The Research On The Evaluation Method Of The Impact Of Large-scale Electric Vehicle Charging And Discharging On The Voltage Quality Of Distribution Network

The large-scale promotion of electric vehicles(EVs)is the gateway to accelerate the transformation of Chinese automobile industry,realize energy conservation and emission reduction.Nevertheless,the power quality problem caused by EVs access to the power grid are attracting more and more the focus of industry attention.On the one hand,the ever-increasing charging load will change the distribution of the original power flow in the distribution network,making power quality problems such as voltage deviation,three-phase unbalance increasingly serious.On the other hand,EVs can also be used as energy storage devices to interact with the power grid(Vehicle to Grid,V2G).By charging during the low load periods while discharging during the peak periods to smooth out the load curve,thereby effectively alleviating the impact of EVs on the power quality of the distribution network.This thesis evaluates the voltage quality problems caused by the charging and discharging loads of EVs connected to the distribution network.The spatial and temporal distribution characteristics of EV charging loads is a crucial basis for the analysis of their impact on the voltage quality of the distribution network.In view of the uncertainty of EV travel and cha rging,this thesis builds the travel chain of EV by analyzing the behavior characteristics that affect the charging load and combining with the existing EV travel data in China.The time variable of charging load is fitted with normal distribution and log-normal distribution,and the Markov chain is used to describe the spatial transfer characteristic of the vehicle.Based on this,the spatial and temporal characteristic model of charging load for EV is modeled.Given that the traditional deterministic powe r flow analysis can not take into account the time-varying charging load of EVs,this thesis proposes a method for evaluating the voltage crossing probability of distribution network containing the disorderly charging load.To begin with,the distribution characteristics of the charging load are sampled by median Latin hypercube to construct a disorderly charging scenario,and the sample space of the charging load is obtained by this calculation.Afterwards,Monte Carlo simulation method is used to calculate the power flow of the sample values one by one to obtain the voltage of each node.Ultimately,the approximate estimation of the voltage crossing probability density at each node is achieved by the nonparametric kernel density estimation method.The effectiveness of the proposed method is verified by simulation in the IEEE3 0 node distribution network to achieve probabilistic assessment of the voltage quality of the distribution network.V2G technology is a key initiative to mitigate the impact of large-scale EVs access on the voltage quality of the distribution network.At the same time,the large-capacity power battery of electric buses and the relatively fixed driving pattern provide sufficient dispatchable capacity for the implementation of V2 G technology.To further measure the role of V2 G on power quality,this thesis proposes a method to evaluate the voltage quality of the distribution network taking into account the participation of electric buses in V2 G.By establishing a charging and discharging model that fits the operating characteristics of the electric bus,the optimal node voltage of the distribution network under the network power flow constraint model is obtained with the participation of electric buses in V2 G charging and discharging,and an evaluation model is established to quantify the impact on voltage quality.The simulation results show that a reasonable charging and discharging of the scaled electric bus can effectively mitigate its impact on the power quality of the distribution network and provide a reference value for urban distribution network construction.