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Optimal strategy of investing in solar energy for meeting the renewable portfolio standard requirement in America

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  • Junhai Ma
  • Tiantong Xu

Abstract

Renewable portfolio standard (RPS) is a legislative requirement for regulating the utility to increase the output of renewable energy, however, it’s not easy for the government to optimally design the target. To address this problem, this study investigates solar investing problems by theoretically investigating a novel game model. To meet the RPS requirement, the utility has to procure not only traditional energy but also solar energy. This paper aims to capture all the frictions among the stakeholders including the regulator, the utility and also a photovoltaic (PV) developer. The results show that the regulator can benefit from the strategy with higher RPS requirements if there is less resistance to regulation and a high penalty rate. Besides, the development of solar technology will increase the optimal PV panel price and investment in solar. Given a high requirement of renewable output, it’s better off to increase the solar investment for more green output. This study also finds the developer enjoys a high requirement because it promotes the PV adoption and increases the panel price as well. Additionally, a dynamic system was developed to study the players’ long-term behavior as well. The stable region and optimal strategy of behavior have been figured out. Interestingly, for the developer and the utility, a salutation of profit regarding the raising of the regulator’s adjusting speed of decision is observed. HighlightsStudy a novel problem of solar investment.Capture the frictions among the stakeholders under the Renewable Portfolio Standard regulation.Reveal the optimal strategy for the players.Investigate the players’ behavior in long term operations.Observe profit ramping phenomena for the developer and utility.

Suggested Citation

  • Junhai Ma & Tiantong Xu, 2023. "Optimal strategy of investing in solar energy for meeting the renewable portfolio standard requirement in America," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(1), pages 181-194, January.
  • Handle: RePEc:taf:tjorxx:v:74:y:2023:i:1:p:181-194
    DOI: 10.1080/01605682.2022.2032427
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    Cited by:

    1. Na Fu & Liyan Geng & Junhai Ma & Xue Ding, 2023. "Price, Complexity, and Mathematical Model," Mathematics, MDPI, vol. 11(13), pages 1-30, June.

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