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Who bears the risk? Incentives for renewable electricity under strategic interaction between regulator and investors

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  • Alcorta, Peio
  • Espinosa, Maria Paz
  • Pizarro-Irizar, Cristina

Abstract

Energy policies for promoting investment in renewable energy sources have become crucial for deploying green energy technologies worldwide. Conventional incentive systems assign risk to either policymakers or investors. In this paper, we combine option theory and game theory to obtain optimal parameters for incentive schemes with different degrees of risk-sharing. We present an empirical application to the Spanish electricity market for 2013, when the Feed-in Tariff scheme was still in force, and for 2019, when Feed-in Tariffs had been completely phased out but before the demand shock caused by COVID-19, the restructuring of market price limits, and the recent energy price crisis in Europe. Our results indicate that there are more flexible systems based on Fixed Tariffs and Premiums that can outperform conventional designs, since they may enable the same investment level to be reached at a lower regulatory cost. In addition, these hybrid schemes permit risk-sharing between both parties. Our results may also be useful for designing incentives awarded through competitive auctions.

Suggested Citation

  • Alcorta, Peio & Espinosa, Maria Paz & Pizarro-Irizar, Cristina, 2023. "Who bears the risk? Incentives for renewable electricity under strategic interaction between regulator and investors," Resource and Energy Economics, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:resene:v:75:y:2023:i:c:s0928765523000568
    DOI: 10.1016/j.reseneeco.2023.101401
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    Keywords

    Renewable energy; Feed-in tariff; Energy policy; Energy economics; Option pricing;
    All these keywords.

    JEL classification:

    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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