Research On Optimal Control Strategy For Charging/Discharging Of Electric Vehicles

With the increasing global energy and environmental problems,the drawbacks of traditional energy sources are becoming increasingly apparent.As a clean emerging energy source,electricity can not only alleviate the shortage of traditional energy resources,but also improve environmental issues.Therefore,the development of the electric vehicle industry is imperative.On the grid side,electric vehicles can use auxiliary functions such as power supply and power grid charging and discharging,and they can use the charge-discharge spread to generate revenues for the user.However,with the expansion of the scale of electric vehicles,their charging and discharging behavior will affect the power grid,so it is necessary to carry out orderly adjustment and control of the charging and discharging behavior of electric vehicles.Based on this,the paper made relevant research as follows:Firstly,the influencing factors of the charging load of the electric vehicle are analyzed,and four factors are considered: the scale and type of the electric vehicle,the daily operation law of the electric vehicle,the battery characteristics of the electric vehicle,and the user's charging habit of the electric vehicle.Based on the above factors,a calculation model for the charging load of electric vehicles was established,and the Monte Carlo sampling method was used to randomly sample the daily mileage and initial charging time of the electric vehicle,and the simulation results were obtained.Based on this analysis,the impact on the power grid was analyzed.Secondly,two objective functions are established under the real-time electricity price,which are the minimum load peak-to-valley difference and the maximum revenue of electric vehicle users.Two control models,single-target and multi-objective,are used to improve the multi-objective particle swarm optimization algorithm.The group algorithm is solved.Two single-target EV charging and discharging load optimization results and Pareto optimal solution sets are obtained respectively.The simulation example shows the correctness and effectiveness of the construction model.Finally,the uncertainty of the charging and discharging power of the electric vehicle is considered.The charging and discharging power optimization model is put into thedistribution network for solving,and the influence of this uncertainty on the distribution network is analyzed.The interval optimization method is used to describe this.For the uncertainty,an interval mathematic optimization model with the minimum difference between peaks and valleys was established and solved by the particle swarm optimization algorithm.Finally,the uncertainty method and the deterministic method were compared to reduce the peak-to-valley difference and robustness.The advantages and disadvantages between the goals,thus verifying the validity of the interval optimization method in obtaining good robustness.