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.

中文翻译：

---

微电网需求响应的新型特定类别定价策略


针对不同类型的负荷设定不同的电价可以有效降低微电网（MG）的峰值用电量。本文提出了一种针对动态MG需求响应计划的特定类别定价策略，通过建立Stackelberg博弈模型，可以有效地利用可再生能源实现调峰填谷。首次提出了基于状态特征聚类（SCC）的非侵入式负载监控（NILM）方案，通过该方案，MG市场运营商（MMO）和用户都可以获取可移动和不可移动负载的详细功耗。 MMO根据用户侧的需求和满意度反馈，动态制定详细电价，同时用户及时调整可转移负荷。通过求解博弈优化问题，推导出Stackelberg均衡的唯一性和存在性。此外，提出了一种分布式求解算法来寻求唯一平衡。最后，使用真实的住宅电力数据集来验证所提出的特定类别定价策略的有效性。数值结果表明，该策略显着减小了峰谷差，缓解了功率失衡，提高了MG参与者的效用。