Research On Optimization Of Electric Vehicle Operation Planning Based On Traffic Factor Analysis

There are many optimization problems in the actual operation and management process of electric vehicles,and charge and discharge and charge navigation planning are two important optimization technology application directions.Among them,many constraints are not available in the operation of traditional fuel vehicles.Due to the charging and discharging functions of electric vehicle batteries,when the number of charging electric vehicles at a certain charging station(region)within a certain period of time,the centralized charging and discharging behavior will affect the electric load on the local area of the charging station It has a significant impact,making the study of the optimization of the charging and discharging behavior of electric vehicle user clusters very important to alleviate or improve the electric load of the charging station area during peak hours.At the same time,the differences in the charging principles of electric vehicles lead to the optimal design of the daily electric vehicle charging navigation path Must consider its specific characteristics(such as long charging time,etc.).More importantly,both of the above optimization problems will be significantly and adversely affected by actual road traffic factors.Therefore,it is of great theoretical and practical application value to carry out research on electric vehicle optimization methods under in-depth traffic factor analysis for the above problems.Based on the above analysis,this article focuses on the research of the following three parts:1)The influence of the random charging behavior of the electric vehicle cluster on the local grid load of the charging station is studied.The random charging behavior model of the user is constructed,and the simulation results show that the behavior will cause the load "peak to peak" and the peak to valley ratio to increase,which provides the necessary validation for the subsequent research on the optimization of the charging and discharging behavior of electric vehicles.2)Aiming at the study of the distribution law of the current charging and discharging moments of electric vehicles without fully considering the influence of traffic factors,an optimization method for charging and discharging behavior of electric vehicle clusters based on quantitative analysis of traffic congestion is proposed.Based on the simulation verification of the random charging behavior of the electric vehicle cluster on the local grid load of the charging station,an energy charging and discharging moment model of the electric vehicle that expresses the degree of traffic congestion is proposed.On the basis of satisfying the needs of users on the demand side and ensuring the stability of power consumption in the local power grid,a multi-objective and multiconstrained optimization function that minimizes the total cost of user power and minimizes the peak-to-valley difference of the power grid is constructed.Through the combination of chaotic mechanism and adaptive inertia weight improvement technology,an optimized calculation method of electric vehicle cluster charging and discharging strategy based on improved PSO algorithm is proposed.The results show that the new method can guide the user's charging and discharging behavior reasonably and effectively.At the same time,the quantitative consideration of the degree of traffic congestion makes the new method obtain better engineering application capabilities.3)Based on the in-depth analysis of the actual traffic system characteristics,an optimization method for electric vehicle charging navigation path planning based on in-depth traffic and charging station dynamic information modeling is proposed.Based on the information provided by the navigation system and intelligent charging station,this paper studies the modeling method of the impact of real-time traffic status on the navigation path optimization model.Based on the in-depth analysis of the dynamic change of the occupancy status mode of the charging pile group at the charging station,the objective function of the electric vehicle charging path planning based on the total time-consuming cost and the corresponding set of constraints are constructed,and a dynamic optimization of charging navigation based on the Dijkstra algorithm is proposed.Strategy calculation method.Simulation experiments show that the new path planning method can effectively adapt to the dynamic changes of the actual transportation system,and at the same time,it can optimize and adjust the real-time navigation strategy according to the change of the charging station usage status of the corresponding charging station.