining Approach to Discover Patterns of Window Opening and Closing Behavior in Offices}, year = {2015}, abstract = {

Understanding the relationship between occupant behaviors and building energy consumption is one of the most effective ways to bridge the gap between predicted and actual energy consumption in buildings. However effective methodologies to remove the impact of other variables on building energy consumption and isolate the leverage of the human factor precisely are still poorly investigated. Moreover, the effectiveness of statistical and data mining approaches in finding meaningful correlations in data is largely undiscussed in literature. This study develops a framework combining statistical analysis with two data-mining techniques, cluster analysis and association rules mining, to identify valid window operational patterns in measured data. Analyses are performed on a data set with measured indoor and outdoor physical parameters and human interaction with operable windows in 16 offices. Logistic regression was first used to identify factors influencing window opening and closing behavior. Clustering procedures were employed to obtain distinct behavioral patterns, including motivational, opening duration, interactivity and window position patterns. Finally the clustered patterns constituted a base for association rules segmenting the window opening behaviors into two archetypal office user profiles for which different natural ventilation strategies as well as robust building design recommendations that may be appropriate. Moreover, discerned working user profiles represent more accurate input to building energy modeling programs, to investigate the impacts of typical window opening behavior scenarios on energy use, thermal comfort and productivity in office buildings

}, author = {Simona D{\textquoteright}Oca and Tianzhen Hong} } @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 {60350, title = {Design choices for thermofluid flow components and systems that are exported as Functional Mockup Units}, year = {2015}, abstract = {

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

}, author = {Michael Wetter and Marcus Fuchs and Thierry Stephane Nouidui} } @article {60960, title = {Development and validation of a new variable refrigerant flow systemmodel in EnergyPlus}, journal = {Energy and Buildings}, volume = {117}, year = {2015}, month = {9/2015}, chapter = {399}, abstract = {

Variable refrigerant flow (VRF) systems vary the refrigerant flow to meet the dynamic zone thermalloads, leading to more efficient operations than other system types. This paper introduces a new modelthat simulates the energy performance of VRF systems in the heat pump (HP) operation mode. Com-pared with the current VRF-HP models implemented in EnergyPlus, the new VRF system model has morecomponent models based on physics and thus has significant innovations in: (1) enabling advanced con-trols, including variable evaporating and condensing temperatures in the indoor and outdoor units, andvariable fan speeds based on the temperature and zone load in the indoor units, (2) adding a detailedrefrigerant pipe heat loss calculation using refrigerant flow rate, operational conditions, pipe length, andpipe insulation materials, (3) improving accuracy of simulation especially in partial load conditions, and(4) improving the usability of the model by significantly reducing the number of user input performancecurves. The VRF-HP model is implemented in EnergyPlus and validated with measured data from fieldtests. Results show that the new VRF-HP model provides more accurate estimate of the VRF-HP systemperformance, which is key to determining code compliance credits as well as utilities incentive for VRFtechnologies.

}, keywords = {building simulation, energy modeling, energyplus, Heat pump, model validation, Variable refrigerant flow}, doi = {10.1016/j.enbuild.2015.09.023}, author = {Tianzhen Hong and Kaiyu Sun and Rongpeng Zhang and Ryohei Hinokuma and Shinichi Kasahara and Yoshinori Yura} } @article {57756, title = {Data and Analytics to Inform Energy Retrofit of High Performance Buildings}, journal = {Applied Energy}, volume = {126}, year = {2014}, month = {08/2014}, pages = {90-106}, publisher = {Elsevier}, abstract = {

