Bidirectional Matching Model of Virtual Power Plant and Distributed Resources Considering Multiple Uncertainties

With the large-scale emergence of distributed energy resources (DERs), the difficulty of grid dispatching has increased dramatically. The aggregation of DERs can continuously expand the scale of virtual power plants (VPPs), reduce the complexity of grid scheduling, and promote the further development of VPPs. First, the multiple uncertainty of wind power, PV, and load within VPP is handled using multi-scenario techniques, and based on calculating uncertainty-based VPP revenue models. Second, the expectation factor-based DER selection VPP model and the cooperative propensity-degree based VPP selection DER model are proposed, respectively. Then, the Gale-Shapley algorithm is used to implement the two-way matching model between VPP and DER. Finally, the effectiveness of the proposed model is verified by arithmetic examples.