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Assessing variability of photovoltaic load supply in Hawai‘i

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Listed:
  • Assané, Djeto
  • Konan, Denise Eby
  • Anukoolthamchote, Pam Chasuta

Abstract

Since 2010, the installed capacity of solar photovoltaic (PV) penetration in Hawai'i has soared due to exceedingly high electricity rates, generous installation tax credits, and net energy metering. The inherent variability of solar resources and changes in customer behavior impose increasing volatility at the circuit level, which poses challenges with grid stability. This study uses a rich and unique proprietary data set to assess the interrelated effects of weather and socio-economic factors on power system operations to maintain a balance between load and supply of solar photovoltaic at the system level. We find that PV penetration, weather and residents on circuit contribute greatly to volatility under varying operating regimes. In the end, Hawai'i shows that “old grids” can tolerate much higher level of penetration than previously understood.

Suggested Citation

  • Assané, Djeto & Konan, Denise Eby & Anukoolthamchote, Pam Chasuta, 2019. "Assessing variability of photovoltaic load supply in Hawai‘i," Energy Policy, Elsevier, vol. 132(C), pages 290-298.
    • Handle: RePEc:eee:enepol:v:132:y:2019:i:c:p:290-298
    DOI: 10.1016/j.enpol.2019.05.007
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    References listed on IDEAS

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    Cited by:

    1. Anukoolthamchote, Pam Chasuta & Assané, Djeto & Konan, Denise Eby, 2020. "Net electricity load profiles: Shape and variability considering customer-mix at transformers on the island of Oahu, Hawai'i," Energy Policy, Elsevier, vol. 147(C).

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    More about this item

    Keywords

    Photovoltaic output variability; Photovoltaic supply; Renewable energy; Customer type; Socio-economic attributes;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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