Stochastic programming for optimizing bidding strategies of a nordic hydropower producer
Fleten, Stein-Erik
Kristoffersen, Trine Krogh
From the point of view of a price-taking hydropower producer participating in the day-ahead power market, market prices are highly uncertain. The present paper provides a model for determining optimal bidding strategies taking into account this uncertainty. In particular, realistic market price scenarios are generated and a stochastic mixed-integer linear programming model that takes in both production and physical trading aspects is developed. The idea is to explore the effects of including uncertainty into the optimization model and to compare the stochastic approach to a deterministic one. The model is illustrated with data from a Norwegian hydropower producer and the Nordic power market at Nord Pool.