The impact of the spot price modeling on the electricity portfolio optimization problem

Previous studies in the literature have suggested that, in deregulated markets, large consumers may adopt stochastic programming for the optimization of their electricity portfolio. Nevertheless, there may be several modeling approaches, characterized by different assumptions on the stochastic behavior of the spot price. Such different approaches could lead to different solutions of the electricity portfolio optimization problem. Besides, these solutions could vary also because of the impact of the risk aversion of each large consumer. In this paper, we then investigate how different spot prices model can lead to different solutions, generalizing the Value of the Stochastic Solution (VSS). Our aim is to build a decision support system that suggests the optimal procurement policy by using the most suitable spot prices model, based on the risk aversion of the decision maker. We evaluate our technique in a realistic case study in which the portfolio optimization problem is modeled as a two-stage problem solved with the Sample Average Approximation method.