Research on multi-objective EV charging task sequence optimization modeling

With the rapid increase in the number of Electric Vehicles (EVs), the disorderly access of a large number of EVs to the distribution network for charging will cause a certain degree of impact on the safe and economic operation of the distribution network, and may even cause problems such as load "peak on peak", node voltage crossing, excessive network loss, and deterioration of power quality. Many problems. Therefore, an effective charging strategy must be adopted to guide the EV charging in an orderly manner and eliminate the impact of EV disorderly charging on the grid. Even, the economy of distribution network operation can be significantly improved under the orderly charging control strategy.To this end, a multi-objective EV grid-connected charging and discharging optimization control strategy is proposed in this paper. Firstly, the EV orderly charging problem is described in detail and a mathematical model of EV orderly charging and discharging is established. Secondly, based on the traditional Greedy Random Adaptive Search Procedure (GRASP) algorithm, a hybrid GRASP-PR algorithm is formed to realize the EV orderly charging and discharging optimal control strategy, and with the objective of minimizing the operating cost of the distribution network and other conditions, a hybrid GRASP-PR algorithm based on The multi-objective EV charging task sequence optimization model based on the GRASP-PR hybrid algorithm is established with the objective of minimizing the operating cost of the distribution network. Finally, a simulation model of the distribution network system with grid-connected EV charging based on IEEE33 nodes is established, and the simulation results verify that the proposed multi-objective hybrid algorithm can achieve the optimization of EV charging in an orderly manner, which is beneficial to the safe and economic operation of the distribution network.