@article{27491,
  keywords = {Energy efficiency, Buildings energy efficiency, Buildings, Energy use, EnergyPlus, Simulation research, External, Building Technology and Urban Systems Division, Building Technologies Department, Commercial Building Systems, Conservation measures, Retrofit Energy},
  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},
  title = {Commercial Building Energy Saver: An energy retrofit analysis toolkit},
  abstract = {<p>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.</p>},
  year = {2015},
  journal = {Applied Energy},
  volume = {159},
  month = {09/2015},
  doi = {10.1016/j.apenergy.2015.09.002},
}