Optimization Strategies for Virtual Power Plants Based on Carbon Credit Constraints and Electric Vehicle Load Scheduling

Virtual power plants (VPPs) optimize power resource scheduling by integrating distributed energy and controllable loads. To improve electric vehicle (EV) participation and reduce carbon emissions, this study proposes a novel VPP regulation strategy. The model uses gas turbines for regulation while optimizing EV charging, incorporating carbon credits to maximize VPP benefits through electricity market prices, carbon allowances, and penalties. Solved via particle swarm optimization and binary particle swarm optimization algorithms, it ensures optimal EV charging sequences and thermal power adjustments. Numerical analyses and results demonstrate that the proposed approach effectively reduces carbon emissions while enhancing the economic benefits for both the VPP and EV owners.