Research On Electric Vehicle Charging Load Forecasting Method And Coordinated Charging Strategy

The development of energy-efficient electric vehicles is an important method of dealing with energy crisis,alleviating environmental pressures and achieving sustainable development.In recent years,with strong support from governments around the world and the continuous improvement of electric vehicle technologies,electric vehicle penetration has increased significantly.Vigorously developing new energy vehicles and gradually replacing traditional fuel vehicles have gradually becoming a social consensus.However,when large-scale electric vehicles are connected to the power grid,their charging and discharging behaviors will affect the operation planning of the power system and challenge the safe and stable operation of the power grid.Therefore,this thesis studies the charging load forecasting method and coordinated charging strategy of electric vehicles.The main work of the thesis is as follows.First,research on the prediction method of electric vehicle charging load.Analysis based on the charging behavior of electric vehicles,the driving behavior of owners and external influence factors of charging.This thesis proposes a prediction method based on cluster analysis that considers traffic congestion factors.On the basis of analyzing the factors affecting the charging load and establishing a probability distribution model,cluster analysis of the two-dimensional space composed of the two characteristics of mileage and travel time in each travel itinerary.Mining road congestion factors that cannot be obtained from conventional statistics,and superimposing this factor into the charging load prediction model to improve the accuracy of load prediction.Experimental verification and analysis of results.The experimental results verified that this method can improve the accuracy of the charging load prediction to a certain extent.Secondly,research on the coordinated charging strategy of electric vehicles.In order to stabilize the load peak-to-valley difference of the power grid and reduce user charging costs.Based on more detailed consideration of user responsiveness this thesis proposes a two-layer orderly charging strategy considering user response.Consider the time-of-use electricity price factor and charging time factor that affect the charging decision to establish user responsiveness.A bi-level coordinated charging strategy model based on a hybrid control method is established by a bi-level programming method,and single-period and multi-period parallel control methods are used to optimize coordinated control.Taking into account the bilateral interests of the user side and the grid side to establish an optimization objective function.Heuristic algorithm is used to solve the optimization function under the analysis of electric vehicle charging constraints.Experiments verify the effectiveness of the proposed optimization control method.Finally,research on orderly charging and discharging method for electric vehicles based on V2G technology.Considering the characteristics of electric vehicles as mobile energy storage that can feed the grid when necessary,charge and discharge optimization is performed through a centralized V2G control method.On the basis of obtaining electric vehicle charging information and grid load status information,the charge and discharge scheduling center is used as middleware to orderly optimize the charging and discharging of electric vehicles.In the process of regulation and control,the electric vehicle is first managed in groups,and the charging cluster and the discharge cluster are divided by establishing a dynamic grouping threshold.The secondary regulation is performed by a multi-period charge and discharge power allocation tuning algorithm.Orderly charging and discharging control of electric vehicles is achieved by the above method,and the effectiveness of the method is verified by experiments.