Aggregating Energy Storage in Virtual Power Plant and Its Application in Unit Commitment

In order to give full play to the positive role of distributed energy storage systems in renewable energy grids, this paper studies the optimization of unit portfolios with virtual power plants. A distributed energy storage flexibility interval aggregation method based on Minkowski Sum and convex edge detection is proposed to aggregate multiple distributed energy storage into a virtual power plant. In this paper, the multi-objective particle swarm optimization algorithm is adopted to solve the multi-objective optimization problem of optimal output and energy storage charging and discharging successfully by considering the conventional constraints of horizontal parallel units and the energy conservation and capacity constraints of longitudinal energy storage in the same scheduling interval. The results of case studies show that the virtual power plant scheduling scheme optimized by MOPSO has a significant effect on peaking and valley filling, eliminating renewable energy and reducing operating costs.