Regulation Strategy of Virtual Power Plant in the V2G-based Highway Scenario

This paper studies the internal load scheduling optimization model of a virtual power plant (VPP) in a highway scenario based on V2G (Vehicle-to-Grid) technology. In response to the problem of the collaborative and complementary utilization of multiple user-side resources in the VPP, based on the consideration of the carbon emission costs during the entire life cycle of electric vehicles and the output of distributed energy, this paper proposes a carbon emission cost model for the VPP under the low-carbon goal. The VPP minimizes the cost as the objective function and constructs a multi-objective optimization model that comprehensively considers the carbon cost of the virtual power plant and the demand response of the user side. An economic scheduling strategy including power interaction between virtual power plants is constructed. The model is solved using the velocity-suspended particle swarm algorithm and verified through simulations on the existing experimental platform. The case study analysis shows that as the depth of VG participation increases, the overall operating cost and carbon emissions of the system significantly decrease, verifying the feasibility and economy of the model.