电力系统自动化2017，Vol.41Issue(16)：96-104,9.DOI:10.7500/AEPS20160919012
大规模电动汽车集群分层实时优化调度
Hierarchical Real-time Optimized Dispatching for Large-scale Clusters of Electric Vehicles
摘要
Abstract
This paper presents a real time optimized dispatching model for large scale cluster electric vehicles (EVs) to achieve the charging demand and safe operation of distribution network.For each new optimization scenario,the accessed EVs can cluster according to their desired completion time.The entire dispatching process for charging/discharging strategy can be divided into two steps,i.e.,the upper dispatching based on grey wolf optimization (GWO) algorithm for each cluster,and the bottom layer based on energy buffer consensus for each EV in the corresponding cluster.Simulation results demonstrate that the proposed model can significantly facilitate the real time large scale optimal dispatching of EVs,while GWO algorithm and energy buffer consensus are suitable to solve large-scale optimal dispatching with superior performance on availability and convergence rate.关键词
能量缓冲一致性/大规模电动汽车/集群分层优化/充放电优化/灰狼优化算法Key words
energy buffer consensus/large-scale electric vehicles/hierarchical optimization of clusters/charging/discharging optimization/grey wolf optimization algorithm引用本文复制引用
潘振宁,张孝顺,余涛,王德志..大规模电动汽车集群分层实时优化调度[J].电力系统自动化,2017,41(16):96-104,9.基金项目
国家重点基础研究发展计划(973计划)资助项目(2013CB228205) （973计划）
国家自然科学基金资助项目(51477055).This work is supported by National Basic Research Program of China (973 Program) (No.2013CB228205) and National Natural Science Foundation of China (No.51477055). （51477055）
