Demand response model and potential prediction of load aggregators

Demand response (DR) serves as an important mechanism for smoothing load curves by effectively reducing peak electricity demands and increasing the load during off-peak hours, thereby mitigating unnecessary investments in power system infrastructure. Although DR has been extensively utilized by large electricity consumers, its application among small-to-medium-scale electricity customers remains relatively limited. This paper emphasizes the analysis of small-to-medium-scale electricity customers participating in electricity market operations with the support of load aggregators (LAs). Initially, the paper proposes a specialized demand response model that allows load aggregators to actively integrate small-to-medium-scale electricity customers into electricity market competition. Then, according to the extent of control exerted by the load aggregator on user-side resources, electrical appliances and devices are categorized into fully controllable and partially controllable types, and corresponding methods for forecasting the demand response potential (DRP) are introduced. Subsequently, a static game model characterized by incomplete information is developed to determine optimal bidding decisions in the upper-level wholesale market, along with a complementary optimal bidding model for participation in the lower-level retail market. Lastly, empirical data collected from a substantial residential community is applied to demonstrate the proposed method, and the results clearly indicate its economic efficiency and practical effectiveness.