| 引用本文: | 王毅,陈进,麻秀,侯兴哲,郑可,陈文礼.采用分群优化的电动汽车与电网互动调度策略[J].电力自动化设备,2020,40(5): |
| WANG Yi,CHEN Jin,MA Xiu,HOU Xingzhe,ZHENG Ke,CHEN Wenli.Interactive scheduling strategy between electric vehicles and power grid based on group optimization[J].Electric Power Automation Equipment,2020,40(5): |
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| 摘要: |
| 大规模电动汽车(EV)无序充电将会威胁电网的安全运行。为此，提出一种采用分群优化的电动汽车与电网互动调度策略。首先，根据EV的电池约束、时间约束及充放电转换次数约束，将各时段的EV动态划分为常规车群和调控车群，常规车群进行无序充电，调控车群包含充电车群和放电车群；然后，在控制中心以车群划分情况和车群负荷信息为约束条件，优化调控车群的可调度负荷使研究时段内的总负荷方差最小化；最后，根据EV的出行约束计算EV的权系数，采用功率分配算法控制充放电功率不高于可调度负荷值。所提方法能保证EV在满足出行需求的情况下，对电网进行削峰填谷。算例结果验证了所提方法的合理性和有效性；所提调度策略方案实施简单，效果明显，有利于进行实际应用。 |
| 关键词: 电动汽车 电动汽车与电网互动 分群优化 功率分配 削峰填谷 调度策略 |
| DOI：10.16081/j.epae.202004010 |
| 分类号:U469.72;TM73 |
| 基金项目:中国博士后基金资助项目(2015T80961)；重庆市教委科学研究项目(KJ120531)；国家科技支撑计划项目(2015BAG10B00) |
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| Interactive scheduling strategy between electric vehicles and power grid based on group optimization |
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WANG Yi1,2,3, CHEN Jin1, MA Xiu1, HOU Xingzhe2, ZHENG Ke2, CHEN Wenli2
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1.School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;2.Electric Power Research Institute of State Grid Chongqing Electric Power Company, Chongqing 400014, China;3.Postdoctoral Workstation of State Grid Chongqing Electric Power Company, Chongqing 400014, China
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| Abstract: |
| The disordered charging of large scale EVs(Electric Vehicles) will threaten the safe operation of power grid. Therefore, an interactive scheduling strategy between EVs and power grid based on group optimization is proposed. Firstly, according to the constraints of battery, time and charging/discharging conversion number, the EVs are dynamically divided into regular EV group and controllable EV group in each period. The regular EV group is charged disorderly, and the controllable EV group includes charging EV group and discharging EV group. Then, in the control center, the division condition of EV groups and their load information are taken as constraints, and the schedulable load of the controllable EV group is optimized to minimize the variance of the total load in the study period. Finally, the weight coefficients of EVs are calculated based on EVs’ travel constraints, and the power allocation algorithm is adopted to control the charging/discharging power not higher than the schedulable load value. The proposed method can ensure that EVs can realize peak load shifting for power grid under the condition of meeting the travel demand. The example results verify the rationality and validity of the proposed method. The proposed scheduling strategy scheme is simple and effective, which is beneficial to practical application. |
| Key words: electric vehicles vehicle to grid group optimization power allocation peak load shifting scheduling strategy |
