A Dynamic Pricing Strategy for Aggregators Considering the Response Potential and Real-time Contribution of Local Market Users

In the context of a new power system, aggregators can aggregate locally adjustable customers to participate in demand response, with aggregators receiving aggregation revenues and customers receiving incentive pricing to reduce electricity costs. However, the aggregator's pricing strategy is sloppy and fails to fully tap the potential of high-quality adjustable resources, making it difficult to realize the value sharing between high-quality resources and the aggregator. Aiming at the above problems, this paper proposes a dynamic pricing strategy for aggregators considering the response potential and real-time contribution of local market users. Taking different types of node users as the research object, the entropy weight method is applied to evaluate the response potential of users, considering the key response indexes such as load rate, time elasticity, price elasticity, and response reliability. On this basis, the incentive price is formulated with differentiation by comprehensively considering the user response potential and the contribution to the aggregator's revenue. Then, local market users with aggregation potential and value are precisely screened. Example analysis results show that the method proposed in this paper can improve the aggregator's aggregation revenue by about 19.27%, meanwhile, improves the response revenue and response motivation of high-quality resources.