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| 基于有序充电的换电站电池冗余度研究 | |
| 引用本文： | 汤波,马世伟,邱云,郑一峰,张绮华,符杨.基于有序充电的换电站电池冗余度研究[J].电力系统自动化,2015,39(10):50-55. |
| 作者姓名： | 汤波 马世伟 邱云 郑一峰 张绮华 符杨 |
| 作者单位： | 1. 上海大学机电工程与自动化学院，上海市 200072; 上海电力学院电气工程学院，上海市 200090 2. 上海大学机电工程与自动化学院,上海市,200072 3. 国网宁波供电公司,浙江省宁波市,315010 4. 国网宁波市鄞州区供电公司,浙江省宁波市,315010 5. 上海电力学院电气工程学院,上海市,200090 |
| 基金项目： | 国家自然科学基金资助项目(51207088);上海市重点支撑攻关计划资助项目(13160500800);上海绿色能源并网工程技术研究中心资助项目(13DZ2251900) |
| 摘 要： | 电动汽车大规模接入电网后,有序充电优化控制具有便于集中管理、抑制负荷波动、降低峰谷差和充电费用等优势,但同时也带来换电站电池冗余度增大的问题。文中针对换电模式,以抑制电网总体负荷波动为有序充电主要目标,采用自适应遗传算法,建立有序充电模式下换电站电池冗余度模型,并使用蒙特卡洛方法模拟电动汽车用户的用车需求。对比分析无序充电和有序充电模式下换电站电池冗余度仿真结果,表明该有序充电策略能够有效削减负荷波动,减小峰谷差,但也相应提升了换电站电池冗余度。 |
| 关 键 词： | 电动汽车 有序充电 电池冗余度 负荷波动 自适应遗传算法 |
| 收稿时间： | 2014/5/21 0:00:00 |
| 修稿时间： | 1/7/2015 12:00:00 AM |
Battery Redundancy of Swapping Station Under Coordinated Charging |
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| TANG Bo,MA Shiwei,QIU Yun,ZHENG Yifeng,ZHANG Qihua and FU Yang.Battery Redundancy of Swapping Station Under Coordinated Charging[J].Automation of Electric Power Systems,2015,39(10):50-55. | |
| Authors: | TANG Bo MA Shiwei QIU Yun ZHENG Yifeng ZHANG Qihua and FU Yang |
| Affiliation: | School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China; School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China,School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China,State Grid Ningbo Power Supply Company, Ningbo 315010, China,State Grid Ningbo Yinzhou Power Supply Company, Ningbo 315010, China,State Grid Ningbo Power Supply Company, Ningbo 315010, China and School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China |
| Abstract: | Coordinated charging by large-scale application of electric vehicles will bring benefits such as facilitating centralized management, inhibiting load fluctuation and reducing the charging cost. Despite the positive effects, it will bring about disadvantages of battery redundancy to swapping station. For the sake of concentrating on battery redundancy under coordinated charging, a load fluctuation optimization model is developed in battery swapping modes using the adaptive genetic algorithm, with the power demand of electric vehicles analyzed through Monte Carlo method. Calculation results show that compared to the uncoordinated charging scenario, the coordinated charging model can not only restrain load fluctuation and peak-valley, but, as a result, increase battery redundancy. This work is supported by National Natural Science Foundation of China (No. 51207088) and Shanghai Key Supported Research Program (No. 13160500800). |
| Keywords: | electric vehicles coordinated charging battery redundancy load fluctuation adaptive genetic algorithm |
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