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How much capacity deferral value can targeted solar deployment create in Pennsylvania?

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  • Keen, Jeremy F.
  • Apt, Jay

Abstract

We assess the ability of distributed solar to defer distribution capacity projects in a typical low load growth utility in the Northeast USA, PECO. We find that targeted placement can increase the deferral value of solar up to fourfold, but that deferrable projects are rare. In our baseline scenario, we find a 5% solar energy penetration with Net Energy Metering rolled out from 2020 to 2030 would increase rates by 0.8% over a 20-year horizon and generate just $1 MM in net present deferral value. This estimate assumes untargeted placement of solar, a low effective capacity (i.e. the reduction in peak load relative to solar's nominal capacity), a 1% growth rate, and 1% of PECO's distribution yearly capex budget that is deferrable. A higher effective capacity (e.g. from coupling energy storage with solar) and targeted placement could generate a net $8 MM of value over the same horizon, but the rate increase is mostly unaffected. We recommend the use of targeted solar placement in utility planning processes. Compared to untargeted placement, targeted placement can increase the total deferral value fourfold, but the effect on rates is small for PECO because few capacity deferral opportunities exist.

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  • Keen, Jeremy F. & Apt, Jay, 2019. "How much capacity deferral value can targeted solar deployment create in Pennsylvania?," Energy Policy, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:enepol:v:134:y:2019:i:c:s030142151930480x
    DOI: 10.1016/j.enpol.2019.110902
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    1. Woo, C.K. & Orans, Ren & Horii, Brian & Pupp, Roger & Heffner, Grayson, 1994. "Area- and time-specific marginal capacity costs of electricity distribution," Energy, Elsevier, vol. 19(12), pages 1213-1218.
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    2. Chang, Lei & Qian, Chong & Dilanchiev, Azer, 2022. "Nexus between financial development and renewable energy: Empirical evidence from nonlinear autoregression distributed lag," Renewable Energy, Elsevier, vol. 193(C), pages 475-483.
    3. Cui, Kai & Li, Xinxue & Li, Gang, 2023. "What kind of fiscal policies and natural resources efficiency promotes green economic growth? Evidence from regression analysis," Resources Policy, Elsevier, vol. 85(PB).
    4. Zhang, Dongyang & Mohsin, Muhammad & Taghizadeh-Hesary, Farhad, 2022. "Does green finance counteract the climate change mitigation: Asymmetric effect of renewable energy investment and R&D," Energy Economics, Elsevier, vol. 113(C).
    5. Lavin, Luke & Apt, Jay, 2021. "The importance of peak pricing in realizing system benefits from distributed storage," Energy Policy, Elsevier, vol. 157(C).
    6. Luo, Shunjun & Zhang, Shaohui, 2022. "How R&D expenditure intermediate as a new determinants for low carbon energy transition in Belt and Road Initiative economies," Renewable Energy, Elsevier, vol. 197(C), pages 101-109.

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