Buildings consume more than one-third of the world{\textquoteright}s primary energy. Reducing energy use in buildings with energy efficient technologies is feasible and also driven by energy policies such as energy benchmarking, disclosure, rating, and labeling in both the developed and developing countries. Current energy retrofits focus on the existing building stocks, especially older buildings, but the growing number of new high performance buildings built around the world raises a question that how these buildings perform and whether there are retrofit opportunities to further reduce their energy use. This is a new and unique problem for the building industry. Traditional energy audit or analysis methods are inadequate to look deep into the energy use of the high performance buildings. This study aims to tackle this problem with a new holistic approach powered by building performance data and analytics. First, three types of measured data are introduced, including the time series energy use, building systems operating conditions, and indoor and outdoor environmental parameters. An energy data model based on the ISO Standard 12655 is used to represent the energy use in buildings in a three-level hierarchy. Secondly, a suite of analytics were proposed to analyze energy use and to identify retrofit measures for high performance buildings. The data-driven analytics are based on monitored data at short time intervals, and cover three levels of analysis {\textendash} energy profiling, benchmarking and diagnostics. Thirdly, the analytics were applied to a high performance building in California to analyze its energy use and identify retrofit opportunities, including: (1) analyzing patterns of major energy end-use categories at various time scales, (2) benchmarking the whole building total energy use as well as major end-uses against its peers, (3) benchmarking the power usage effectiveness for the data center, which is the largest electricity consumer in this building, and (4) diagnosing HVAC equipment using detailed time-series operating data. Finally, a few energy efficiency measures were identified for retrofit, and their energy savings were estimated to be 20\% of the whole-building electricity consumption. Based on the analyses, the building manager took a few steps to improve the operation of fans, chillers, and data centers, which will lead to actual energy savings. This study demonstrated that there are energy retrofit opportunities for high performance buildings and detailed measured building performance data and analytics can help identify and estimate energy savings and to inform the decision making during the retrofit process. Challenges of data collection and analytics were also discussed to shape best practice of retrofitting high performance buildings.

}, keywords = {Analytics, data model, Energy benchmarking, energy use, High performance buildings, retrofit}, doi = {10.1016/j.apenergy.2014.03.052}, author = {Tianzhen Hong and Le Yang and David Hill and Wei Feng} } @article {60154, title = {Development of Diagnostic and Measurement and Verification Tools for Commercial Buildings}, year = {2014}, month = {09/2014}, institution = {California Energy Commission}, abstract = {

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

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

Project 1 consisted of administrative tasks related to the project.

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

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

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

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

}, keywords = {application programming interface, fault detection and diagnosis, M\&V, Measurement and verification, Universal Translator}, author = {Philip Haves and Craig P. Wray and David A. Jump and Daniel Veronica and Christopher Farley} } @article {56249, title = {Data Analysis and Modeling of Lighting Energy Use in Large Office Buildings}, year = {2013}, abstract = {

Lighting consumes about 20 to 40\% of total electricity use in large office buildings in the U.S. and China. In order to develop better lighting simulation models it is crucial to understand the characteristics of lighting energy use. This paper analyzes the main characteristics of lighting energy use over various time scales, based on the statistical analysis of measured lighting energy use of 17 large office buildings in Beijing and Hong Kong. It was found that the daily 24-hour variations of lighting energy use were mainly driven by the schedule of the building occupants. Outdoor illumination levels have little impact on lighting energy use in large office buildings due to the lack of automatic daylighting controls and relatively small perimeter areas. A stochastic lighting energy use model was developed based on different occupant activities during six time periods throughout a day, and the annual distribution of lighting power across those periods. The model was verified using measured lighting energy use of one selected building. This study demonstrates how statistical analysis and stochastic modeling can be applied to lighting energy use. The developed lighting model can be adopted by building energy modeling programs to improve the simulation accuracy of lighting energy use.

