TY - RPRT T1 - Small and Medium Building Efficiency Toolkit and Community Demonstration Program Y1 - 2017 A1 - Mary Ann Piette A1 - Tianzhen Hong A1 - William J. Fisk A1 - Norman Bourassa A1 - Wanyu R. Chan A1 - Yixing Chen A1 - H.Y. Iris Cheung A1 - Toshifumi Hotchi A1 - Margarita Kloss A1 - Sang Hoon Lee A1 - Phillip N. Price A1 - Oren Schetrit A1 - Kaiyu Sun A1 - Sarah C. Taylor-Lange A1 - Rongpeng Zhang KW - CBES KW - commercial buildings KW - energy efficiency KW - energy modeling KW - energy savings KW - indoor air quality KW - indoor environmental quality KW - outdoor air measurement technology KW - outdoor airflow intake rate KW - retrofit KW - ventilation rate AB -

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’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.

U2 - LBNL-2001054 ER - TY - JOUR T1 - Advances in research and applications of energy-related occupant behavior in buildings JF - Energy and Buildings Y1 - 2016 A1 - Tianzhen Hong A1 - Sarah C. Taylor-Lange A1 - Simona D'Oca A1 - Da Yan A1 - Stefano P. Corgnati KW - Behavior Modeling KW - Building design and operation KW - building performance simulation KW - energy use KW - occupant behavior AB -

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.

VL - 116 U2 - LBNL-1004497 ER - TY - JOUR T1 - Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance JF - Energy Y1 - 2015 A1 - Sang Hoon Lee A1 - Tianzhen Hong A1 - Mary Ann Piette A1 - Geof Sawaya A1 - Yixing Chen A1 - Sarah C. Taylor-Lange KW - building simulation KW - Energy conservation measure KW - energy modeling KW - energyplus KW - High Performance computing KW - retrofit AB -

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.

U2 - LBNL-1004494 ER - TY - JOUR T1 - Commercial Building Energy Saver: An energy retrofit analysis toolkit JF - Applied Energy Y1 - 2015 A1 - Tianzhen Hong A1 - Mary Ann Piette A1 - Yixing Chen A1 - Sang Hoon Lee A1 - Sarah C. Taylor-Lange A1 - Rongpeng Zhang A1 - Kaiyu Sun A1 - Phillip N. Price KW - Building Technologies Department KW - Building Technology and Urban Systems Division KW - buildings KW - buildings energy efficiency KW - Commercial Building Systems KW - conservation measures KW - energy efficiency KW - energy use KW - energyplus KW - External KW - Retrofit Energy KW - simulation research AB -

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.

VL - 159 U2 - LBNL-1004502 ER - TY - JOUR T1 - Energy retrofit analysis toolkit for commercial buildings: A review Y1 - 2015 A1 - Sang Hoon Lee A1 - Tianzhen Hong A1 - Mary Ann Piette A1 - Sarah C. Taylor-Lange KW - Building energy retrofit KW - Energy conservation measures KW - Energy efficiency KW - Energy simulation KW - Retrofit analysis tools KW - Web-based applications AB -

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.

PB - Elsevier Ltd. VL - 89 U2 - LBNL-1004503 ER - TY - JOUR T1 - An Ontology to Represent Energy-Related Occupant Behavior in Buildings. Part II: Implementation of the DNAS framework using an XML schema JF - Building and Environment Y1 - 2015 A1 - Tianzhen Hong A1 - Simona D'Oca A1 - Sarah C. Taylor-Lange A1 - William J. N. Turner A1 - Yixing Chen A1 - Stefano P. Corgnati KW - building energy consumption KW - building simulation KW - energy modeling KW - obXML KW - occupant behavior KW - XML schema AB -

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 ‘occupant behavior XML’ (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.

VL - 94 IS - 1 U2 - LBNL-1004501 ER - TY - JOUR T1 - An Ontology to Represent Energy-related Occupant Behavior in Buildings Part I: Introduction to the DNAs Framework JF - Building and Environment Y1 - 2015 A1 - Tianzhen Hong A1 - Simona D'Oca A1 - William J. N. Turner A1 - Sarah C. Taylor-Lange KW - Building energy KW - human-building-system interaction KW - modeling KW - occupant behavior KW - ontology KW - simulation AB -

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.

VL - 92 U2 - LBNL-180349 ER - TY - JOUR T1 - A pattern-based automated approach to building energy model calibration Y1 - 2015 A1 - Kaiyu Sun A1 - Tianzhen Hong A1 - Sarah C. Taylor-Lange A1 - Mary Ann Piette AB -

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.

U2 - LBNL-1004495 ER -