Decoupling Based Customer Baseline Load Estimation Method Considering Cross Effects of Composite Demand Response Programs

As the basis of incentive-based demand response (DR) settlement, accuracy customer baseline load (CBL) estimation is crucial. As the marketization process advances, there are cases where users participate in both price-based DR and incentive-based DR at the same time. Two types of demand response are coupled together, making it difficult for existing CBL estimation methods to accurately extract load characteristics. If the additional factors introduced by composite DR are not taken into account, using traditional methods for estimating CBL will result in significant deviations. Therefore, this paper reveals the mechanism of error generation in existing estimation methods. And based on consumer psychology, this paper proposes a CBL estimation method that decouples the user’s historical load pattern and the impact of electricity prices on the load. In order to make a preliminary estimation of the CBL, this method first constructs a load dataset without considering the impact of electricity prices. Then, based on consumer psychology demand response models, it calculates the load changes caused by price-based DR. Finally, it combines the two to obtain the final CBL estimation results. Simulation experiments show that the proposed method can obtain accurate estimation results under composite DR.