Hydropower producers need to schedule when to release water from reservoirs and participate In wholesale electricity markets where the day-ahead production Is physically traded. This lecture will view the bidding problem of hydropower producers as an application of stochastic programming. There is uncertainty in both spot market prices and inflow to the reservoirs. The presence of reservoirs also means that the short-term problem of determining bids for the next 12-36 hours is a part of a long-term problem in which the question is whether to release water now or store it for the future. This multi-scale challenge is usually addressed by using several models for hydropower planning, at least one long-term model and one short-term model. The talk will discuss construction of market price scenarios and explain the development of a stochastic mixed-integer linear programming model that takes in both production and physical trading aspects. 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.
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