摘要
在现有的电池技术和充电条件下,快换式充电站成为国内纯电动公交最主要的能量补给摸式。针对电池组充电电费过高和增加配电网峰谷差的问题,以及换电站内快换工位和备用电池空闲的情况,在保证车辆正常运营的前提下,以充电站内全天充电电费最低为目标,建立了充电变功率工况下基于分时电价的换电站经济运行模型,通过遗传智能优化算法合理安排电池组的开始充电时间,降低充电电费,从而实现换电站的经济运行。分别基于北京北土城充电站和上海世博会充电站的实际数据和统计结果进行算例仿真,验证了算法的有效性。结果表明,该算法不仅能降低充电站充电电费,还能降低充电站白天对配电网的负荷压力,补充夜间负荷,减小配电网的峰谷差,在实现充电站经济运行的同时还有助于配电网的经济运行。
Under existing battery technology and charging condition the quick exchange station becomes the main energy replenishment mode for all-electric battery buses in China.In allusion to expensive charging cost of batteries and enlarging the peak-valley difference in distribution network as well as the idle quick exchange station and standby batteries within the swapping station,under the premise of ensuring normal operation of electric buses and taking minimal all-day charging expense as the objective a time-of-use power price based economic operation model under working condition with variable charging power is built,and through intelligent optimization of genetic algorithm the time to starting the charging of battery packs is reasonably scheduled to decrease charging expense,thus the economic operation of swapping station is implemented.Simulations based on actual data and statistical results from Beijing Beitucheng charging station and Shanghai World Expo charging station are respectively performed to validate the effectiveness of the proposed algorithm.Simulation results show that using the proposed algorithm not only the charging expenses of charging stations can be decreased,but also the pressure of load exerted on distribution network in daytime can be reduced and the load in nighttime can be raised and the peak-valley difference in distribution network can be mitigated,thus it contributes to the economic operation of distribution network while the economic operation of charging station is achieved.
出处
《电网技术》
EI
CSCD
北大核心
2013年第8期2101-2107,共7页
Power System Technology
基金
国家863高技术基金项目(2011AA05A108)
中央高校基本科研业务费专项资金资助(2013YJS084)~~
关键词
电动汽车
换电站
遗传算法
经济运行
充电功率
electric vehicle
battery swapping station
genetic algorithms
economic operation
charging power
