Maximization of Expected Wind Power Plant Profit Through Optimal Offers on the Day-Ahead Market

In the electricity markets every deviation between the contracted power production and the real energy supplied is usually penalized or paid according to the market prices. This gives incentive to the market participants to provide accurate production schedules. Wind power producers (WPP) can generate production forecasts with limited accuracy due to wind nature itself. In the markets where WPP are treated as a balance responsible parties they will account for the day-ahead market prices and balancing energy prices when placing market bids in order to maximize their profit. This paper presents mixed integer optimization model for the optimal bidding of WPP production in the day-ahead market in order to minimize imbalance costs. The uncertainty related to the market prices on the day-ahead and balancing markets as well as WPP forecasts is accounted for by considering large scenario set which is than reduced by applying the fast forward scenario reduction algorithm.