Research On Price Strategy Of Electric Vehicles Charging Based On Improved Moth Flame Algorithm

Excessive fossil fuels using causes worse environmental problems,applying renewable energy into use is an important direction of future development,electric vehicles have received extensive attention as renewable energy driving vehicles.However,the power load formed by the random charging behavior of electric vehicle users will affect the smooth operation of the grid,appropriate scheduling methods should be used to guide the users.As an important scheduling method,charging price dispatching can directly affect users,which is highly targeted and effective.The core content of price dispatching is the specific plan of price setting.therefore,it is necessary to conduct research on the setting strategy of charging price,by which the charging actions of electric vehicle users can be guided and the stable operation of the grid can be ensured.Firstly,the regional grid system model with electric vehicle access is studied.The total power model of the grid is composed of the charging load of electric vehicles in the area and the fixed load formed by the residential,by analyzing multiple related factors that affect the charging of electric vehicles,the overall charging demand model of electric vehicle users in the area can be determined.At the same time,the price setting model formulated by the grid and the response model of users are analyzed.The theoretical foundation for the further research is established by setting the aforementioned models.Secondly,the multi-objective optimization model under charging price dispatching considering the charging behavior of electric vehicle users in the grid is studied.Fuzzy reasoning is used to establish the charging decision model of users who use electric vehicles as commuting tools at the time of parking,by taking the charging price and the remaining battery power as input,the charging probability can be obtained as output through the decision of users,then the total charging demand can be calculated further.With the price as a variable,an optimization problem is established to maximize the satisfaction of electric vehicle charging and minimize the power fluctuation of the grid,the moth-flame algorithm is used to solve the optimization problem,and the process of the algorithm is improved to speed up the optimization.The simulation results compare the scheduling results under different electricity price strategies,and the results show that the optimized electricity price strategy can increase the charging satisfaction of electric vehicle users and better improve the fluctuation of the grid.Finally,the issue of electricity price strategy formulation considering the optimal charging plan for electric vehicles under the delayed state is studied.Based on the background of long parking time of commuting electric vehicle,the optimal charging plan for electric vehicle users is designed during the parking time,and the purpose of avoiding peak hours and delaying charging can be achieved.The users make charging decisions according to the charging plan and their own needs,and the grid formulates price strategies in order to improve the stability.An optimization problem is established to minimize power fluctuations,and the satisfaction of users with charging is not reduced as a constraint.The optimal charging price will be obtained by using moth flame algorithm combined with the optimal charging schedule for each user.The simulation results show that by using the obtained price,the electric vehicle users can reduce the cost while the power fluctuation of the grid can be reduced effectively,and the power load of peak period can be transferred to valley period.