Optimal Scheduling For Electric Vehicles In A Distribution System With Photovoltaic Units And Planning For Charging Facilities

In recent years,the electric vehicle(EV)industry has developed rapidly,and the penetration rate has increased year by year.The EV coordinated charging strategy is a key to reduce the negative impacts of the charging load on the power system concerned.On the other hand,charging failities planning determines their efficiency and the convenience of EV users.A coordinated charging strategy is presented for EVs in the distribution system with three-phase unbalanced PV power inputs.First,the charging load is modeled based on the travelling behavior and charging characteristic of EVs.Then,based on the three-phase power flow model of the distribution system,an EV coordinated charging strategy is proposed with the objectives to optimize the daily load profile and to minimize the three-phase imbalance degree in the distribution system.The relevant decision variables include the charging phase,charging power and charging time of EVs.The formulated optimization model is solved by using the adaptive genetic algorithm.Finally,a modified IEEE 33-bus distribution system is employed to demonstrate the proposed method.An optimal scheduling strategy for EVs and photovoltaics(PVs)in dynamic time-of-use(TOU)tariff environment is proposed.The charging/discharging schedules are optimized by EV users/agents with the objective to minimize the charging cost and maximize the discharging profit.Then,the regional operator adjusts the schedule in order to enhance the usage of the PV power output locally.TOU tariffs are updated at set intervals,and can guide charging/discharging schedules of EVs so as to improve the load profile.Finally,a distribution system with 3 residential communities is employed to demonstrate the effectiveness of the proposed method.A collaborative planning strategy for integrated power distribution systems and centralized EV charging stations is proposed based on the Voronoi method.In the developed model,the annual cost of charging stations,EV driving and investment on distribution systems is minimized.The service range of centralized charging station is divide by Voronoi diagram.And load of each charging station is determined by the daily charging load of the existing typical charging station and service range.Finally,the developed model is solved by using the adaptive genetic algorithm combined with the Voronoi diagram.