|Title||Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Lee, Sang Hoon, Tianzhen Hong, Mary Ann Piette, Geof Sawaya, Yixing Chen, and Sarah C. Taylor-Lange|
|Keywords||building simulation, Energy conservation measure, energy modeling, energyplus, High Performance computing, retrofit|
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 detailedon-site energy audit to identify and evaluate cost-effective energy technologies. This study presents aDEEP (database of energy efficiency performance) that provides a direct resource for quick retrofitanalysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlussimulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. Thesimulations utilize prototype models representative of small and mid-size offices and retails in Californiaclimates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performancecomputing clusters to evaluate hundreds of individual and packaged ECMs covering envelope,lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture andsimulation 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, theCommercial Building Energy Saver, which provides a platform for energy retrofit decision making byquerying DEEP and unearthing recommended ECMs, their estimated energy savings and financialpayback.
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