Optimal Operation Strategy of Virtual Power Plant in Spot-Peak Regulation Auxiliary Service Market

This study proposes an optimized virtual power plant (VPP) operation strategy for peak regulation ancillary services, enhancing power system flexibility and economic efficiency through coordinated management of distributed energy resources (DERs). A VPP aggregation model is developed, incorporating distributed generation, energy storage, and demand-responsive loads. An economic-maximization scheduling model is formulated using mixed-integer linear programming (MILP), accounting for peak regulation incentives, operational constraints, and electricity price variations. Simulation results demonstrate that the approach improves peak-shaving capability, reduces operating costs, and increases renewable energy utilization, offering a viable solution for VPP participation in electricity markets. The findings provide both theoretical and practical insights for real-world VPP implementations.