}, keywords = {building simulation, energy use, lighting, modeling, occupant behavior, office buildings, Poisson distribution}, author = {Xin Zhou and Da Yan and Xiaoxin Ren and Tianzhen Hong} } @article {56245, title = {A Detailed Loads Comparison of Three Building Energy Modeling Programs: EnergyPlus, DeST and DOE-2.1E}, journal = {Building Simulation}, volume = {6}, year = {2013}, month = {09/2013}, pages = {323-335}, publisher = {Tsinghua University Press}, chapter = {323}, abstract = {

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

}, keywords = {building energy modeling program, building thermal loads, comparison, dest, DOE-2.1E, energyplus}, issn = {Print: 1996-3599; Online 1996-8744}, doi = {10.1007/s12273-013-0126-7}, author = {Dandan Zhu and Tianzhen Hong and Da Yan and Chuang Wang} } @conference {2635, title = {Data Enviroments and Processing in Sem-Automated Simulation with EnergyPlus}, booktitle = {CIB W078-W102}, year = {2011}, address = {Sophia Antipolis, France}, author = {Vladimir Bazjanac and Tobias Maile and James O{\textquoteright}Donnell and Cody Rose and Natasa Mrazovic} } @conference {2633, title = {Development of a user interface for the EnergyPlus whole building energy simulation program}, booktitle = {IBPSA Building Simulation 2011}, year = {2011}, month = {11/2011}, address = {Sydney, Australia}, author = {Richard See and Philip Haves and Pramod Sreekanathan and Mangesh Basarkar and James O{\textquoteright}Donnell and Kevin Settlemyre} } @conference {244, title = {Development and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage}, booktitle = {2010 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2010}, publisher = {Omnipress}, organization = {Omnipress}, address = {Asilomar, California, USA}, abstract = {

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

}, issn = {0-918249-60-0}, author = {Brian E. Coffey and Philip Haves and Michael Wetter and Brandon Hencey and Francesco Borrelli and Yudong Ma and Sorin Bengea} } @conference {224, title = {Development of an isothermal 2D zonal air volume model with impulse conservation}, booktitle = {Clima 2010, 10th Rehva World Congress "Sustainable Energy Use in Buildings"}, year = {2010}, address = {Antalya, Turkey}, abstract = {

This paper presents a new approach to model air flows with a zonal model. The aim of zonal models is to perform quick simulations of the air distribution in rooms. Therefore an air volume is subdivided into several discrete zones, typically 10 to 100. The zones are connected with flow elements computing the amount of air exchanged between them. In terms of complexity and needed computational time zonal models are a compromise between CFD calculations and the approximation of perfect mixing. In our approach the air flow velocity is used as property of the zones. Thus the distinction between normal zones and jet or plume influenced zones becomes obsolete. The model is implemented in the object oriented and equation based language Modelica. A drawback of the new formulation is that the calculated flow pattern depends on the discretization. Nevertheless, the results show that the new zonal model performs well and is a useful extension to existing models.

}, author = {Norrefeldt Victor and Thierry Stephane Nouidui and Gunnar Gruen} } @conference {2641, title = {Design of Underlying Network Infrastructure of Smart Buildings}, booktitle = {2008 IET 4th International Conference on Intelligent Environments}, year = {2008}, month = {07/2008}, address = {Seattle, WA}, abstract = {

Wireless Building Management Systems (BMS) are an attractive option when it comes to building retrofitting due to the cost constraints introduced by wired systems. A crucial part of the wireless BMS is the initial planning stage, this process can be impossible for a designer to undertake, therefore highlighting the requirement for a software design tool to aid in this process.

}, keywords = {design, optimisation, Wireless BMS}, isbn = {978-0-86341-894-5 }, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4629790}, author = {Alan McGibney and Martin Klepal and James O{\textquoteright}Donnell} } @conference {283, title = {Discussion of strategies for UK zero energy building design}, booktitle = {2nd PALENC conference and 28th AIVC conference, 27-29 September}, year = {2007}, month = {09/2007}, author = {Liping Wang and Julie Gwilliam} } @conference {416, title = {Dehumidification Enhancement of Direct Expansion Systems through Component Augmentation of the Cooling Coil}, booktitle = {Fifteenth Symposium on Improving Building Systems in Hot and Humid Climates, July 24-26, 2006}, year = {2006}, address = {Orlando, FL}, abstract = {

