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Stochastic model to aid decision making on investments in renewable energy generation: Portfolio diffusion and investor risk aversion

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  • de Freitas, Renan Alves
  • Vogel, Ederson Paulo
  • Korzenowski, André Luis
  • Oliveira Rocha, Luiz Alberto

Abstract

Brazil has a different energy matrix from the world, from electricity generation with renewable resources. With the increase in energy demand, environmental problems of hydroelectric plants show a need to increase the installed capacity of renewable sources. Investments in renewable generation are required, decision affected by different aspects, such as variability in generation, uncertainties in the energy market and investor risk aversion, the company’s current portfolio. The paper presents a stochastic decision support model for renewable energy investments, maximizing the expected return for a given level of risk aversion. To assess uncertainties, the Conditional Value-at-Risk (CVaR) is used. Scenarios are generated based on past generation and NEWAVE output data. Simulations with the investment option are related in this energy complementation. The risk for intermittent source involves the company using CVaR assessment. The results conclude that the diversification of the firm’s assets and the complementary composition of the sources of generation reduce the investor’s portfolio’s financial risks and the risk aversion level of the decision maker influences the market position that the company must adopt. Model tending to more conservative solutions when risk aversion is higher, confirming the literature, the existence of a trade-off between risk aversion and expected return.

Suggested Citation

  • de Freitas, Renan Alves & Vogel, Ederson Paulo & Korzenowski, André Luis & Oliveira Rocha, Luiz Alberto, 2020. "Stochastic model to aid decision making on investments in renewable energy generation: Portfolio diffusion and investor risk aversion," Renewable Energy, Elsevier, vol. 162(C), pages 1161-1176.
    • Handle: RePEc:eee:renene:v:162:y:2020:i:c:p:1161-1176
    DOI: 10.1016/j.renene.2020.08.012
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    References listed on IDEAS

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    Cited by:

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    9. Wenjiao Zai & Yuying He & Huazhang Wang, 2023. "Risk Prediction Method for Renewable Energy Investments Abroad Based on Cloud-DBN," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
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