Risk averse two-stage stochastic optimization for the electric power generation capacity expansion problem

We consider the optimal electric power generation capacity expansion problem, over a multiyear time horizon, of a price-taker power producer who has to choose among thermal power plants and power plants using renewable energy sources (RES), while taking into account regulatory constraints on CO2 emissions, incentives to generation from RES and risk due to fuel price volatility which affects the generation variable costs. A two-stage stochastic mixed integer model is developed that determines the number of new power plants for each chosen technology, as well as the years in which the construction of the new power plants is to begin. The solution allows determining the evolution of the power producer’s generation system along the time horizon, so that the expected total profit is maximized, with revenues from sale of electricity and of Green Certificates and costs for the annual debt repayment of new power plants, purchase costs of CO2 emission permits and of Green Certificates, fixed and variable production costs of new power plants and of power plants owned by the producer at the beginning of the planning period. Alternative risk measures are considered and tested.