@article {29854, title = {Small and Medium Building Efficiency Toolkit and Community Demonstration Program}, year = {2017}, month = {03/2017}, abstract = {

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

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

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

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

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

}, keywords = {CBES, commercial buildings, energy efficiency, energy modeling, energy savings, indoor air quality, indoor environmental quality, outdoor air measurement technology, outdoor airflow intake rate, retrofit, ventilation rate}, doi = {10.7941/S93P70}, author = {Mary Ann Piette and Tianzhen Hong and William J. Fisk and Norman Bourassa and Wanyu R. Chan and Yixing Chen and H.Y. Iris Cheung and Toshifumi Hotchi and Margarita Kloss and Sang Hoon Lee and Phillip N. Price and Oren Schetrit and Kaiyu Sun and Sarah C. Taylor-Lange and Rongpeng Zhang} } @article {60962, title = {Advances in research and applications of energy-related occupant behavior in buildings}, journal = {Energy and Buildings}, volume = {116}, year = {2016}, month = {03/2016}, pages = {694-702}, abstract = {

Occupant behavior is one of the major factors influencing building energy consumption and contributing to uncertainty in building energy use prediction and simulation. Currently the understanding of occupant behavior is insufficient both in building design, operation and retrofit, leading to incorrect simplifications in modeling and analysis. This paper introduced the most recent advances and current obstacles in modeling occupant behavior and quantifying its impact on building energy use. The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact. There has been growing research and applications in this field, but significant challenges and opportunities still lie ahead.

}, keywords = {Behavior Modeling, Building design and operation, building performance simulation, energy use, occupant behavior}, doi = {10.1016/j.enbuild.2015.11.052}, author = {Tianzhen Hong and Sarah C. Taylor-Lange and Simona D{\textquoteright}Oca and Da Yan and Stefano P. Corgnati} } @article {60965, title = {Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance}, journal = {Energy}, year = {2015}, month = {07/2015}, chapter = {738}, abstract = {

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

}, keywords = {building simulation, Energy conservation measure, energy modeling, energyplus, High Performance computing, retrofit}, doi = {10.1016/j.energy.2015.07.107}, author = {Sang Hoon Lee and Tianzhen Hong and Mary Ann Piette and Geof Sawaya and Yixing Chen and Sarah C. Taylor-Lange} } @article {61107, title = {Commercial Building Energy Saver: An energy retrofit analysis toolkit}, journal = {Applied Energy}, volume = {159}, year = {2015}, month = {9/2015}, chapter = {298}, abstract = {

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

}, keywords = {Building Technologies Department, Building Technology and Urban Systems Division, buildings, buildings energy efficiency, Commercial Building Systems, conservation measures, energy efficiency, energy use, energyplus, External, Retrofit Energy, simulation research}, doi = {10.1016/j.apenergy.2015.09.002}, author = {Tianzhen Hong and Mary Ann Piette and Yixing Chen and Sang Hoon Lee and Sarah C. Taylor-Lange and Rongpeng Zhang and Kaiyu Sun and Phillip N. Price} } @article {60955, title = {Energy retrofit analysis toolkit for commercial buildings: A review}, volume = {89}, year = {2015}, month = {09/2015}, pages = {1087-1100}, publisher = {Elsevier Ltd.}, chapter = {1087}, abstract = {

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

}, keywords = {Building energy retrofit, Energy conservation measures, Energy efficiency, Energy simulation, Retrofit analysis tools, Web-based applications}, doi = {10.1016/j.energy.2015.06.112}, author = {Sang Hoon Lee and Tianzhen Hong and Mary Ann Piette and Sarah C. Taylor-Lange} } @article {60959, title = {An Ontology to Represent Energy-Related Occupant Behavior in Buildings. Part II: Implementation of the DNAS framework using an XML schema}, journal = {Building and Environment}, volume = {94}, year = {2015}, month = {08/2015}, pages = {196-205}, abstract = {

Energy-related occupant behavior in buildings is difficult to define and quantify, yet critical to our understanding of total building energy consumption. Part I of this two-part paper introduced the DNAS (Drivers, Needs, Actions and Systems) framework, to standardize the description of energy-related occupant behavior in buildings. Part II of this paper implements the DNAS framework into an XML (eXtensible Markup Language) schema, titled {\textquoteleft}occupant behavior XML{\textquoteright} (obXML). The obXML schema is used for the practical implementation of the DNAS framework into building simulation tools. The topology of the DNAS framework implemented in the obXML schema has a main root element OccupantBehavior, linking three main elements representing Buildings, Occupants and Behaviors. Using the schema structure, the actions of turning on an air conditioner and closing blinds provide two examples of how the schema standardizes these actions using XML. The obXML schema has inherent flexibility to represent numerous, diverse and complex types of occupant behaviors in buildings, and it can also be expanded to encompass new types of behaviors. The implementation of the DNAS framework into the obXML schema will facilitate the development of occupant information modeling (OIM) by providing interoperability between occupant behavior models and building energy modeling programs.

}, keywords = {building energy consumption, building simulation, energy modeling, obXML, occupant behavior, XML schema}, doi = {10.1016/j.buildenv.2015.08.006}, author = {Tianzhen Hong and Simona D{\textquoteright}Oca and Sarah C. Taylor-Lange and William J. N. Turner and Yixing Chen and Stefano P. Corgnati} } @article {59959, title = {An Ontology to Represent Energy-related Occupant Behavior in Buildings Part I: Introduction to the DNAs Framework}, journal = {Building and Environment}, volume = {92}, year = {2015}, month = {10/2015}, pages = {764-777}, abstract = {

Reducing energy consumption in the buildings sector requires significant changes, but technology alone may fail to guarantee efficient energy performance. Human behavior plays a pivotal role in building design, operation, management and retrofit, and is a crucial positive factor for improving the indoor environment, while reducing energy use at low cost. Over the past 40 years, a substantial body of literature has explored the impacts of human behavior on building technologies and operation. Often, need-action-event cognitive theoretical frameworks were used to represent human-machine interactions. In Part I of this paper a review of more than 130 published behavioral studies and frameworks was conducted. A large variety of data-driven behavioral models have been developed based on field monitoring of the human-building-system interaction. Studies have emerged scattered geographically around the world that lack in standardization and consistency, thus leading to difficulties when comparing one with another. To address this problem, an ontology to represent energy-related occupant behavior in buildings is presented. Accordingly, the technical DNAs framework is developed based on four key components: i) the Drivers of behavior, ii) the Needs of the occupants, iii) the Actions carried out by the occupants, and iv) the building systems acted upon by the occupants. This DNAs framework is envisioned to support the international research community to standardize a systematic representation of energy-related occupant behavior in buildings. Part II of this paper further develops the DNAs framework as an XML (eXtensible Markup Language) schema, obXML, for exchange of occupant information modeling and integration with building simulation tools.

}, keywords = {Building energy, human-building-system interaction, modeling, occupant behavior, ontology, simulation}, doi = {10.1016/j.buildenv.2015.02.019}, author = {Tianzhen Hong and Simona D{\textquoteright}Oca and William J. N. Turner and Sarah C. Taylor-Lange} } @article {60964, title = {A pattern-based automated approach to building energy model calibration}, year = {2015}, abstract = {

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

}, author = {Kaiyu Sun and Tianzhen Hong and Sarah C. Taylor-Lange and Mary Ann Piette} }