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The capacity value of optimal wind and solar portfolios

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  • Shahriari, Mehdi
  • Blumsack, Seth

Abstract

Using large data sets of simulated wind and solar energy production, we create optimal wind, solar and blended (combined wind and solar) portfolios over various spatial and temporal scales, and use portfolio theory to quantify the capacity benefits in various portions of the electric grid in the Eastern United States. We add to the existing literature on portfolio analysis of renewable energy resources by (i) studying the benefits of optimal aggregation over various spatial and temporal scales, (ii) quantifying the capacity benefits of renewable portfolios over space and time, and (iii) analyzing spatial distributions of renewable installations in optimal renewable portfolios. The results indicate that full time availability of wind and blended portfolios are respectively 14 and 17 times larger than full time availability of an individual wind farm and adding solar to wind portfolios increases the availability factor of renewable portfolios by more than 40% in most regions. Further, optimal hourly portfolios provide higher capacity value relative to daily and weekly portfolios.

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  • Shahriari, Mehdi & Blumsack, Seth, 2018. "The capacity value of optimal wind and solar portfolios," Energy, Elsevier, vol. 148(C), pages 992-1005.
    • Handle: RePEc:eee:energy:v:148:y:2018:i:c:p:992-1005
    DOI: 10.1016/j.energy.2017.12.121
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    6. Huang, Zhenyu & Liu, Youbo & Li, Kecun & Liu, Jichun & Gao, Hongjun & Qiu, Gao & Shen, Xiaodong & Liu, Junyong, 2023. "Evaluating long-term profile of demand response under different market designs: A comparison of scarcity pricing and capacity auction," Energy, Elsevier, vol. 282(C).
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    8. Castro, Gabriel Malta & Klöckl, Claude & Regner, Peter & Schmidt, Johannes & Pereira, Amaro Olimpio, 2022. "Improvements to Modern Portfolio Theory based models applied to electricity systems," Energy Economics, Elsevier, vol. 111(C).
    9. Tangerås, Thomas & Wolak, Frank A., 2019. "Locational Marginal Network Tariffs for Intermittent Renewable Generation," Working Paper Series 1310, Research Institute of Industrial Economics.
    10. Chu, Cheng-Ta & Hawkes, Adam D., 2020. "Optimal mix of climate-related energy in global electricity systems," Renewable Energy, Elsevier, vol. 160(C), pages 955-963.
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    12. Han, Chanok & Vinel, Alexander, 2022. "Reducing forecasting error by optimally pooling wind energy generation sources through portfolio optimization," Energy, Elsevier, vol. 239(PB).
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    15. Gabriel Malta Castro & Claude Klockl & Peter Regner & Johannes Schmidt & Amaro Olimpio Pereira Jr, 2021. "Improvements to Modern Portfolio Theory based models applied to electricity systems," Papers 2105.08182, arXiv.org.
    16. Kashanian, Motahareh & Pishvaee, Mir Saman & Sahebi, Hadi, 2020. "Sustainable biomass portfolio sourcing plan using multi-stage stochastic programming," Energy, Elsevier, vol. 204(C).

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