A Coordinated Charging Model for Electric Vehicles in a Smart Grid using Whale Optimization Algorithm

In this study, we focused on the optimal coordinated charging of electric vehicles in a centralized charging model, based on a special multi-objective model. The objective functions are charging cost minimization, load variance minimization, and power loss minimization. The multi-objective problem has been solved by the Whale Optimization Algorithm (WOA). In the proposed approach, the probability density function was used to characterize a single EV (e.g. driving distance). For each time step, the optimal load variance is calculated. The WOA was compared to other optimization algorithms, and was tested on the IEEE 33-bus test distribution network. The simulation results suggest that the proposed framework can through the objective function, improve grid performance and simultaneously encourage EV drivers to participate in a centralized coordinated charging system. The WOA gives a superior performance in both grid performance and economic benefits. Compared to the uncoordinated charging system, the WOA outperforms other tested algorithms with a 90% minimization of charging cost. The WOA also reduces the real power loss more than the BAT, GWO, GWOCS, and PSOGWO.