Coordinated Charging Strategy For Electric Vehicles Based On Demand Response

With the development of society and the improvement of people's living standard,cars have been available to thousands of households.However,the rapid growth of the number of cars results in two major problems that are the environmental pollution and energy shortage.With the advantages of high efficiency,environmental protection and energy saving,electric vehicles have become the main trend of the development of the automobile industry.However,due to the randomness and uncertainty of the charging time and location of the electric vehicle,the disorder charging will bring new challenges to power grid,affect the stability of the power system,and reduce the power quality.Therefore,it is very important to study the optimization strategy of electric vehicle charging.In order to reduce the effect of disordered charging on power grid,an optimal control strategy for the coordinated charging of electric vehicles based on demand response is proposed in this paper.The main research work is shown as following:(1)According to the charging characteristics of electric vehicle,the charging mode and charging power of electric vehicle are analyzed,and the main types of electric vehicle are classified,and that the charging load model of electric vehicle is established.Based on the vehicle travel statistics released by Beijing Transportation Development Research Institute,Monte Carlo simulation is used to simulate the charging demand of electric vehicles and the charging load is superimposed on the basic load of the distribution network.Then the disorder charging load of the electric vehicle is analyzed.The simulation results show that: large scale electric vehicle charging will aggravate the load fluctuation of distribution network,increase load peak and valley difference,and that is not conducive to the stable and economic operation of distribution network.In addition,the higher the occupancy rate of electric vehicle,the more adverse effects it will bring.(2)The electric vehicle charging area control scheme is proposed with the optimization goal of the lowest cost of electric vehicle charging and distribution load difference between peak and valley minimum.Multi-objective charging optimization and control strategy of the two phase is established in order to stabilize the peak load and the optimal charging cost to achieve the purpose by using of genetic algorithm to solve the optimization problem.On the basis of meeting the fast charging demand of public vehicles such as electric taxis and electric buses,we can reduce the impact of the electric vehicle uncoordinated charging by adjusting the charging load of electric private cars.The simulation results show that the peak and valley difference and charge cost can be effectively reduced by optimizing the charging load and by charging time of the electric vehicle.(3)So as to improve the responsiveness of electric vehicle owners to orderly charging,the peak and valley time price is optimized,starting from two aspects: peak valley time division and electricity price formulation.According to the load characteristics of local distribution network,the membership degree function is used to reclassify peak and valley period.The response model of the electric vehicle is established by the price elastic matrix,and the genetic algorithm is used to solve the optimized peak and valley time price.The simulation results show that the optimization model established in this paper can effectively reduce the load fluctuation of distribution network and further reduce the charging cost of electric vehicles.Besides,it can promote the response of electric vehicle owners to orderly charging.