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.
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