Optimal Scheduling of Multi-Energy Virtual Power Plants Considering Multi-Type Demand Response

Integrating demand response into virtual power plants can enhance their flexibility and economic efficiency, but the inherent uncertainty of demand response poses challenges for scheduling and operation. Moreover, research on applying multiple demand response types in virtual power plants remains limited. To address these issues, this paper proposes an incentive-based demand response model incorporating a benefit coefficient that adjusts incentive compensation to reduce payouts under unsatisfactory demand response performance, as well as a replaceable-based demand response model considering customer satisfaction to better reflect its influence on replaceable demand response. Finally, a multi-energy virtual power plants model integrating multiple demand response types is established, considering three demand response strategies to achieve superior optimization. Case studies demonstrate that the incentive-based demand response model considering the benefit-coefficient can improve economic efficiency of the system, and the replaceable-based demand response model considering customer satisfaction can more accurately capture potential load variations to enhance demand response precision, and the coordinated participation of multiple demand response types in virtual power plant scheduling yields optimal overall performance.