The Decision Of Charging Selection For Grid Congestion Adjustment With Electric Vehicle Participation

In recent years,with its clean and efficient characteristics,electric vehicles have become an effective way to reduce fossil fueland alleviate air pollution.With the increasing subsidies for the purchase of electric vehicles in China and the continuous improvement of related technologies,the electric vehicle market will show an explosive growth trend in the future nationwide.However,with the gradual increase of electric vehicle penetration,it will also bring new challenges to the safe and stable operation of distribution network.For the distribution network containing electric vehicles,on the one hand,with the gradual increase of electric vehicle access,its unconstrained or unguided power consumption behavior is not conducive to the power balance control of distribution network,and may even cause network congestion.On the other hand,how to improve the overall utilization of power grid facilities without increasing the scale of power grid construction,while avoiding the transmission congestion caused by electric vehicle charging is also an urgent problem to be solved.Considering the good flexibility of EV load under the control of market incentive mechanism,reasonable dispatch of EV will help alleviate network congestion and improve system stability and economy.Therefore,how to solve the problem of power grid transmission congestion and guide the orderly charging of electric vehicles has become the main research issue in this paper.Firstly,this paper firstly models the electric vehicle load on the user side,analyzes various factors affecting the load distribution of electric vehicles,and simulates the characteristic distribution curves of battery charging,daily driving mileage and user charging habits.Secondly,the distribution network system framework of electric vehicle charging equipment is established from the perspective of distribution network.At the same time,according to the specific simulation scenarios and parameter settings of the system,the simulation experiment is carried out from Peak-valley difference of load,node voltage off-limit and branch overload of different electric vehicle penetration rates,and the influence of the disordered charging of electric vehicles on the grid congestion is obtained.Then,corresponding solutions are proposed at the distribution network level and the user level.Among them,at the distribution network level,starting from the congestion adjustment,a congestion pricing model based on power sensitivity is proposed,that is,when the distribution network is blocked,calculating the amount of load that each charging station needs to adjust according to the power sensitivity of each charging station node to the blocked line,and based on the actual situation of the power market in China,dynamically set the congestion price for the user,By using low electricity price to guide the owners to change their electricity consumption habits and make appropriate charging plans,the congestion power of distribution network can be regulated and controlled,so as to optimize the allocation of resources.At the level of electric vehicles,the electric vehicle navigation system is introduced.Based on the congestion price,other practical factors affecting the charging decision of electric vehicle users are analyzed,the Multiple Attribute Decision Making(MADM)is used to formulate the most feasible and economical charging decision for users.This method enables users to obtain economic benefits while also alleviating the congestion problem of the distribution network.Finally,an experimental simulation was performed on a 34-node system with an electric vehicle charging device.The Monte Carlo method is used to compare the branch power,the overall load curve,each charging station load curve and voltage overrun probability before and after user response to multi-attribute cooperative decision-making,so as to verify the correctness and effectiveness of the proposed the decision of charging selection for grid congestion adjustment with electric vehicle participation.