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Pricing, capacity and financing policies for investment of renewable energy generations

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  • Tsao, Yu-Chung
  • Vu, Thuy-Linh
  • Lu, Jye-Chyi

Abstract

The costs of renewable energy technologies are highly sensitive to financing terms. Power companies are willing to invest in renewable energy generation because of clean and sustainability concerns. However, renewable energy generation poses a potentially high risk, both in generation and consumption. In this study, we consider how a power company makes its decisions if a credit bank willing to lend to it for renewable energy generation. The repayment ability of the company depends on sales revenue under demand uncertainty. We formulate a mathematical model to help the company determine the optimal electricity price, renewable energy capacity, and amount of loan while maximizing the total expected profit. A searching algorithm is proposed to solve the problem. Several numerical examples are provided to illustrate the proposed model and solution approach. Managerially, our study suggests that increasing renewable energy investments through financing institutions requires careful attention to pricing, capacity, and financing policies.

Suggested Citation

  • Tsao, Yu-Chung & Vu, Thuy-Linh & Lu, Jye-Chyi, 2021. "Pricing, capacity and financing policies for investment of renewable energy generations," Applied Energy, Elsevier, vol. 303(C).
    • Handle: RePEc:eee:appene:v:303:y:2021:i:c:s0306261921010278
    DOI: 10.1016/j.apenergy.2021.117664
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    References listed on IDEAS

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    5. Rui Ai & Yuhang Zheng & Serhat Yüksel & Hasan Dinçer, 2023. "Investigating the components of fintech ecosystem for distributed energy investments with an integrated quantum spherical decision support system," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.

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