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

Travis Simpkins, Dylan Cutler, Katherine Anderson, Matthew Long

Research output: Contribution to conferencePaperpeer-review

13 Scopus Citations

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, of the variables considered, 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 pages6
DOIs
StatePublished - 17 Nov 2016
Event48th North American Power Symposium, NAPS 2016 - Denver, United States
Duration: 18 Sep 201620 Sep 2016

Conference

Conference48th North American Power Symposium, NAPS 2016
Country/TerritoryUnited States
CityDenver
Period18/09/1620/09/16

Bibliographical note

See NREL/CP-7A40-66832 for preprint

NREL Publication Number

  • NREL/CP-7A40-67830

Keywords

  • Batteries
  • energy storage
  • mathematical programming
  • Monte Carlo methods
  • regression analysis

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