Establishment And Solution Of Many-Objective Optimal Scheduling Model For Charging And Swapping Station

As a new energy vehicle,the electric vehicle has the characteristics of environmental protection,low noise,and high energy efficiency.It has developed into one of the strategic emerging industries supported by China.With the rapid increase of the number of electric vehicles,the way of electric energy supply has attracted social attention.The switching mode is highly competitive and effectively solves the problems of slow power supply for electric vehicles.However,in switching mode,there are relatively few studies on the operation of the charging and swapping network and scheduling of batteries.Therefore,this paper studies the charging and swapping network of batteries,establishes the multi-objective scheduling model and many-objective scheduling model under designs a many-objective optimization algorithm to be applied to the model.The main content of this paper is divided into the following three aspects.Firstly,a multi-objective optimal scheduling model of the charging and swapping network is proposed.The current research on charging scheduling mainly considers the cost of a charging station,which makes the charging station arrange more batteries to charge at a low electricity price under the time-of-use price,but ignores the new load peak of power grid load.To solve this problem,this paper constructs a multi-objective optimal scheduling model for charging and swapping station,which considers the cost of the charging station and the minimum variance of power grid load.In order to solve the model,some classical multi-objective optimization algorithms are introduced and simulated.Secondly,a many-objective optimal scheduling model of charging and swapping station based on chance constrained programming is proposed.The scheduling problem in charging and swapping stations cannot be limited to the charging side.Only when fully charged batteries are transported to each changing station through logistics as required can the operation of the entire charging and swapping network be completed.In this paper,a many-objective optimal scheduling model with chance constraints is designed by integrating a centralized charging station,swapping stations,and delivery terminal considering the uncertainty caused by random environment.The penalty function method is used to deal with the individuals who violate the constraints to minimize the charging cost,load variance,transportation cost and time cost.Then,the classical many-objective optimization algorithms are introduced,and the proposed scheduling problem is solved by the combination of random simulation and many-objective optimization algorithm.Thirdly,a many-objective optimization algorithm based on a hybrid strategy is designed.In practical problems,with the increase of optimization objectives and more and more complex constraints,the number of non-dominated individuals in the population increases and the solution converges prematurely.In order to improve the diversity and convergence of the algorithm in scheduling problem of batteries,this paper improves the many-objective algorithm by the hybrid strategy of the integration of rejection strategy,repair strategy and punishment strategy.By modifying the boundary of the constraint,the excellent gene of the infeasible solution is retained,so that the solution converges to the global optimum.The algorithm carries out comparative experiments on the test set,and solves the proposed scheduling model,which reflects the advantages of the algorithm,and verifies the rationality of the charging and swapping network.