Research On Strategy Of Large Scale Electric Vehicle Charging Power Allocation

At present,with the gradual deterioration of energy and environmental problems,electric vehicles(EVs)have gradually developed into the mainstream development direction of new energy vehicles because of their energy-saving and environmental protection characteristics.Due to the diversification of charging needs of a large number of users,the traditional power allocation strategy used in charging stations can no longer solve the reasonable and unified charging problem of large-scale EVs.Therefore,this thesis proposes a charging power allocation strategy of large-scale EVs,the specific contents are as follows:(1)Aiming at the diversification of users’ charging needs,a charging service mechanism combining fast and slow charging is proposed.By analyzing the advantages and disadvantages of fast and slow charging modes,the fast charging and slow charging modes are further combined to provide an effective service mechanism for subsequent related research.(2)According to the charging data of each electric vehicle user,the nonparametric kernel density method is used to estimate the probability of each charging characteristic variable of the user.Through simulation analysis,the probability distribution of each characteristic variable or the number of charging vehicles and the average waiting time of users in each period under the original random queuing mode are obtained.It provides data support and comparison basis for subsequent power allocation and user satisfaction analysis and related example simulation.(3)For M/M/C/N queuing system,a priority penalty mechanism is proposed.Using this mechanism to initially optimize the waiting time of users in a queue.Through simulation and comparison of the average waiting time of users in different service intensities,the superiority of the optimization mechanism in reducing the average waiting time of users is reflected and a fixed queuing mode is provided for subsequent research.(4)Aiming at the problem of user satisfaction during electric vehicle charging,a user satisfaction function model is established.Firstly,the initial charging power of users is obtained by node branch method.Secondly,the priority penalty mechanism is used to preliminarily optimize the charging power of users.Finally,taking the obtained charging power as one of the variables and considering the waiting time,charging price and other factors,an optimal user satisfaction function based on penalty is proposed.This function quantifies the user’s attitude towards charging service and provides an effective evaluation standard for the subsequent power allocation strategy.(5)Aiming at the problem about charging power allocation of EVs,a charging power allocation strategy based on user satisfaction is proposed.Firstly,on the basis of the charging service mechanism combining fast and slow charging,an allocation algorithm for new users to join charging is proposed.Secondly,through the power allocation algorithm based on fair weight,it can meet the personalized needs of users and allocate fair and reasonable power values for each user.Finally,the user satisfaction function is used to evaluate the strategy.It is verified by simulation that this strategy can reduce the overall charging load fluctuation while improving the fairness and rationality in the charging power distribution process,reducing the waiting time of users,improving charging efficiency and improving user experience.