Distributionally robust optimization for virtual power plant clusters considering carbon emission-based dynamic dispatch priority

Abstract

A virtual power plant (VPP) is an effective way to manage distributed energy resources. Virtual power plant cluster (VPPC) is constructed due to the increasing number of VPPs. It has great potential in carbon emission reduction through coordination between VPPs. Therefore, a dynamic dispatch priority model is proposed. The model adjusts the dispatch sequence of VPPs based on carbon emissions. The higher the carbon emissions, the lower the dispatch priority. The VPPC participates in carbon trading and the carbon trading cost is included in the optimization objective. There are still many uncontrolled distributed energy resources, e.g., wind power, out of the VPPC. The distributionally robust optimal method is used to deal with the uncertainty of wind power. Finally, this paper proposes a two-stage distributionally robust optimal model of VPPC considering carbon emission-based dynamic dispatch priority. This model can be solved by the column-and-constraint generation (C&CG) algorithm. A VPPC with four VPPs is used in case studies, which verify the economic benefit and low carbon of the proposed model.