Research On The Optimal Scheduling Of Orderly Charging Of Electric Vehicles Under The Regional Internet Of Vehicles

Energy and environment have always been the focus of attention of all countries in the world.In recent years,global climate warming,worsening urban environmental pollution,global energy crisis and other issues have become increasingly serious,and studies on energy alternatives and sustainable development have gradually become the focus of the world’s energy development.Replacing the traditional oil-powered automobile industry with electric vehicle industry is an important way to effectively solve the energy crisis and environmental pollution.At the same time,charging electric vehicles into the power grid will also bring some negative effects on power grid load balance and power quality.Therefore,it is necessary to analyze the impact of the natural charging scenario of large-scale EV on the power grid,studying the constraints of restricting the unordered charging of EV and giving the charging strategy of it.Firstly,the influence of EV charging on regional power grid under different permeability is studied.According to the charging principle and charging standard of EV,the charging model of EV is established.The influence factors of limiting EV access are analyzed,including voltage deviation,branch blockage degree,transformer carrying capacity and harmonic distortion rate.A typical regional EV charging model was built to analyze the influence of EV charging on regional power grid under different permeability.Secondly,in view of the negative impact of large-scale application of electric vehicles and unordered charging on grid planning and operation,an orderly charging control strategy for electric vehicles in the region under the Internet of vehicles is established.This paper analyzes the feasibility of EV operation mode and orderly regulation under the Internet of vehicles,establishes a regulatory framework for orderly charging of EV under the Internet of vehicles,and establishes a charging control strategy for EV under the Internet of vehicles by taking the minimum load fluctuation of the regional power grid as the objective,taking into account EV charging and power grid operation constraints.Taking the daily load data of electric vehicles in typical residential areas as an example,this paper analyzes the influence of the orderly charging control strategy on the load characteristics of distribution network.Finally,aiming at the problem of slow speed and poor convergence caused by the randomness and dispersion of EV charging process,this chapter proposes a cuckoo search algorithm with dynamic step size and self-learning discovery probability.When the algorithm searches solution space,learning factors are introduced to generate dynamic step size to accelerate the speed of local solution space search.In the early stage of algorithm iteration,self-learning discovery probability is adopted to increase the global search ability.Through simulation and comparative analysis,it can be concluded that the improved cuckoo searchalgorithm is designed to make up for the shortcomings of the existing algorithm,to achieve rapid response in the charging process of EV,and to improve the convergence speed of charging regulation optimization of EV in the region.