Electric Vehicle Load Forecasting Research On Optimal Scheduling Of And Orderly Charge And Discharge

Environmental pollution and energy crisis have become two major problems in today’s world.As a green means of transportation,electric vehicle has attracted extensive attention and attention from all countries because of its advantages of no pollution,low noise and energy saving.It has developed rapidly and its ownership has increased year by year.However,with the expansion of the scale of electric vehicles and the randomness of charging behavior of electric vehicle users in time and space,if their charging behavior is not guided and planned,it will have a great impact on the safe and economic operation of distribution network.Therefore,it is of great significance for the long-term development of electric vehicles to study the charging load forecasting method of electric vehicles,analyze its impact on the distribution network and put forward the corresponding orderly charging and discharging optimal scheduling strategy.Firstly,the paper analyzes the main factors affecting the temporal and spatial distribution of electric vehicle charging load.Considering the great differences in charging laws of different types of electric vehicles,electric vehicles are divided into three categories according to their uses,and they are studied and modeled one by one.Based on the travel chain theory,the charging load of electric private cars is predicted.According to the different travel laws of private cars on weekdays and rest days,the charging load calculation model is established by Monte Carlo simulation method.Through example simulation,the simulation results under different conditions are analyzed and superimposed with the charging load of buses and taxis according to a certain proportion,The temporal and spatial distribution of total charging load of electric vehicle is obtained;Then,on the basis of meeting the daily travel needs of users,the optimal charging and discharging dispatching of electric vehicles is carried out,comprehensively considering the variance of power grid load curve,peak valley difference and user economy,taking into account the travel needs of users,a multi-objective optimal dispatching model is established,which is solved by improved particle swarm optimization algorithm and simulated by an example,The optimal dispatching results under different TOU price systems are compared and analyzed;Then,the peak valley level period is accurately and carefully divided by the fuzzy clustering method.Based on the distributed control,the cluster optimal scheduling strategy for the orderly charge and discharge of electric vehicles is proposed,and the cluster scheduling model for the real-time response of orderly charge and discharge of electric vehicles in V2 G mode is established.The upper layer aims to minimize the variance of distribution grid load curve in the adjustment period,Coordinate the charge and discharge power of each electric vehicle cluster in each period;In the lower layer,aiming at minimizing the charging cost of each electric vehicle owner in the cluster,the optimal charging and discharging plan of a single electric vehicle in the cluster is solved by using the improved gray wolf algorithm;Finally,the ieee33 node distribution network including three local dispatching agencies is used to simulate the two-tier model of electric vehicle cluster dispatching strategy and the improved gray wolf algorithm.The results verify the effectiveness of the proposed model,and the improved gray wolf algorithm has faster convergence speed and stronger optimization ability.