A Multi-stage Stochastic Programming Model for Managing Risk-optimal Electricity Portfolios

We present a multi-stage decision model, which serves as a building block for solving various electricity portfolio management problems. The basic setup consists of a portfolio optimization model for a large energy consumer, which has to decide about its mid-term electricity portfolio composition. The given stochastic demand may be fulfilled by buying energy on the spot or futures market, by signing a supply contract, or by producing electricity in a small plant. We formulate the problem in a dynamic risk management-based stochastic optimization framework, whose flexibility allows for extensive parameter studies and comparative analysis of different types of supply contracts. A number of application examples is presented to outline the possibilities of using the basic multi-stage stochastic programming model to address a range of issues related to the design of optimal policies. Apart from the question of an optimal energy policy mix for a large energy consumer, we investigate the pricing problem for flexible supply contracts from the perspective of an energy trader, demonstrating the wide applicability of the framework.