| With the rapid development of the electric vehicle industry,the number of electric vehicles and their charging stations has surged,and operators are facing major challenges such as discrete and randomized charging behaviors of electric vehicle users.Considering the space-time transfer characteristics of electric vehicle users,how to accurately predict the charging behavior of electric vehicles,and guide,manage and schedule the charging load of electric vehicles at the space-time scale to achieve the goal of economic optimization of electric vehicle charging stations have become the current research focus.In the management and operation of electric vehicle charging stations,the volatility and intermittency of renewable energy power generation,the uncertainty of spot market electricity prices,and the randomness of the basic charging load distribution will have an impact on the scheduling results.Flexible scheduling of charging loads in charging stations is a challenging problem.Therefore,this topic studies the charging scheduling strategy of electric vehicle charging stations in uncertain environments.The main research work of this topic is as follows:First of all,it is analyzed that the charging load of electric vehicles as electric vehicle charging stations has strong time-space transfer characteristics.As a kind of electric power flexible load,electric vehicles can establish a time-space model of the charging load of cluster electric vehicles by studying the time transfer characteristics and space transfer characteristics of cluster electric vehicles,and lay a solid foundation for the integrated scheduling of the supply and demand sides of subsequent cluster charging stations.Secondly,the uncertain factors faced in the operation of electric vehicle charging stations are analyzed,and the conditional value-at-risk method(CVaR)is selected as the measurement of operating risk,and the optimal model of electric vehicle charging load scheduling considering uncertainty is established.A simulation example is constructed,and the operator’s day-to-day load scheduling scheme is given under the premise of considering the uncertain factors of the day-to-day scheduling.By adjusting the risk preference coefficient,the influence on the scheduling resource selection and operating cost of the cluster charging station is studied.,Perfected the research theory of uncertain factors of cluster charging stations.Finally,a comprehensive optimization modeling model for cluster electric vehicle charging scheduling considering uncertainty is established.In an uncertain environment,price incentives and other measures are used to actively guide the electric vehicle charging load at the time and space scale to achieve the operating costs and The goal with the lowest risk cost.The optimal scheduling scheme is obtained by solving the mixed integer quadratic programming problem,and compared with the result of applying only part of the optimization method,the effectiveness of the model is verified. |
