A Coordinated Charging Control Strategy For Electric Vehicles Charging Load In Residential Area

The problem of energy crisis and environment pollution is becoming more and more severe recently. The application of electric vehicle (EV) is bound to be the future trend of industry. With the widespread applications of EVs, especially for household EV, residential area will be a major charging place in the future. Although the government has offered many favorable policies to promote EVs, there are still practical problems, for example, the residential property is not willing to be involved in the construction of EV charging piles considering operation cost and safety issue, which will greatly block the application of EVs. There are two crux of this problem here:first, with more and more EVs connected to grid disorderly, there charging load will possibly lead to transformer overload and cause safety risk; second, due to the expensive operation costs and insufficient charging profit, it is hard to motive operators to participate. What’s more, the expensive charging expenses of EV will also influence potential customers.Therefore, a coordinated control strategy for EV charging load is studied, which is mainly aimed at avoiding transformer overload and maximizing charging income. First, a flexible method, named grid picking method is proposed to conveniently satisfy transformer capacity and plan the charging period. Second, take minimizing charging expenses as the objective function based on time-of-use electricity price, and design the method and flow of an optimal charging control strategy using the genetic algorithm. Lastly, using Monte Carlo method to simulate and analyze cases in point. Results show that the implication of transformer capacity limits of the grid picking method can simplify the coordinated charging plan and make it more suitable for solution by the optimization algorithm. The coordinated charging strategy can effectively shift peak load and reduce charging expenses, thereby increasing charging revenues and initiative to operate. To validate the influence of distributed EV charging load on distribution network, this paper builds a IEEE33 model and analyzed how the coordinated and uncoordinated charging load influence the feeder load, power loss and node voltage in this model, therefore, indicated the optimization effect of this coordinated control strategy in terms of distribution network.On this basis, considering the habit of customers’ charging and operators’ supervision, this paper designed and established a charging management system with a built-in coordinated charging strategy. With its information interaction and resources sharing, this system builds the connection between customers and grid and achieves the unified control of charging piles, which is highly beneficial to the EV charging management and has showed the practical application value of this study well.