Optimized charging strategy for large-scale electric vehicles

Electric vehicles (EVs) have gained support from many governments, including China, due to their low-carbon, oil-independent and environmentally friendly characteristics. However, many EVs connected to the grid for charging will significantly burden the grid. In this paper, considering the actual situation, we propose a control strategy centered on EV users and supplemented by the power grid. Under the premise of guaranteeing users' demand, we establish mathematical models to reduce users' expenses and the peak-to-valley difference of the power grid and improve the particle swarm optimization algorithm to obtain better performance. We have verified the feasibility of the proposed strategy with examples, prioritizing the state of charge (SOC) of EVs even if the electricity price is expensive because EV users are more concerned about the EV SOC. The proposed strategy has a positive significance in reducing the cost and the grid's peak-to-valley difference. The strategy has an excellent prospect for application because it takes into account the actual situation of large-scale charging of EVs.