Research On Orderly Charging Control Strategy For Scaled Electric Vehicles Into The Network

In response to the world’s deteriorating energy and environmental issues,fuel vehicles are one of the chief contributors to fossil fuels and environmental pollution.It is imperative to develop and promote new types of vehicles that can replace fuel vehicles.Under this environment,electric vehicles are increasingly being accepted and recognized globally due to their pollution-free and energy-saving features,and their development boom remains high.The dramatic increase in the scale of development is obvious.However,the large-scale uncontrolled access of the electric vehicle to the distribution network will bring unprecedented impact on the stable operation of the current grid.Therefore,the effective and effective guidance and regulation of the electric vehicles that easily develop into disordered charging is inevitable.It is indispensable to develop and optimize the corresponding charging strategy.This will not only alleviate the severe situation caused by the disorderly charging of electric vehicles,but also greatly benefit the overall promotion of electric vehicles.This thesis first analyzes the random factors that can affect the charging demand of electric vehicles,and then analyzes the driving habits of electric vehicles based on the uncertainty of the charging behavior of electric vehicles in time and space,and uses the Monte Carlo simulation method to obtain the charging of electric vehicles.The daily load curve was followed by the mathematical modeling of the disordered charging load of large-scale electric vehicles.Taking the most common type of electric vehicle-private car as the research subject and the IEEE33 node distribution network as the simulation system,the chain reaction caused by the penetration of different penetration electric vehicles into the distribution network was simulated.The simulation results show that with the continuous improvement of the penetration level of electric vehicles,the maximum load of the distribution network and the peak-to-valley dinfference of the load will increase.The phenomenon of node voltage offset and the network loss of the distribution network will also become more serious.Therefore,it is imminent to propose an effective and effective charging strategy.The optimized charging strategy proposed in this thesis fully considers the interests of both the user side and the grid side of the electric vehicle,and establishes a multi-target aiming at the minimum charging cost of the electric vehicle owner,the minimum daily load peak and valley difference in distribution network,and the minimum loss of the distribution network.Optimize the model,and use the crowd distance-based multi-objective particle swarm optimization algorithm(MOPSO-CD)to obtain the Pareto optimal solution set of the model,and then use the analytic hierarchy process to find the optimal Pareto optimal solution to obtain the optimal solution.Take into account the optimal solution set of the three objective functions.Finally,the influence of the proposed multi-objective optimization strategy on the distribution network during the charging of the electric vehicle is analyzed through simulation.