Commercial Building Energy Saver: An energy retrofit analysis toolkit

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.

[1]  Jessica Granderson,et al.  Small- and Medium-Sized Commercial Building Monitoring and Controls Needs: A Scoping Study , 2012 .

[2]  Qiang Zhang,et al.  Model-based benchmarking with application to laboratory buildings , 2002 .

[3]  Mary Ann Piette,et al.  Action–oriented Benchmarking: Concepts and Tools , 2008 .

[4]  Bing Liu,et al.  U.S. Department of Energy Commercial Reference Building Models of the National Building Stock , 2011 .

[5]  William Chung,et al.  Review of building energy-use performance benchmarking methodologies , 2011 .

[6]  Franz Fuerst,et al.  Building momentum: An analysis of investment trends in LEED and Energy Star-certified properties , 2009 .

[7]  Tianzhen Hong,et al.  Building simulation: an overview of developments and information sources , 2000 .

[8]  Simon Roberts,et al.  Altering existing buildings in the UK , 2008 .

[9]  Daniel Macumber,et al.  OpenStudio: An Open Source Integrated Analysis Platform , 2011 .

[10]  Kwang Ho Lee,et al.  Advanced Benchmarking for Complex Building Types: Laboratories as an Exemplar , 2010 .

[11]  Sang Hoon Lee,et al.  The use of normative energy calculation beyond building performance rating , 2013 .

[12]  Sang Hoon Lee,et al.  Review of Existing Energy Retrofit Tools , 2014 .

[13]  Amir Roth,et al.  DEnCity: An Open Multi-Purpose Building Energy Simulation Database , 2012 .

[14]  Mary Ann Piette,et al.  Energy retrofit analysis toolkits for commercial buildings: A review , 2015 .

[15]  Ali F. Alajmi Energy audit of an educational building in a hot summer climate , 2012 .

[16]  Fu Xiao,et al.  Quantitative energy performance assessment methods for existing buildings , 2012 .

[17]  Frédéric Magoulès,et al.  A review on the prediction of building energy consumption , 2012 .

[18]  Ernst Worrell,et al.  A novel approach for barriers to industrial energy efficiency , 2013 .

[19]  Natasa Nord,et al.  Success factors of energy efficiency measures in buildings in Norway , 2014 .

[20]  Chee Ming Lim,et al.  Developing building benchmarking for Brunei Darussalam , 2014 .

[21]  Edward Morofsky,et al.  Effectiveness of single and multiple energy retrofit measures on the energy consumption of office bu , 2011 .

[22]  U Haverinen-Shaughnessy,et al.  A preliminary study on the association between ventilation rates in classrooms and student performance. , 2006, Indoor air.

[23]  Le Yang,et al.  Data and analytics to inform energy retrofit of high performance buildings , 2014 .

[24]  Sang Hoon Lee,et al.  Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance , 2015 .

[25]  Paul Cooper,et al.  Existing building retrofits: Methodology and state-of-the-art , 2012 .

[26]  Yeonsook Heo,et al.  Calibration of building energy models for retrofit analysis under uncertainty , 2012 .

[27]  C. Filippín Benchmarking the energy efficiency and greenhouse gases emissions of school buildings in central Argentina , 2000 .

[28]  Endong Wang,et al.  Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach , 2015 .

[29]  E. M. Sterling,et al.  Building Performance Database , 1986 .

[30]  Tianzhen Hong,et al.  An insight into actual energy use and its drivers in high-performance buildings , 2014 .

[31]  Stuart Barlow,et al.  Occupant comfort in UK offices—How adaptive comfort theories might influence future low energy office refurbishment strategies , 2007 .

[32]  Hans Martin Mathisen,et al.  Energy cost models for air supported sports hall in cold climates considering energy efficiency , 2015 .

[33]  Travis Gliedt,et al.  Energy upgrades as financial or strategic investment? Energy Star property owners and managers improving building energy performance , 2015 .

[34]  Gregor P. Henze,et al.  An energy signal tool for decision support in building energy systems , 2015 .

[35]  Mohammad S. Al-Homoud,et al.  Computer-aided building energy analysis techniques , 2001 .

[36]  Michael D. Sohn,et al.  Big-data for building energy performance: Lessons from assembling a very large national database of building energy use , 2015 .

[37]  Na Wang Development of an Online Toolkit for Measuring Commercial Building Energy Efficiency Performance -- Scoping Study , 2013 .

[38]  W. Fisk,et al.  Association of ventilation rates and CO2 concentrations with health and other responses in commercial and institutional buildings. , 1999, Indoor air.

[39]  M J Mendell,et al.  Quantitative relationship of sick building syndrome symptoms with ventilation rates. , 2009, Indoor air.

[40]  Sang Hoon Lee,et al.  DEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings , 2015 .

[41]  William Chung,et al.  Benchmarking the energy efficiency of commercial buildings , 2006 .