Diverse air conditioning products with enhanced dehumidification features are being introduced to meet the increased moisture laden ventilation air requirements of ASHRAE Standard 62 in humid climates. In this evaluation, state point performance spreadsheet models for single path, mixed air packaged systems compare a conventional "off the shelf" direct expansion (DX) cooling system and its performance to systems that augment the DX coil with enhanced dehumidification components, such as heat exchangers and desiccant dehumidifiers. Using common performance metrics for comparisons at ARI rating conditions, these alternative systems define a best practice for enhanced dehumidification performance. The state point performance spreadsheet models combine available algorithms from the EnergyPlus{\texttrademark} simulation program for DX coils and heat exchangers with newly developed algorithms for desiccant dehumidifiers. All the models and their algorithms are applied in EnergyPlus{\texttrademark} for simulations of annual system cooling performance, including sensible and latent loads met, energy consumed, and humidity levels maintained, in select building types and climatic locations. Per this EnergyPlus{\texttrademark} analysis, these enhanced dehumidification systems present challenging decision-making tradeoffs between humidity control improvements over conventional DX systems, condensing (compressor) unit energy consumption reductions versus DX cool and reheat approaches, and fan energy use increases due to the additional component pressure drops.

}, author = {Douglas Kosar and Don Shirey and Mangesh Basarkar and Muthasamy Swami and Richard Raustad} } @proceedings {268, title = {Development of a Model Specification for Performance Monitoring Systems for Commercial Buildings}, journal = {2006 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2006}, month = {08/2006}, address = {Asilomar, California, USA}, abstract = {

The paper describes the development of a model specification for performance monitoring systems for commercial buildings. The specification focuses on four key aspects of performance monitoring: performance metrics measurement system requirements data acquisition and archiving data visualization and reporting The aim is to assist building owners in specifying the extensions to their control systems that are required to provide building operators with the information needed to operate their buildings more efficiently and to provide automated diagnostic tools with the information required to detect and diagnose faults and problems that degrade energy performance. The paper reviews the potential benefits of performance monitoring, describes the specification guide and discusses briefly the ways in which it could be implemented. A prototype advanced visualization tool is also described, along with its application to performance monitoring. The paper concludes with a description of the ways in which the specification and the visualization tool are being disseminated and deployed.

}, url = {http://www.aceee.org/proceedings-paper/ss06/panel03/paper10}, author = {Philip Haves and Robert J. Hitchcock and Kenneth L. Gillespie and Martha Brook and Christine Shockman and Joseph J Deringer and Kristopher L. Kinney} } @proceedings {3391, title = {Development of a Model Specification for Performance Monitoring Systems for Commercial Buildings}, journal = {2006 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2006}, month = {08/2006}, address = {Pacific Grove, CA, USA}, author = {Philip Haves and Robert J. Hitchcock and Kenneth L. Gillespie and Martha Brook and Christine Shockman and Joseph J Deringer and Kristopher L. Kinney} } @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} } @conference {2665, title = {Design of the Natural Ventilation System for the New San Diego Children{\textquoteright}s Museum}, booktitle = {IBPSA Building Simulation 2005}, year = {2005}, month = {08/2005}, address = {Montreal, Canada}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Martha Brook} } @article {280, title = {Design and Testing of a Control Strategy for a Large Naturally Ventilated Office Building}, journal = {Building Services Engineering Research \& Technology}, volume = {25}, year = {2004}, pages = {223-239}, abstract = {The design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. Each floor is designed to be cross-ventilated, through upper windows that are controlled by the building management system. Users have control over lower level windows, which can be as much as 50\% of the total openable area. There are significant differences in the performance and the control of the windward and leeward sides of the building, and separate monitoring and control strategies are determined for each side. The performance and control of the building has been designed and tested using a modified version of EnergyPlus. Results from studies with EnergyPlus and computational fluid dynamics are used in designing the control strategy. Wind-driven cross-ventilation produces a main jet through the upper openings of the building, across the ceiling from the windward to the leeward side. Below this jet, the occupied regions are subject to a recirculating airflow. Results show that temperatures within the building are predicted to be satisfactory, provided a suitable control strategy is implemented that uses night cooling in periods of hot weather. The control strategy has 10 window opening modes. EnergyPlus was extended to simulate the effects of these modes, and to assess the effects of different forms of user behaviour. The results show how user behaviour can significantly influence the building performance.}, doi = {10.1191/0143624404bt107oa}, url = {http://bse.sagepub.com/content/25/3/223}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Philip Haves} } @article {11714, title = {Design and Testing of a Control Strategy for a Large Naturally Ventilated Office Building}, journal = {Building Services Engineering Research \& Technology}, volume = {25}, number = {3}, year = {2004}, pages = {211-221}, abstract = {

