Social Evolutionary Programming Algorithm onUnit Commitment in Wind Power Integrated System

Social Evolutionary Programming algorithm based on a Social Cognitive Model is proposed in this paper. The uphill and downhill spinning reserves are introduced to cope with the power imbalances caused by wind fluctuation on the premise of full utilization of wind energy. The proposed algorithm has an advantage in the convergent stability and computational efficiency. Since climbing rates constraints have impacts on both start-up & shutdown schedules of generating units and the economic dispatch based on a fixed schedule, two different ways are put forward to calculate UC problem containing climbing rates constraints. Simulation results of a 10-unit system show that such a Social Evolutionary Programming algorithm can effectively cope with the change of reserve requirement due to the grid-connection of wind farm, and meet the multiple requirements of UC and dispatching.