Risk aversion approach for energy trading based on multistage stochastic programming

Abstract

This paper presents a methodology to define the trading policy of an energy generation agent. The proposed approach uses stochastic programming to represent the uncertainty related to the short-term price fluctuation. The aim of the model (based on possible prices) is to identify the composition of an optimum portfolio in accordance with the decision-maker risk perception. The most important contribution of this paper is the fact that the risk criteria are considered in the decision-making model. This is done through the use of tools such as Value at Risk (VaR) and the Conditional Value at Risk (CVaR). Despite the fact that the calculation of CVaR requires previous knowledge of VaR, in the proposed model both risk measures are simultaneously determined.