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Solar farm investment game model: A data‐driven case in Florida

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  • Junhai Ma
  • Tiantong Xu

Abstract

The most effective approach to subsidizing power producers in order to bolster the penetration of renewable energy is continuously debated. To address this issue, this paper undertakes an in‐depth investigation into a solar farm investment problem, aiming at capturing the common interests and frictions among the government, the solar system developer, and the utility. In this paper, both static and dynamic game models are proposed with the consideration of the uncertainty of solar power generation. Before investing in a solar farm project, a potential solar farm investor takes into account of subsidy rate regulation for utilities enacted by the government, the panel price announced by the solar developer. In this study, we identified two thresholds of solar panel cost, which provide valuable insights for government policymakers when formulating an appropriate subsidy rate for the solar energy industry. Besides, a optimal policy for each stakeholder has been exposed. The finding from the dynamic model discloses the profound influence of various behaviors on the long‐term profitability of each stakeholder. Finally, based on the real‐world solar power data in Orlando, a case study is presented to expose a more tangible prospect for industrial application.

Suggested Citation

  • Junhai Ma & Tiantong Xu, 2023. "Solar farm investment game model: A data‐driven case in Florida," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(6), pages 3724-3738, September.
    • Handle: RePEc:wly:mgtdec:v:44:y:2023:i:6:p:3724-3738
    DOI: 10.1002/mde.3904
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