A Coordinated Operation Strategy for Multi-Virtual Power Plants and Load Aggregation Under Electricity Market Gaming

Abstract

The increasing penetration of renewable energy sources introduces significant uncertainty into power system operation, challenging the market participation and coordination of virtual power plants. This paper proposes a risk-aware dynamic pricing framework based on a cooperative Stackelberg game to optimize the interaction between a load aggregator and multiple virtual power plants. The upper-level load aggregator employs Conditional Value-at-Risk to quantify trading risks and determines differentiated pricing signals to incentivize virtual power plants participation in energy and reserve markets. The lower-level structure separates physical operation from cooperative settlement: VPPs first solve a convex operational scheduling problem involving peer-to-peer energy trading, demand response, and continuous battery dispatch under scenario uncertainty, and the cooperative surplus is then allocated through a weighted bargaining rule. This layered structure preserves the leader–follower pricing logic while providing a mathematically consistent basis for the KKT-based reformulation of the physical dispatch subproblem. Simulation results demonstrate that the proposed framework achieves balanced pricing, fair profit distribution, and effective risk mitigation under high wind power uncertainty, providing a scalable decision-making tool for coordinating renewable-dominated electricity markets.