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Internal hedging of intermittent renewable power generation and optimal portfolio selection

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  • Carlo Lucheroni

    (University of Camerino)

  • Carlo Mari

    (University of Chieti - Pescara)

Abstract

This paper introduces a scheme for hedging and managing production costs of a risky generation portfolio, initially assumed to be dispatchable, to which intermittent electricity generation from non-dispatchable renewable sources like wind is further added. The proposed hedging mechanism is based on fixing the total production level in advance, then compensating any unpredictable non-dispatchable production with a matching reduction of the dispatchable fossil fuel production. This means making no recourse to short term techniques like financial hedging or storage, in a way fully internal to the portfolio itself. Optimization is obtained in the frame of the stochastic LCOE theory, in which fuel costs and $$\hbox {CO}_2$$ CO 2 prices are included as uncertainty sources besides intermittency, and in which long term production cost risk, proxied either by LCOE standard deviation and LCOE CVaR Deviation, is minimized. Closed form solutions for optimal hedging strategies under both risk measures are provided. Main economic consequences are discussed. For example, this scheme can be seen as a method for optimally including intermittent renewable sources in an otherwise dispatchable generation portfolio under a long term capacity expansion perspective. Moreover, within this hedging scheme, (1) production cost risk is reduced and optimized as a consequence of the substitution of the dispatchable fossil fuel generation with non-dispatchable $$\hbox {CO}_2$$ CO 2 free generation, and (2) generation costs can be reduced if the intermittent generation can be partially predicted.

Suggested Citation

  • Carlo Lucheroni & Carlo Mari, 2021. "Internal hedging of intermittent renewable power generation and optimal portfolio selection," Annals of Operations Research, Springer, vol. 299(1), pages 873-893, April.
    • Handle: RePEc:spr:annopr:v:299:y:2021:i:1:d:10.1007_s10479-019-03221-2
    DOI: 10.1007/s10479-019-03221-2
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    References listed on IDEAS

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    1. Jung, Jaesung & Broadwater, Robert P., 2014. "Current status and future advances for wind speed and power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 762-777.
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    6. Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.
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    Cited by:

    1. Abate, Arega Getaneh & Riccardi, Rossana & Ruiz, Carlos, 2022. "Contract design in electricity markets with high penetration of renewables: A two-stage approach," Omega, Elsevier, vol. 111(C).
    2. Arega Getaneh Abate & Rossana Riccardi & Carlos Ruiz, 2022. "Contract design in electricity markets with high penetration of renewables: A two-stage approach," Papers 2201.09927, arXiv.org, revised Jun 2022.

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