Maintenance scheduling is an important and complex task in hydropower systems. In a liberalized market, the generation company will schedule maintenance periods to maximize the expected profit. This paper describes a method for hydropower maintenance scheduling suitable for a profit maximizing, price-taking and risk neutral hydropower producer selling energy and reserve capacity to separate markets. The method uses Benders decomposition principle to coordinate the timing of power plant maintenance with the medium-term scheduling of the hydropower system, treating inflow to reservoirs and prices for energy and reserve capacity as stochastic variables. The proposed method is applied in a case study for a Norwegian watercourse, and results, in terms of maintenance schedules and computational performance, are presented and discussed.

We study a hydropower producer’s potential for value-creation from multi-market trading given the price variations in the markets and the flexibility provided through access to hydro reservoirs. We use a perfect foresight optimization model for a price-taking hydropower producer co-optimizing his trades in the day-ahead, intra-day and balancing markets. The model is used on real market data from Norway, Sweden and Germany. The study shows a theoretical potential for added value when selling energy in multiple markets relative to optimal day-ahead sale. Most of this value is achievable also when the perfect foresight is limited to the period from day-ahead bidding until operation. Flexible production plants achieve the largest relative added values for multi-market sales, and has the largest benefit from a long horizon with perfect foresight.

We present a model for optimal trade in a weekly power reserve market under day-ahead and balancing market price uncertainty. The model takes the perspective of a price-taking hydropower producer and a case study for the Norwegian market design and a Norwegian multi-reservoir water course for a winter week is presented. We demonstrate how a bid curve for the reserve market can be established through a sensitivity analysis on reserve prices, and observe that the optimal trade in the succeeding day-ahead and balancing market is highly sensitive to the reserve obligation.