Research On Distribution Network Reconfiguration Method Under V2G Mode

With the continuous growth of car ownership,automobile exhaust emissions have become one of the important causes of air pollution.The frequent occurrence of haze weather has affected the lives of most cities,making people pay more and more attention to environmental issues.At the same time,with the increasing consumption of non-renewable energy such as petroleum,electric vehicles have promoted the rapid development of electric vehicles due to the advantages of using clean energy and zero exhaust emissions.As the scale of electric vehicles continues to expand,the scale of electric vehicles is large.The popularity of scale will become an inevitable trend in the future development.Due to the charging of many electric vehicles to the distribution network,the structure of the distribution network is becoming more and more complicated,which causes problem such as increased loss of the distribution network.If the electric car is charged during peak load periods,the burden on the distribution network will become heavier.Thereby affecting the power quality of the power supply for the power system.Distribution network reconfiguration reduces distribution network losses without requiring significant investment.At the same time,the electric battery of the electric vehicle can also be used as a mobile energy storage unit,but how to effectively use the electric vehicle when it is parked.This thesis studies the reconfiguration of electric vehicles and distribution networks in V2 G mode.The driving characteristics of electric vehicles in the distribution network are analyzed.Based on the vehicle data collected by NHTS,the distribution of the first travel time of the vehicle throughout the day,the distribution of the last return time in the whole day,the vehicle throughout the day are obtained and mileage in the middle.The discharge of electric vehicle charging is mainly completed by V2 G charging and discharging machine.This thesis makes the corresponding control strategy.The electric vehicle charging and discharging system model is built in MATLAB/S imulink.According to the simulation results,the output current is analyzed when the electric vehicle is discharged to the grid.Changes in voltage,output power,etc.For the closed loop-design of the distribution network,open-loop operation and a variety of network branches.In the process of reconfiguration of the distribution network,it is necessary to continuously calculate the power flow.Due to repeated calls,the requirements for rapidity are high.Therefore,this thesis uses an improved forward-backward algorithm for power flow calculation,this method is easy to program and calculate;On this basis,the objective function is calculated.When the electric vehicle is in the state of charge,the loss of the distribution network increases and the supply voltage decreases when the electric load increased,the distribution network reconstruction is used to reduce the line loss and improve the voltage quality.An improved genetic algorithm is adopted.It can ensure that the individuals in the genetic operation are feasible solutions,which greatly shortens the optimization time and dependence of the initial population during the reconstruction of the distribution network.On the other hand,when the electric vehicle is in the discharge state,as the mobile energy storage unit,the electric energy can be feedback to the grid.In this case,the reconfiguration of the distribution network is considered.In this thesis,the IEEE33 node system is used for simulation.When the simulation results are compared with the same load,Considering the active network loss and voltage quality after reconfiguration of the electric vehicle during discharge,it is better to directly perform reconstruction after considering the electric vehicle discharge.