@article {31669, title = {A novel approach for selecting typical hot-year (THY) weather data}, journal = {Applied Energy}, volume = {242}, year = {2019}, month = {03/2019}, pages = {1634 - 1648}, abstract = {

The global climate change has resulted in not only warmer climate conditions but also more frequent extreme weather events, such as heat waves. However, the impact of heat waves on the indoor environment has been investigated in a limited manner. In this research, the indoor thermal environment is analyzed using a building performance simulation tool for a typical residential building in multiple cities in China, over a time period of 60 years using actual measured weather data, in order to gain a better understanding of the effect of heat wave events. The simulation results were used to analyze the indoor environment during hot summers. A new kind of weather data referred to as the typical hot year was defined and selected based on the simulated indoor environment during heat waves. The typical hot-year weather data can be used to simulate the indoor environment during extreme heat events and for the evaluation of effective technologies and strategies to mitigate against the impact of heat waves on the energy demand of buildings and human health. The limitations of the current study and future work are also discussed.

}, keywords = {Actual weather data, dest, Heat wave, Multiyear simulation, Residential indoor thermal environment, Typical hot year}, issn = {03062619}, doi = {10.1016/j.apenergy.2019.03.065}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261919304659}, author = {Siyue Guo and Da Yan and Tianzhen Hong and Chan Xiao and Ying Cui} } @conference {31980, title = {Prototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings}, booktitle = {IBPSA Building Simulation 2019}, year = {2019}, address = {Rome, Italy}, abstract = {

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

}, keywords = {benchmarking, building simulation, Model predictive control, software development}, author = {David Blum and Filip Jorissen and Sen Huang and Yan Chen and Javier Arroyo and Kyle Benne and Yanfei Li and Valentin Gavan and Lisa Rivalin and Lieve Helsen and Draguna Vrabie and Michael Wetter and Marina Sofos} } @conference {31743, title = {Control Description Language}, booktitle = {1st American Modelica Conference}, year = {2018}, month = {08/2018}, abstract = {

Properly designed and implemented building control sequences can significantly reduce energy consumption. However, there is currently no process with supporting tools that allows the assessment of the performance of different control sequences, export the control sequences in a vendor-neutral format for cost estimation and for implementation on a building automation system through machine-to-machine translation, and reuse the sequences for verification during commissioning.

This paper describes a Control Description Language (CDL) that we developed to create such a process. For CDL, we selected a subset of Modelica that allows a convenient representation of control sequences, simulation of the control sequence coupled to a building energy model, and development of translators from CDL to building automation systems. To aid in the development of such translators, we created a translator from CDL to a JSON intermediate format. In future work, we seek to work with building control providers to develop translators from CDL to commercial building automation systems.

Through a case study, we show that CDL suffices for simulation-based performance assessment of two ASHRAE-published control sequences for a variable air volume flow system of an office building. Moreover, the case study showed that merely due to differences in the control sequences, annual HVAC energy use was reduced by 30\%. This difference is larger than the accuracy required when comparing different HVAC systems, thereby questioning the current practice of idealizing control sequences in building energy simulations, and demonstrating the importance of ensuring that the control sequence used during design simulations corresponds to the control sequence that will be implemented in the real building

}, keywords = {buildings, controls, hvac}, url = {https://simulationresearch.lbl.gov/wetter/download/2018-americanModelica-WetterGrahovacHu.pdf}, author = {Michael Wetter and Milica Grahovac and Jianjun Hu} } @conference {31688, title = {OpenBuildingControl: Modeling Feedback Control as a Step Towards Formal Design, Specification, Deployment and Verification of Building Control Sequences}, booktitle = {2018 Building Performance Modeling Conference and SimBuild co-organized by ASHRAE and IBPSA-USA}, year = {2018}, month = {09/2018}, address = {Chicago, IL}, abstract = {