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

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

}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Philip Haves} } @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} } @article {2588, title = {Development of a Thermal Energy Storage Model for EnergyPlus}, journal = {Energy and Buildings}, volume = {36}, year = {2004}, month = {2004}, pages = {807-814}, chapter = {807}, keywords = {energyplus, thermal energy storage (tes) system}, author = {Pyeongchan Ihm and Moncef Krarti and Gregor P. Henze} } @proceedings {2820, title = {Development of Trade-Off Equations for EnergyStar Windows}, journal = {SimBuild 2004, Building Sustainability and Performance Through Simulation}, year = {2004}, month = {08/2004}, address = {Boulder, Colorado, USA}, author = {Yu Joe Huang and Robin Mitchell and Stephen E. Selkowitz} } @proceedings {294, title = {Design and Testing of a Control Strategy for a Large Naturally Ventilated Office Building}, journal = {Building Simulation {\textquoteright}03}, year = {2003}, month = {08/2003}, address = {Eindhoven, Netherlands}, author = {Guilherme Carrilho da Gra{\c c}a and Paul F. Linden and Erin McConahey and Philip Haves} } @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} } @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} } @article {423, title = {A design day for building load and energy estimation}, journal = {Building and Environment}, volume = {34}, year = {1999}, month = {07/1999}, pages = {469-477}, chapter = {469}, abstract = {

We describe how a design day for building energy performance simulation can be selected from a typical meteorological year of a location. The advantages of the design day weather file are its simplicity and flexibility in use with simulation programs. The design day is selected using a weather parameter comprising the daily average dry bulb temperature and total solar insolation. The selection criterion addresses the balance between the need to minimise the part-load performance of the air-conditioning systems and plants and the number of hours of load not met. To validate the versatility of the design day weather file, we compare simulation results of the peak load and load profile of a building obtained from the DOE-2.1E code and a specially developed load estimation program, PEAKLOAD. PEAKLOAD is developed using the transfer function method and ASHRAE databases. Comparative results are in good agreement, indicating that a design day thus selected can be used when quick answers are required and simulations using a TMY file cannot be easily done or justified.

}, keywords = {building simulation, design day, doe-2, peak load calculation, weather data}, doi = {10.1016/S0360-1323(98)00035-3}, author = {Tianzhen Hong and Siaw K. Chou and T.Y. Bong} } @proceedings {325, title = {Development and Testing of a Prototype Tool for HVAC Control System Commissioning}, journal = {ASHRAE Transactions}, volume = {102}, year = {1996}, edition = {1}, address = {Atlanta, GA}, abstract = {

Describes a set of automated tests for use in commissioning the controls associated with coils and mixing boxes in air-handling units. The test procedures were developed using a computer simulation of an office building air conditioning system and were verified by manual testing in real buildings. A prototype automated commissioning system was then evaluated in blind tests on a large air conditioning test rig. Concludes that automated commissioning has the potential to reduce the cost and increase the thoroughness of HVAC controls commissioning. A prototype commissioning tool is under development based on the described approach.

