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 language | American English |
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Number of pages | 6 |
DOIs | |
State | Published - 17 Nov 2016 |
Event | 48th North American Power Symposium, NAPS 2016 - Denver, United States Duration: 18 Sep 2016 → 20 Sep 2016 |
Conference
Conference | 48th North American Power Symposium, NAPS 2016 |
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Country/Territory | United States |
City | Denver |
Period | 18/09/16 → 20/09/16 |
Bibliographical note
See NREL/CP-7A40-66832 for preprintNREL Publication Number
- NREL/CP-7A40-67830
Keywords
- Batteries
- energy storage
- mathematical programming
- Monte Carlo methods
- regression analysis