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

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

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

}, url = {https://www.ashrae.org/File\%20Library/Conferences/Specialty\%20Conferences/2018\%20Building\%20Performance\%20Analysis\%20Conference\%20and\%20SimBuild/Papers/C107.pdf}, author = {Michael Wetter and Jianjun Hu and Milica Grahovac and Brent Eubanks and Philip Haves} } @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 {30314, title = {Analysis of heating load diversity in German residential districts and implications for the application in district heating systems}, journal = {Energy and Buildings}, volume = {139}, year = {2017}, month = {01/2017}, pages = {302-313}, chapter = {302}, abstract = {

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

}, keywords = {district heating, domestic hot water, dynamic building simulation, heat supply, Load diversity, peak load, residential district, space heating}, doi = {10.1016/j.enbuild.2016.12.096}, author = {Claudia Weissmann and Tianzhen Hong and Carl-Alexander Graubner} } @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 {30482, title = {IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings}, journal = {Energy and Building}, volume = {156}, year = {2017}, abstract = {

More than 30\% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupant behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle.

}, keywords = {building performance, energy modeling, energy use, IEA EBC Annex 66, Interdisciplinary approach, occupant behavior}, doi = {10.1016/j.enbuild.2017.09.084}, author = {Da Yan and Tianzhen Hong and Bing Dong and Ardeshir Mahdavi and Simona D{\textquoteright}Oca and Isabella Gaetani and Xiaohang Feng} } @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 {60948, title = {Occupant Behavior Modeling for Building Performance Simulation: Current State and Future Challenges}, journal = {Energy and Buildings}, volume = {107}, year = {2015}, month = {11/2015}, pages = {264-278}, abstract = {

Occupant behavior is now widely recognized as a major contributing factor to uncertainty of building performance. While a surge of research on the topic has occurred over the past four decades, and particularly the past few years, there are many gaps in knowledge and limitations to current methodologies. This paper outlines the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools. Major themes include the need for greater rigor in experimental methodologies; detailed, honest, and candid reporting of methods and results; and development of an efficient means to implement occupant behavior models and integrate them into building energy modeling programs.

}, keywords = {building simulation, energy efficiency, energy modeling, energy use, occupant behavior}, doi = {10.1016/j.enbuild.2015.08.032}, author = {Da Yan and William O{\textquoteright}Brien and Tianzhen Hong and Xiaohang Feng and H. Burak Gunay and Farhang Tahmasebi and Ardeshir Mahdavi} } @article {59969, title = {Integrated Design for High Performance Buildings}, year = {2014}, author = {Tianzhen Hong and Cheng Li and Richard C. Diamond and Da Yan and Qi Zhang and Xin Zhou and Siyue Guo and Kaiyu Sun and Jingyi Wang} } @article {59964, title = {Stochastic Modeling of Overtime Occupancy and Its Application in Building Energy Simulation and Calibration}, year = {2014}, abstract = {

Overtime is a common phenomenon around the world. Overtime drives both internal heat gains from occupants, lighting and plug-loads, and HVAC operation during overtime periods. Overtime leads to longer occupancy hours and extended operation of building services systems beyond normal working hours, thus overtime impacts total building energy use. Current literature lacks methods to model overtime occupancy because overtime is stochastic in nature and varies by individual occupants and by time. To address this gap in the literature, this study aims to develop a new stochastic model based on the statistical analysis of measured overtime occupancy data from an office building. A binomial distribution is used to represent the total number of occupants working overtime, while an exponential distribution is used to represent the duration of overtime periods. The overtime model is used to generate overtime occupancy schedules as an input to the energy model of a second office building. The measured and simulated cooling energy use during the overtime period is compared in order to validate the overtime model. A hybrid approach to energy model calibration is proposed and tested, which combines ASHRAE Guideline 14 for the calibration of the energy model during normal working hours, and a proposed KS test for the calibration of the energy model during overtime. The developed stochastic overtime model and the hybrid calibration approach can be used in building energy simulations to improve the accuracy of results, and better understand the characteristics of overtime in office buildings.

