A Risk Averse Stochastic Optimization Model for Wind Power Plants Portfolio Selection

Abstract

This work focuses on the wind power plants portfolio selection. We developed a stochastic optimization model whose objective function considers the financial risk and return, weighted by the risk aversion profile of the decision-maker. The financial risk is measured by the Conditional Value-at-Risk metric. The agent risk aversion profile brings important implications for resource allocation strategy definition. We apply the model in a case study considering sixteen locations in Brazil, where optimal portfolios compositions are analyzed under risk aversion levels, from the perspective of a risk-neutral agent (decision based only on the Expected Revenue) up to risk-averse (decision based only on CVaR), considering intermediate levels of these extremes. The results showed relevant changes in the portfolio allocation under different risk aversion levels. The model application contributes to discussions on this relevant subject and for mapping potential strategic association between wind power plants in Brazil. The model can be effortlessly adapted for applications in any location worldwide.