Maximization of Expected Wind Power Plant Profit Through Optimal Offers on the Day-Ahead Market
Abstract
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.
Damir Jakus
Full Professor | Department of Power Grids and Substations
Researcher and a full professor at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split. His research interests include power system optimization and planning, RES integration, electricity market modeling.
Josip Vasilj
Associate Professor | Department of Power Grids and Substations
Researcher and Associate Professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, where he teaches courses related to engineering economics, power system analysis, power grids and machine learning. His research focus is the application of advanced numerical methods to problems in the analysis and planning of power system operations.
