Abstract
In recent years, the difficulty of charging schedules for electric vehicles (EVs) in viable parking lots has become a major problem, First of all, there is a smart charging control system. The problem of optimization of charging is conceived as a cost minimization problem. Adaptive utility-oriented scheduling is then applied as a method to find the right solution. In view of the restriction conditions in the optimization problem, an improved adaptive utility-oriented scheduling is suggested which may increase the convergence speed and optimization accuracy. Finally, a scheduling strategy for short-term PV forecasts and IBGWO for real-time EV charging is implemented. To test the effectiveness of the planned approach, it simulates several scenarios. The experimental findings indicate that the proposed algorithm is superior to other meta-heuristic algorithms when it comes to solving the proposed charging scheduling problem. In addition, the proposed plan would ultimately increase the rate of PV usage and reduce the cost of energy to operators.
Published Version
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