Research On Orderly Charging Strategy Of Electric Vehicles Based On Real-time Electricity Price

In the process of rapid social and economic development,all countries in the world have brought about increasingly serious problems such as fossil energy depletion and environmental pollution.In 2015,178 countries passed the "Paris Agreement" at the Paris Climate Conference to promote CO2 emission reduction.The Chinese government also put forward the “dual-carbon” goal in the 2021 government work report and the 14 th Five-Year Plan.While the power industry is deploying changes in the energy structure of power generation,it starts with energy-saving load and load regulation on the load demand side,and promotes large-scale electric power.Cars are connected in an orderly manner to improve the operation of the power grid,and play a positive role in reducing the "carbon emissions" pollution caused by fuel vehicles at the same time.Electric vehicle charging load has uncertainties in time and space,which are closely related to factors such as the travel characteristics of electric vehicle users,charging modes,and battery charging characteristics.Based on travel data and Monte Carlo simulation method,short-term charging load forecasting is carried out for electric vehicle load in residential areas with slow charging mode as the mainstay.Studies have shown that in the disordered charging scenario,the grid load exhibits the phenomenon of "increasing peaks on the peak" and "reverse peak regulation",which will have a negative impact on the operation characteristics and dispatch adjustment of the grid under the condition of high penetration rate.Taking into account the peak-to-valley difference of the distribution network,the charging cost of electric vehicle users,the income of charging stations,etc.,a comprehensive charging cost minimum orderly charging optimization goal that integrates the interests of the three parties has been constructed,and the orderly charging of electric vehicles under different application scenarios has been designed.The charging strategy is used to simulate three types of application scenarios: single-stakeholder first,two-party interests first,and three-party comprehensive benefit maximization through the clustering method.In the multi-objective collaborative optimization model,a real-time electricity price mathematical model based on load rate change factors is established,a dynamic weighting coefficient adjustment method associated with each time period is proposed,and a penalty factor is introduced to deal with the charging time default problem of individual users.The research results show that the target weight dynamic adjustment method avoids the problem of the loss of the optimal solution set and subjective choice,can quickly optimize the target function.An orderly charging strategy for electric vehicles based on real-time electricity prices and time-of-use electricity prices is designed,the stability and adaptability of orderly charging guidance strategies under different access scales and responsiveness of electric vehicles are analyzed.The optimization results show that regardless of the increase or decrease of the access scale and responsiveness,the real-time electricity price-based guidance strategy can better take into account the interests of all parties,and as the number of electric vehicles increases and the responsiveness increases,the real-time electricity price guidance strategy is more effective.On the basis of minimizing the revenue loss of charging stations,the smaller the peak-to-valley difference and user expenditures.In view of the shortcomings of the quantum particle swarm algorithm,the improved chaos mapping is added to avoid premature algorithm,and the hill-climbing search method is introduced in the local search to enhance the search ability.The performance of the hybrid leapfrog algorithm and genetic algorithm is compared,and the improved chaotic quantum is proposed in the article.The improved chaotic quantum particle swarm algorithm proposed in the paper is not easy to mature,and the search ability and convergence speed are improved.The orderly charging guidance strategy proposed in this paper can make the interests of the power grid,electric vehicle users and charging stations more balanced,and provide a theoretical basis and application guidance for the operation and control of large-scale electric vehicles connected to the distribution network.