Portfolio optimization of renewable energy assets: Hydro, wind, and photovoltaic energy in the regulated market in Brazil

Daywes Pinheiro Neto, Elder Geraldo Domingues, António Paulo Coimbra, Aníbal Traça de Almeida, Aylton José Alves and Wesley Pacheco Calixto

Energy Economics, 2017, vol. 64, issue C, 238-250

Abstract: This study proposes a methodology for risk analysis and portfolio optimization of power generation assets with hydro, wind, and solar power, considering the Regulated Contracting Environment and the Mechanism for Reallocation of Energy in Brazil. Innovative stochastic models are used to generate synthetic time series for the random variables water inflow, wind speed, solar irradiance, temperature of the photovoltaic panel, and average generation capacity of the Mechanism for Reallocation of Energy. The simulation is implemented using the Monte Carlo method associated with a Cholesky decomposition. An economic approach is presented taking into account taxation and financing, as well as the Markowitz Portfolio theory. The results show that the initial correlation between the energy resources is altered by the cash flow model and mainly by the debt. In the diversification process, the complementarity between sources helps to reduce the economic risk. The increase in debt increases the correlation, decreases the return and risk and, consequently, affects the diversification process and economic results. The Mechanism for Reallocation of Energy significantly reduces the hydroelectric economic risk and increases the financial return, which directly benefits the formation of portfolios.

Keywords: Monte Carlo method; Renewable energy; Risk analysis; Mechanism for reallocation of energy; Portfolio optimization (search for similar items in EconPapers)
JEL-codes: C10 C51 C52 C53 C63 Q40 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:64:y:2017:i:c:p:238-250

DOI: 10.1016/j.eneco.2017.03.020

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