Multi-Objective Scheduling of Electric Vehicles and Distributed Generation in Smart Distribution System

One of the proposed solutions to increase the penetration of Renewable Energy Sources (RES) in the power system is the use of Electric Vehicles (EVs) potential. The use ofEVs in the smart distribution system requires the management of charging/discharging power of them. In this paper, the multiobjective scheduling of EVs in the presence of Distributed Generation (DG) in the smart network is investigated. The objective functions are the minimization of the operation cost and the amount of power system emission. The Monte Carlo method has been used to apply the uncertainties of renewable resources. In this study, the Gray Wolf Optimizer (GWO) algorithm is used to solve the scheduling problem. As well as, the fuzzy method is used to solve the multi-objective optimization problem. The performance of the proposed method is evaluated on the IEEE 33- bus distribution system in a 24-hour period, taking into consideration the operational constraints of the power system, DG, and EVs. The results of simulation show the high performance of the proposed method in the planning of resources and improving the efficiency of distribution system by optimal operating of EVs and DG.

کلیدواژه ها:

Multi-objective Scheduling ، Electric vehicles ، Distributed generation ، Gray wolf optimizer algorithm.