Modeling And Optimization For The Scheduling Problem Of Charging And Discharging At Battery Swapping And Charging Stations

As the improvement of performance on electric vehicles and growing awareness of environment protection,electric vehicles have been becoming a popular choice.Similar to the relationship between gas stations and traditional vehicles,electric vehicles are inseparable from charging stations which provide them with battery charging and replacement.Swapping and changing station is a station based on battery leasing mode,which has the functions of battery charging and battery replacement.A large number of electric vehicle batteries need to charge in swapping and changing station.Without reasonable management,new load peak will be generated by centralized charging and the peak-valley difference of power grid load will be aggravated.If the batteries can be charged effectively during the off-peak period of power grid load and discharged during the peak period of power grid supply,it will contribute to peak-load shifting.Therefore,charging and discharging scheduling of swapping and changing stations is significantly important to power grid.Considering a class of charging and discharging scheduling problems of swapping and changing stations,this thesis develops some research work as follows:(1)Related articles are retrieved.The current research situations about the operation problems of electric vehicle stations,charging and discharging scheduling problems of electric vehicle stations and some related algorithms are summarized.(2)Aiming at the charging and discharging scheduling problem of electric vehicle swapping and changing station,a charging and discharging scheduling problem that considering influence of power grid is proposed.After analyze income composition of the swapping and changing station,the power grid load fluctuation index is given which can measure its influence degree on the power grid.Taking the income and the fluctuation load index as the optimization objectives,and assuming the battery only charge or discharge once a day,a 0-1 integer nonlinear programming model is established.Then CPLEX is used to solve the model and verified the model’s correctness.(3)Aiming at the mathematical model in(2),an improved adaptive particle swarm optimization algorithm is designed to solve the model.Based on the idea of mutation in genetic algorithm,the mutation probability is calculated according to population variance and the fitness value of global extremum.In the velocity update formula,the particle search ability is improved by adding a variation term on the basis of the global extremum to avoid falling into the local optimal solution.In addition,the components of charging-discharging particles are mutated with a certain probability,so that them could jump out of bad state.After verifying the improved algorithm performance,results of the improved algorithm are compared with the results from CPLEX.comparative experiments are conducted to analyze the number of reserved batteries and charging piles,and constructive suggestions are given.(4)The assumption in(2)is relaxed,a charge-discharge scheduling problem is proposed,which allows the battery to charge and discharge multiple times.A mathematical model of the problem is established based on the original model.CPLEX solution is used to verify the correctness of it.In the experiment,it compared with the model in(2)that can charge and discharge only once in a day,and analyzed the influence of the number of reserved batteries and charging piles on this problem.It is concluded that allowing charging-discharging for multiple times can improve the income and the quality of the power grid,and the number of reserved batteries and charging piles can affect the actual charging-discharging times in the scheduling.