A Novel Category-Specific Pricing Strategy for Demand Response in Microgrids

Abstract

Setting different electricity prices for different types of loads can effectively reduce the peak power consumption in microgrids (MGs). This paper proposes a category-specific pricing strategy for demand response program in dynamic MGs that can efficiently utilize renewable energy to achieve peak shaving and valley filling via establishing a Stackelberg game model. A state characteristic clustering (SCC) based non-intrusive load monitoring (NILM) scheme is first proposed, by which both the MG market operator (MMO) and users can access the detailed power consumptions of shiftable and non-shiftable loads. MMO then specifies detailed electricity prices dynamically based on user-side demand and satisfaction feedback, while users adjust their shiftable loads in a timely manner accordingly. Through solving the game optimization problem, the uniqueness and existence of the Stackelberg equilibrium is derived. Moreover, a distributed solution algorithm is presented to seek the unique equilibrium. Finally, a real residential power dataset is used to verify the effectiveness of the proposed category-specific pricing strategy. Numerical results show that the strategy reduces the peak-valley difference significantly, mitigates the power imbalance, and improves the utility of MG participators.