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

Travis Simpkins, Katherine Anderson, Dylan Cutler, Matthew Long

Research output: Contribution to conferencePaper

Abstract

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.
Original languageAmerican English
Number of pages8
StatePublished - 2016
Event2016 North American Power Symposium (NAPS) - Denver, Colorado
Duration: 18 Sep 201620 Sep 2016

Conference

Conference2016 North American Power Symposium (NAPS)
CityDenver, Colorado
Period18/09/1620/09/16

NREL Publication Number

  • NREL/CP-7A40-66832

Keywords

  • batteries
  • energy storage
  • mathematical programming
  • Monte Carlo methods
  • regression analysis
  • REopt

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