Implementation of price-based demand response programs through a load pattern clustering process

This study addresses the problem of the optimal design of price-based Demand Response (DR) programs such as Real-Time Pricing (RTP) utilizing the load profiling tool. The proposed model corresponds to a profit maximization problem of a retailer that serves a group of residential consumers. Through a clustering process the consumers are grouped together in several clusters. For each cluster a dynamic tariff is offered that is specially design to fit to the typical load pattern of the cluster. The sensitivity of the demand over the offered selling price is modeled through a price responsive demand function. Apart from implementing different demand functions, the flexibility of the proposed model offers a selection of different clustering algorithms and different retailer pricing policy.