Research Of Charging Dynamic Time-of-use Tariffs For PEV Based On User Behavior Habits And Charging Station Profit

Under the background of the current shortage of oil resources,the aggravation of environmental pollution and global warming,vigorously promoting and developing new energy vehicles with energy saving,environmental protection and low carbon is the direction and goal of human society in pursuit of sustainable development of automobile industry.Therefore,the large-scale development of electric vehicles has become an inevitable trend.However,the number of charging stations is also increasing with the large-scale development of electric vehicles.The randomness and disorder of electric vehicle charging will lead to load fluctuation of charging station.These fluctuations will cause"peak-to-peak"phenomenon in the power grid to a certain extent,which will have a significant impact on the power grid,charging facilities and users.In order to reduce or restrain these negative effects,the charging behavior of electric vehicles should be guided and controlled.As an economic stimulus,time-of-use tariffs can use price leverage to play the role of cutting peaks and filling valleys.In this paper,the behavior habits of electric vehicle users are analyzed.Considering the interests of charging stations,an optimization model of electric vehicle time-of-use tariff considering user behavior and charging station profit is established.The main contents are as follows:(1)the development status of electric vehicles and charging stations is discussed.Aiming at the influence of randomness and disorder of electric vehicle charging on power system load,the time-sharing tariff is used to guide users to charge in the load trough and reduce the peak load of power.At the same time,the profit of charging station of electric vehicle is taken into account to ensure the normal survival and operation of charging station.(2)The membership degree of each time point in peak and valley periods is calculated based on the data of typical daily load.And the fuzzy clustering method is used to obtain the clustering set of each time period.The attribute values of responsiveness at each time point are calculated respectively to obtain peak time,flat time and valley time.Similarly,the fuzzy membership degree is used to determine the pinnacle peak period,and finally the results of the pinnacle peak period,the peak period,the flat period and the valley period are obtained.(3)the distribution rules of travel habits,parking habits and charging habits of electric vehicle users are analyzed.Based on the theory of price elasticity of electricity demand,considering the influence of charging station and electric vehicle users,based on the objective function of minimizing the peak load of the system and maximizing the benefits of the charging station,optimization model of dynamic time-of-use tariffs for PEV based on user behavior habits and charging station profit is established.The principle of genetic algorithm used to solve the model is briefly described,the improvements of NSGA-II and the steps to solve the model are also introduced.Finally,the model is analyzed with relevant examples and verify by simulation with MATLAB.(4)The genetic algorithm is used to optimize the minimization of peak load,the peak load is reduced by 128 MW and the profit of charging station is increased by 0.534×10~4yuan.The genetic algorithm is used to optimize the profit maximization of charging station,the peak load is reduced by 76 MW and the profit of charging station is increased by 2.345×10~4 yuan.The fast and elitist non-dominated sorting genetic algorithm is used to optimize the minimization of peak load and the profit maximization of charging station,the peak load is reduced by 92 MW and the profit of charging station is increased by 1.366×10~4 yuan.The simulation results show that the load rate,peak-valley difference rate and other indicators have improved to a certain extent.The peak load is reduced,the trough load is increased and the gap between peaks and valleys is narrowed.And the curve gradually tends to be stable,reaching the expected goal of"peak cutting and valley filling"The scheduling strategy guided by the time-of-use tariffs can better guide the charging behavior of electric vehicles,so that electric vehicle users can change the charging time and transfer to other time periods to charge.Then it can alleviate the power load tension during the peak period of power consumption,so as to ensure the safe and stable operation of the power system.On the other hand,it can improve the profit of charging station and ensure the normal operation of charging station.