A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings

Conference · Mon Nov 21 04:00:00 EST 2016

DOI:https://doi.org/10.1109/NAPS.2016.7747918· OSTI ID:1342084

Long, Matthew; Simpkins, Travis; Cutler, Dylan; Anderson, Kate

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape of the load profile is the most significant predictor of the size of the battery.

• Research Organization: NREL (National Renewable Energy Laboratory (NREL), Golden, CO (United States))
• Sponsoring Organization: USDOE Science Undergraduate Laboratory Internships
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1342084
• Report Number(s): NREL/CP-7A40-67830
• Country of Publication: United States
• Language: English

Related Subjects

25 ENERGY STORAGE
Monte Carlo methods
batteries
energy storage
mathematical programming
regression analysis