Novel Electric Vehicle V2G Control Strategy for Weak Communication Scenario

Communication obstacles between Vehicle-to-Grid (V2G) piles and microgrid hinder the sustainable implementation of orderly charging and discharging. This paper proposes a vehicle-grid cooperative framework, which ensures microgrid stability and improves economic efficiency under communication constraints. The implementation steps are as follows: First, the Monte Carlo method is applied to generate base load and photovoltaic data, and k-means clustering is adopted for scenario simplification. Second, an economic objective function covering power generation costs, electricity purchase and sales expenses, and electric vehicle (EV) discharging losses is constructed to achieve day-ahead optimal scheduling. Finally, a probability-guided EV V2G strategy is proposed, and the Improved Particle Swarm Optimization (IPSO) algorithm is used to calculate the optimal guidance probability of piles at future moments, thereby enabling offline EV scheduling under communication constraints. Simulation verification based on the IEEE 33-bus system shows that this method can still effectively sustain the V2G strategy under communication constraints and exhibit excellent performance.