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Demand charge savings from solar PV and energy storage

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  • Darghouth, Naïm R.
  • Barbose, Galen
  • Zuboy, Jarett
  • Gagnon, Pieter J.
  • Mills, Andrew D.
  • Bird, Lori

Abstract

With an increasing number of jurisdictions considering alternatives to net metering policies to financially compensate behind-the-meter solar photovoltaics (PV), customer economics will increasingly depend on its ability to reduce demand charges. Understanding these demand charge savings from PV—and how behind-the-meter storage can potentially enhance those savings—is essential to understand PV market dynamics and adoption in the coming years. This article explores how these demand charge savings vary with demand charge designs and customer load profiles, modeled for a variety of residential and commercial customers. Our findings indicate that demand charge savings are lowest under a basic, non-coincident demand charge design where the demand charge is based on the maximum demand level over the month, regardless of timing, resulting primarily from the temporal mismatch between the timing of the PV host's demand peak and PV generation. PV provides greater demand charge savings, for both commercial and residential customers, when demand charge designs are based on predefined, daytime peak periods or longer averaging intervals. Demand charge savings from PV combined with storage are almost always greater than the sum of the savings attained through either technology separately. We also explore how well demand charge savings from PV align with corresponding utility savings.

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  • Darghouth, Naïm R. & Barbose, Galen & Zuboy, Jarett & Gagnon, Pieter J. & Mills, Andrew D. & Bird, Lori, 2020. "Demand charge savings from solar PV and energy storage," Energy Policy, Elsevier, vol. 146(C).
    • Handle: RePEc:eee:enepol:v:146:y:2020:i:c:s0301421520304882
    DOI: 10.1016/j.enpol.2020.111766
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    2. Prabha Bhola & Alexandros-Georgios Chronis & Panos Kotsampopoulos & Nikos Hatziargyriou, 2023. "Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach," Energies, MDPI, vol. 16(18), pages 1-30, September.

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