Research On Intelligent Scheduling Strategy Of Rapid Charging For Electric Vehicles In Distributed Scene

With the development of the electric vehicle industry,especially in the face of the new outdoor charging scenarios for network-ordering and shared electric vehicles entering the scale,there are many issues that need to be further studied.Such as solving the overall parallel scheduling optimization of large-scale charging requests in distributed charging scenarios,reasonably matching charging requests with the charging facilities,guaranteeing the regional real-time dispatching,ensuring the user’s charging experience and the utilization of the charging facilities.First of all,an optimization model based on assignment model for global parallel scheduling of electric vehicles is proposed in this paper.By estimating travel time,waiting time and charging time,an optimization strategy to balance the demands of users,operators and power grids is achieved.Secondly,in order to enhance the applicability of the charging scheduling model in large-scale charging scenarios,a local charging scheduling optimization model is proposed.The local model is based on the improved hierarchical clustering algorithm and a regional selection model,which not only reduces the computational complexity of the global optimization,but also increases the ability of regional differential analysis.In addition,this paper considers that the charging scheduling for distributed scene should take the power allocation strategy of single station into account.And a priority power allocation strategy is proposed in this paper.It can make full use of the power load resources of the charging distributed stations and reduces the average charging time of the users futher.A multi-agent simulation platform containing a variety of agent models from real environment is established in this paper.The distributed charging scheduling strategy proposed in this paper is simulated and verified.The experimental results show the models proposed in this paper which can enhance the user charging experience and the utilization of charging facilities well.