Application Of Electric Vehicle And Grid Layering Optimization Strategy Based On Improved Fish Swarm Algorithm

With the increase in the number of electric vehicles(EVs)year by year,large-scale disorderly charging has aggravated the uncertainty of grid operation,worsened the operation indicators of the power system,and affected the stability of the power system.As a new element in the power grid,electric vehicles not only absorb energy from the grid as charging loads,but also play the role of distributed power sources,using V2 G technology to feedback grid energy to achieve the optimization goal of "peak shaving and valley filling".If the charging and discharging behavior of electric vehicles is guided,it can not only bring users certain benefits,but also alleviate the power shortage of the power grid and improve the utilization rate of electric energy,promote the integration and consumption of new energy into the grid.After referring to the existing research directions,the power shock in the process of grid connection of electric vehicles,the reasonable distribution of power in the process of photovoltaic consumption and charging are the focus,and the main research contents are as follows:Firstly,the types and charging and discharging characteristics of electric vehicles are introduced,and the travel rules of electric vehicles are analyzed.Based on the uncertainty of the starting charging time and charging duration of electric vehicles,the Monte Carlo method is used to establish a charging load prediction model of electric vehicles,and the influence of disorderly charging of electric vehicles on the power grid under different penetration rates is analyzed.Secondly,on the basis of meeting the next-day use needs of electric vehicles,an orderly charging scheduling model under the hierarchical control architecture is established.On the basis of using fuzzy algorithms to formulate the charging price during valley hours,the upper control center sends a power guidance curve according to the user’s charging demand and the charging volume of electric vehicles in the valley range,and the lower charging station takes the minimum load fluctuation of the power grid and the optimal execution of the power guidance curve as the comprehensive optimization goals.In order to avoid the problem of "dimensional disaster" caused by a large number of electric vehicles,electric vehicles are clustered and grouped to determine the charging priority.Through specific examples,the improved artificial fish swarm algorithm(IAFSA)is used to solve the problem,and after optimizing scheduling,a relatively flat charging load curve is obtained during the valley period.Thirdly,in order to realize the potential of mobile energy storage power for electric vehicles,a V2 G operation mode of vehicle-network interconnection is constructed,and idle electric vehicles are used to feedback power to the grid during peak power consumption periods.This strategy takes the V2 G revenue of electric vehicles as the optimization goal on the user side,and the variance of the grid load fluctuation as the optimization goal on the grid side.In order to achieve a balance between the optimization of two objectives,the hierarchical sequence method is used to transform multiple objectives into single-objective problems for processing,and solve them in layers.The results show that this strategy can effectively stabilize the load fluctuation of the power grid and increase the income of electric vehicle charging and discharging in the V2 G dispatching mode.Finally,based on the consideration of the flexibility of charging and discharging of electric vehicles,a hierarchical scheduling strategy for co-optimization of electric vehicles and photovoltaics is proposed in the grid-connected system architecture including photovoltaic and electric vehicles,and the upper control center constructs a two-objective optimization model with the smallest load fluctuation of the power grid and the largest on-site consumption of photovoltaic power generation.In order to make the solution most in line with the requirements of decision makers,the maximum fuzzy satisfaction method is used to transform the multi-objective function problem into a nonlinear one-objective optimization problem.The lower control center evaluates the flexibility of charging and discharging of electric vehicles connected to the power system,and minimizes the square sum of the deviation between the charging and discharging power of electric vehicles mobilized in each period and the upper plan.The calculation results show that the use of electric vehicles to participate in the collaborative optimization dispatch of photovoltaic power generation is not only conducive to smoothing the load fluctuation of the power grid,but also can achieve the maximum on-site consumption of photovoltaic output.