}, keywords = {air conditioning, automatic, commissioning, controls, prototypes, testing, year 1996}, author = {Philip Haves and Jorgensen, D.R. and Tim I. Salsbury and Arthur L. Dexter} } @proceedings {328, title = {Detailed Modelling and Simulation of a VAV Air-Conditioning System}, journal = {Building Simulation {\textquoteright}95}, year = {1995}, month = {08/1995}, address = {Madison, WI}, abstract = {The paper describes a component-based dynamic simulation of a variable air volume (VAV) airconditioning system. The model is based closely on the design of one floor of a real commercial office building in London. The model includes an air handling unit and a duct system incorporating pressure-independent VAV boxes. The paper describes the simulation environment used to test control systems and to develop fault detection and diagnosis procedures and presents results of simulations that illustrate how the simulation can be used to study the interactions between control loops.}, url = {http://www.ibpsa.org/proceedings/BS1995/BS95_056_63.pdf}, author = {Philip Haves} } @article {335, title = {Design, Construction and Commissioning of Building Emulators for EMCS Applications}, journal = {ASHRAE Transactions}, volume = {100}, year = {1994}, author = {Shengwei Wang and Philip Haves and Pierre Nusgens} } @proceedings {337, title = {Development of Techniques to Assist in the Commissioning of HVAC Control Systems}, journal = {CIBSE National Conference}, year = {1993}, month = {05/1993}, address = {Manchester, UK}, author = {Arthur L. Dexter and Philip Haves and Jorgensen, D.R.} } @article {348, title = {Daylight in Dynamic Thermal Modelling Programs: a Case Study}, journal = {Building Services Engineering Research \& Technology}, volume = {9}, year = {1988}, month = {11/1988}, pages = {183-188}, chapter = {183}, abstract = {

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

}, doi = {10.1177/014362448800900406}, author = {Philip Haves and Paul J. Littlefair} } @proceedings {353, title = {Development of SERI-RES within the UK Passive Solar Programme}, journal = {10th National Passive Solar Conference}, year = {1986}, month = {06/1986}, address = {Boulder, CO}, author = {John G.F. Littler and Philip Haves} } @conference {55797, title = {The DOE-2 Computer Program for Thermal Simulation of Buildings}, booktitle = {American Institute of Physics (AIP)}, volume = {135}, number = {642}, year = {1985}, month = {01/1985}, publisher = {American Institute of Physics}, organization = {American Institute of Physics}, doi = {10.1063/1.35478}, author = {Birdsall, Bruce E. and Walter F. Buhl and Richard B. Curtis and Ender Erdem and Joseph Eto and James J. Hirsch and Karen H. Olson and Frederick C. Winkelmann} } @conference {55945, title = {The DOE-2 Building Energy Analysis Program}, booktitle = {ASEAN Conference on Energy Conservation in Buildings}, year = {1984}, month = {05/1984}, address = {Singapore}, author = {Richard B. Curtis and Birdsall, Bruce E. and Walter F. Buhl and Ender Erdem and Joseph H. Eto and James J. Hirsch and Karen H. Olson and Frederick C. Winkelmann} } @proceedings {359, title = {Dehumidification and Passive Cooling for Retrofit and Conventional Construction}, journal = {7th National Passive Solar Conference}, year = {1982}, month = {07/1982}, address = {Knoxville, TN}, author = {Philip Haves and Fred M. Loxsom and Earl S. Doderer} } @proceedings {365, title = {Design and Operating Strategies and Sizing Relationships for Solar Regenerated Desiccant Dehumidifiers Used with Passive Cooling Systems}, journal = {1st International Passive \& Hybrid Cooling Conference}, year = {1981}, month = {11/1981}, address = {Miami, FL}, author = {Peter E. Nelson and Philip Haves} }