南方电网技术2017，Vol.11Issue(1)：52-57,73,7.DOI:10.13648/j.cnki.issn1674-0629.2017.01.008
基于多群组均衡协同搜索算法的电动汽车充放电多目标优化
Multi-Objective Optimization of Charging and Discharging Strategy for Electric Vehicles Based on Equilibrium-Inspired Multiple Group Search Optimization
摘要
Abstract
The uncoordinated charging strategy of massive electric vehicles (EVs) will threaten the safe operation of the grid, this situation can be relieved if coordinated charging/discharging strategy is developed.Based on classical battery-wear model and time-of-use price, a multi-objective optimal model for EVs` charging/discharging process is proposed to reduce the daily load fluctuation and the charging cost considering EV`s charging demand.The Pareto front and the compromise solution are calculated by equilibrium-inspired multiple group search optimization with synergistic learning (EMGSS).Rolling optimization is adapted to deal with the day and night random variance of charging demand and reach the double-win of grid and EV owners.The simulation results demonstrate that daily load fluctuation is reduced effectively and EVs` charging cost is also decreased.关键词
电动汽车/有序充放电/多目标优化/多群组均衡协同搜索算法Key words
electric vehicles/charging/discharging optimization/multi-objective optimization/EMGSS分类
信息技术与安全科学引用本文复制引用
郑宇,张睿,李正佳,潘振宁,王德志..基于多群组均衡协同搜索算法的电动汽车充放电多目标优化[J].南方电网技术,2017,11(1):52-57,73,7.基金项目
中国南方电网公司科技项目(WYKJ00000027).Supported by the Science and Technology Project of China Southern Power Grid (WYKJ00000027). （WYKJ00000027）
