Regulation Capability And Energy Management Of Electric Vehicle Charging Station At Low Temperature

Facing the increasingly serious energy shortage and ecological environment problems,the electric vehicle industry has become the main direction of transformation and upgrading of the automotive industry.With the large-scale access of electric vehicles to the power grid,it brings great challenges to the security and stability of power system,and injects vigor and vitality into the development of smart grid.As the regulation capacity and energy management strategy of electric vehicle charging stations depend heavily on the number of electric vehicles and battery performance,how to achieve accurate prediction is a major difficulty.Based on the influence of ambient temperature on the performance of lithium battery and the energy consumption of vehicle air conditioning,the thesis focuses on the influence mechanism of ambient temperature on the regulation capacity and energy management of charging station.The main research contents are as follows:Firstly,based on Arrhenius formula,the charge and discharge performance of lithium batteries at different ambient temperatures and the cycle life of lithium battery at low temperature are studied experimentally,and the nonlinear models of capacity decay rate and charge and discharge energy efficiency with ambient temperature are established.According to the stable heat transfer theory,the load of vehicle air conditioning is approximately calculated,and the energy consumption characteristic model of vehicle air conditioning varying with ambient temperature is constructed by using the least square method.In order to study the spatio-temporal randomness of electric vehicle travel,taking the National Household Travel Survey(NHTS2017)released by the US Federal Highway Administration in 2017 as an example,based on the trip chain theory,the probability distribution model of each characteristic quantity of the electric vehicle trip chain(including the first departure time,driving time,driving mileage and parking time)is established.The discrete matrix is used to construct the probability mode of trip destination transfer.The accuracy of the model is verified by evaluating and analyzing each model through the coefficient of determination and the adjusted coefficient of determination.Monte Carlo method is used to simulate the trip chain of electric vehicles.Combined with the influence mechanism of ambient temperature on the charge and discharge capacity,energy efficiency and energy consumption of vehicle air conditioning,the charging demand of electric vehicles under different types of travel days and different ambient temperature conditions is estimated,and then the estimation model of regulation capacity of electric vehicle charging station considering the influence of ambient temperature is established.And the influence of ambient temperature on the regulation capacity of charging station is revealed.Finally,taking the optimal user side economy and the best power grid stability as the objective function,the energy management strategy of charging station is discussed with full consideration of the regulation capacity of charging station,the charging demand of electric vehicles,the power of charging equipment and the power of grid.Aiming at the multi-objective,multi-constraint and nonlinear characteristics of the optimization problem,the nonlinear dynamic inertia weight is used to improve the Finally,taking the optimal user side economy and the best grid stability as the objective function,the energy management strategy of the charging station is discussed by fully considering the constraints of the regulation ability of the charging station,the charging demand of the electric vehicle,the power of the charging equipment and the power of the grid.Aiming at the multi-objective,multi-constraint and non-linear characteristics of the optimization problem,the nonlinear dynamic inertia weight is used to improve the basic particle swarm algorithm,and an energy management optimization strategy considering the influence of ambient temperature is proposed to realize the orderly control of the charging behavior of electric vehicles.The example results show that this strategy can effectively avoid the peak period of electricity consumption and meet the basic travel demand of electric vehicles,which verifies the rationality and feasibility of the strategy.