Optimal scheduling of microgrid-based virtual power plants considering demand response and capacity withholding opportunities

Abstract

This work addresses a stochastic framework for optimal coordination of a microgrid-based virtual power plant (VPP) that participates in day-ahead energy and ancillary service markets. The microgrids are equipped with different types of distributed energy resources. A two-stage optimization formulation is proposed to maximize the benefit of the virtual power plant and minimize the energy procurement costs of the Distribution System Operator (DSO). The proposed model determines the optimal commitment scheduling of energy resources, considering the capacity withholding opportunities of the VPP that should be detected by the DSO. To evaluate the effectiveness of the proposed model, the algorithm is assessed for the 123-bus IEEE test system. The results show that the proposed method successfully maximizes the virtual power plant profit considering capacity withholding penalties.