}, keywords = {building energy use, building simulation, model calibration, occupant behavior, overtime occupancy, stochastic modeling}, author = {Kaiyu Sun and Tianzhen Hong and Siyue Guo} } @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} } @conference {31981, title = {Sustainable Campus with PEV and Microgrid}, booktitle = {2012 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2012}, month = {08/2019}, address = {Pacific Grove, CA}, abstract = {

Market penetration of electric vehicles (EVs) is gaining momentum, as is the move
towards increasingly distributed, clean and renewable electricity sources. EV charging shifts a
significant portion of transportation energy use onto building electricity meters. Hence,
integration strategies for energy-efficiency in buildings and transport sectors are of increasing
importance. This paper focuses on a portion of that integration: the analysis of an optimal
interaction of EVs with a building-serving transformer, and coupling it to a microgrid that
includes PV, a fuel cell and a natural gas micro-turbine. The test-case is the Nanyang
Technological University (NTU), Singapore campus. The system under study is the Laboratory
of Clean Energy Research (LaCER) Lab that houses the award winning Microgrid Energy
Management System (MG-EMS) project. The paper analyses three different case scenarios to
estimate the number of EVs that can be supported by the building transformer serving LaCER.
An approximation of the actual load data collected for the building into different time intervals is
performed for a transformer loss of life (LOL) calculation. The additional EV loads that can be
supported by the transformer with and without the microgrid are analyzed. The numbers of
possible EVs that can be charged at any given time under the three scenarios are also determined.
The possibility of using EV fleet at NTU campus to achieve demand response capability and
intermittent PV output leveling through vehicle to grid (V2G) technology and building energy
management systems is also explored.

}, keywords = {buildings, campus, electric vehicles, energy, loads, microgrids, renewable energy, transport}, url = {https://aceee.org/files/proceedings/2012/data/papers/0193-000363.pdf}, author = {K. Nandha Kumar and B. Sivaneasan and P.L. So and H.B. Gooi and Nilesh Jadhav and Reshma Singh and Chris Marnay} } @conference {2634, title = {A software tool to compare measured and simulated building energy performance data}, booktitle = {IBPSA Building Simulation 2011}, year = {2011}, month = {11/2011}, address = {Sydney, Australia}, abstract = {

Building energy performance is often inadequate when compared to design goals. To link design goals to actual operation one can compare measured with simulated energy performance data. Our previously developed comparison approach is the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured and simulated performance data. In context of this method, we developed a software tool that provides graphing and data processing capabilities of the two performance data sets. The software tool called SEE IT (Stanford Energy Efficiency Information Tool) eliminates the need for manual generation of data plots and data reformatting. SEE IT makes the generation of time series, scatter and carpet plots independent of the source of data (measured or simulated) and provides a valuable tool for comparing measurements with simulation results. SEE IT also allows assigning data points on a predefined building object hierarchy and supports different versions of simulated performance data. This paper briefly introduces the EPCM, describes the SEE IT tool and illustrates its use in the context of a building case study.

}, author = {Tobias Maile and Vladimir Bazjanac and James O{\textquoteright}Donnell and Matthew Garr} } @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} } @article {237, title = {Case study of zero energy house design in UK}, journal = {Energy and Buildings}, volume = {41}, year = {2009}, month = {11/2009}, pages = {1215-1222}, author = {Liping Wang and Julie Gwilliam and Phillip Jones} } @conference {2640, title = {Integrating the Specification, Acquisition and Processing of Building Performance Information}, booktitle = {12th International Conference on Computing in Civil and Building Engineering}, year = {2008}, month = {10/2008}, address = {Beijing, China}, author = {Martin Keller and James O{\textquoteright}Donnell and Karsten Menzel and Marcus Keane and Ufuk G{\"o}k{\c c}e} } @conference {2659, title = {Airflow Network Modeling in EnergyPlus}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Lixing Gu} } @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 {2662, title = {A Simplified Hot Water Distribution System Model (DOE-2)}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Lixing Gu} } @conference {2654, title = {Simulation Enhanced Prototyping of an Experimental Solar House}, booktitle = {Proc. Building Simulation 2007}, year = {2007}, month = {09/2007}, address = {Beijing, China}, author = {Ruchi Choudhary and Godfried Augenbroe and Russell Gentry and Huafen Hu} } @article {2584, title = {Using Indicators to Profile Energy Consumption and Inform Energy Policy in a University - A Case Study in Ireland}, journal = {Energy and Buildings}, volume = {39}, year = {2007}, month = {08/2007}, pages = {913-922}, chapter = {913}, abstract = {

