A long timescale sensorless sequential charging method based on a large-scale electric vehicle distribution network support type

We study the long-term large-scale electric vehicle (EV) sensorless orderly charging method based on distribution network support to balance grid load and improve EV charging efficiency. Large-scale EVs are connected to the reactive power-supported distribution network from the point of common coupling and a reactive power-supported large-scale EV distribution network-supported grid-connection architecture is established. Based on this, a long-term sensorless charging optimization model is constructed, with the minimization of the operational cost of the supporting distribution network as the upper-level objective and the minimization of plan execution deviation penalties as the lower-level objective. Constraints such as active/reactive power balance in the distribution network, EV state-of-charge limits, and charging station capacity limits are incorporated into the model. The particle swarm optimization algorithm is employed to solve the proposed charging optimization model and output the optimal EV charging scheme. The experimental results demonstrate that the method effectively reduces the grid’s peak-to-valley difference and EV users’ queuing time is reduced by over 20%.