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

被引:50
|
作者
Neto, Daywes Pinheiro [1 ,2 ]
Domingues, Elder Geraldo [1 ]
Coimbra, Antonio Paulo [3 ]
de Almeida, Anibal Traca [3 ]
Alves, Aylton Jose [1 ]
Calixto, Wesley Pacheco [1 ,2 ]
机构
[1] Fed Inst Goias, Nucleus Expt & Technol Studies NExT, BR-74055110 Goiania, Go, Brazil
[2] Univ Goias, Sch Elect & Comp Engn, BR-74605010 Goiania, Go, Brazil
[3] Univ Coimbra, Dept Elect & Comp Engn, ISR, P-3030290 Coimbra, Portugal
关键词
Monte Carlo method; Renewable energy; Risk analysis; Mechanism for reallocation of energy; Portfolio optimization; GENERATING PORTFOLIO; POWER; SPEED; RISK; TEMPERATURE; PERFORMANCE; MODULES; PV;
D O I
10.1016/j.eneco.2017.03.020
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:238 / 250
页数:13
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