The services sector has the least amount of energy end use data available, which poses significant challenges to companies within the sector attempting to benchmark their energy performance and inform energy management decisions. This paper explores through a case study analysis the use of simple performance indicators and how additional data and new metrics can greatly enhance the understanding of energy trends and in particular the assessment of building energy performance. The country chosen for the analysis is Ireland, where the services sector has experienced high energy demand growth since 1990 (4.1\% annually) compared with the EU-15 (1.5\% annually). Despite this growth, the available energy data is poor, in particular for the public service sub-sectors. The case study chosen is an institution within the education sub-sector, University College Cork. The paper presents some simple energy performance indicators that have been used to date to inform energy policy. The paper then introduces new approaches and tools for assessing energy performance in buildings and how these may be utilised to improve the energy policy decision making and energy management. It discusses how these approaches are been implemented for buildings with separate functions, presents some initial results and discusses future planned work.

}, keywords = {building energy performance, Energy in services sector, energy policy, University}, doi = {10.1016/j.enbuild.2006.11.005}, author = {Brian {\'O} Gallach{\'o}ir and Marcus Keane and Elmer Morrissey and James O{\textquoteright}Donnell} } @proceedings {2794, title = {Assessment of the Technical Potential for Achieving Zero-Energy Commercial Buildings}, journal = {2006 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2006}, month = {08/2006}, author = {Brent T. Griffith and Paul A. Torcellini and John Ryan} } @proceedings {2795, title = {Automated Multivariate Optimization Tool for Energy Analysis}, journal = {SimBuild 2006}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Peter G. Ellis and Brent T. Griffith and Nicholas Long and Paul A. Torcellini} } @proceedings {2809, title = {A Case Study Demonstrating the Utility of Inter-Program Comparative Testing for Diagnosing Errors in Building Simulation Programs}, journal = {eSim 2006}, year = {2006}, month = {05/2006}, address = {Toronto, Canada}, author = {Andreas Weber and Ian Beausoleil-Morrison and Brent T. Griffith and Teemu Vesanen and S{\'e}bastien Lerson} } @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 {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 {270, title = {A Guide for Specifying Performance Monitoring Systems in Commercial and Institutional Buildings}, journal = {14th National Conference on Building Commissioning}, year = {2006}, month = {2006}, address = {San Francisco, CA}, abstract = {

This paper describes a guide for specifying performance monitoring systems that was developed as part of jointly funded CEC PIER-DOE project intended to assist commercial and institutional building owners in specifying what is required to obtain the information necessary to initiate and sustain an ongoing commissioning activity. The project{\textquoteright}s goal was to facilitate the delivery of specific performance related information to the benefit of both commissioning providers and building operators. A number of large-building owners were engaged in order to help create {\textquoteright}market pull{\textquoteright} for performance monitoring while producing a specification that met their needs. The specification guide and example specification language addresses four key aspects of performance monitoring:

The paper describes key aspects of the guide including how measurement accuracy requirements relate to the performance metrics that are used in both troubleshooting and routine reporting. Guide development activities and related tech-transfer efforts are also presented.

}, author = {Kenneth L. Gillespie and Philip Haves and Robert J. Hitchcock and Joseph J Deringer and Kristopher L. Kinney} } @proceedings {2807, title = {Methodology for Analyzing the Technical Potential for Energy Performance in the U.S. Commercial Buildings Sector With Detailed Energy Modeling}, journal = {SimBuild 2006}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Brent T. Griffith and Drury B. Crawley} } @proceedings {2799, title = {A Model for Naturally Ventilated Cavities on the Exteriors of Opaque Building Thermal Envelopes}, journal = {SimBuild 2006}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Brent T. Griffith} } @proceedings {2808, title = {Thermal Performance Simulation of an Atrium Building}, journal = {eSim 2006}, year = {2006}, month = {05/2006}, address = {Toronto, Canada}, author = {{\"O}zg{\"u}r G{\"o}{\c c}er and Aslihan Tavil and Ertan {\"O}zkan} } @proceedings {2817, title = {Contrasting the Capabilities of Building Energy Performance Simulation Programs}, journal = {IBPSA Building Simulation 2005}, year = {2005}, month = {08/2005}, address = {Montreal, Canada}, author = {Drury B. Crawley and Jon W. Hand and Michael Kummert and Brent T. Griffith} } @conference {2642, title = {Reducing Building Operational Cost Through Environmental Effectiveness Ratios}, booktitle = {Building Simulation 2005 IBPSA International Conference}, year = {2005}, month = {08/2005}, address = {Montreal, Canada}, author = {James O{\textquoteright}Donnell and Elmer Morrissey and Marcus Keane and Brian {\'O} Gallach{\'o}ir} } @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} } @article {2590, title = {Framework for Coupling Room Air Models to Heat Balance Model Load and Energy Calculations (RP-1222)}, journal = {HVAC\&R Research (ASHRAE)}, volume = {10}, year = {2004}, month = {04/2004}, author = {Brent T. Griffith and Qingyan Chen} } @proceedings {2818, title = {Photovoltaic and Solar Thermal Modeling with the EnergyPlus Calculation Engine}, journal = {World Renewable Energy Congress VIII and Expo}, year = {2004}, month = {09/2004}, address = {Denver, Colorado, USA}, author = {Brent T. Griffith and Peter G. Ellis} } @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 {344, title = {Self-tuning Control with Fuzzy Rule-Based Supervision for HVAC Applications}, journal = {ITAC 91}, year = {1991}, address = {Singapore}, author = {Keck-Voon Ling and Arthur L. Dexter and Geng, G. and Philip Haves} } @article {343, title = {Use of a Building Emulator to Develop Techniques for Improved Commissioning and Control of HVAC Systems}, journal = {ASHRAE Transactions}, volume = {97}, year = {1991}, keywords = {air conditioning, automatic, commissioning, computer programs, controls, energy management, heating, ventilation}, author = {Philip Haves and Arthur L. Dexter and Jorgensen, D.R. and Keck-Voon Ling and Geng, G.} } @conference {55644, title = {Modeling Cogeneration Systems with DOE-2.1C}, booktitle = {ASHRAE 1988 Winter Meeting}, year = {1988}, month = {01/1988}, publisher = {LBNL}, organization = {LBNL}, address = {Dallas, TX}, author = {Joseph H. Eto and Steven D. Gates} } @proceedings {354, title = {Generation of Data for Passive Solar Building Simulation from a Three Dimensional Architectural Modelling System}, journal = {PLEA{\textquoteright}86 Conference}, year = {1986}, month = {09/1986}, address = {Pecs, Hungary}, author = {Cedric Green and Philip Haves} } @proceedings {355, title = {The Integration of Graphic and Thermal Simulation Models}, journal = {Computer Graphics {\textquoteright}85 Conference}, year = {1985}, month = {10/1985}, publisher = {Wembley, Online Publications Ltd}, address = {Pinner, Middlesex, UK}, author = {Cedric Green and Philip Haves and Paul Huddy} }