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换电站与电网协调的多目标双层实时充放电调度方法(2015年第4期)
类别:联席会学术论文专栏 发布时间:[2015-06-08] 点击数:981

曹一家1,刘易珠1,阙凌燕2,卢  敏2,李  勇1,黄小庆1,辛建波3
(1. 湖南大学 电气与信息工程学院,湖南 长沙 410082;
2. 国网浙江省电力公司,浙江 杭州 310007;3. 国网江西省电力科学研究院,江西 南昌 330006)

摘要: 大规模电动汽车无序充电会对电网安全经济运行及换电站经济运营产生严重的负面影响。计及未入网电动汽车充换电预测,考虑电力网络运行、大规模电动汽车用户充换电需求等约束,建立了换电站与电网协
调的多目标双层实时充放电调度模型,其中上层模型以电网负荷波动最小和上下层调度偏差最小为目标,由上层调度机构安排各换电站实时充放电计划;下层以各充放电装置响应上层计划为目标,同时满足用户充换电需求,将大规模混合整数非线性规划问题转化为非线性多目标规划问题和大规模混合整数线性规划问题。采用基于Zaslavskii 混沌映射的改进NSGA鄄Ⅱ和YALMIP / CPLEX 求解方式对上下层问题分别进行迭代求解滚动优化。以IEEE 30 节点系统为例,验证了所构建模型的正确性和有效性。
关键词: 电动汽车; 换电站; 换电站协调入网; 充放电滚动优化; Zaslavskii 映射; 多目标双层优化; 模型; 优化; 调度

Multi-objective bi-level real-time charging / discharging dispatch
with coordination of BSS and grid
CAO Yijia1,LIU Yizhu1,QUE Lingyan2,LU Min2,LI Yong1,HUANG Xiaoqing1,XIN Jianbo3
(1. College of Electrical and Information Engineering,Hunan University,Changsha 410082,China;
2. Zhejiang Electric Power Company of State Grid Corporation of China,Hangzhou 310007,China;
3. Jiangxi Electric Power Research Institute of State Grid Corporation of China,Nanchang 330006,China)

Abstract: The disordered charging of numerous EVs(Electric Vehicles) may produce significant negative impacts on the secure and economic operation of both grid and BSS(Battery Swapping Station). A multi-objective bi-level optimization model of real-time charging / discharging dispatch with coordination of BSS and grid is established,which considers the prediction of incoming EVs,the battery swapping needs of customers and the operational constraints of grid and BBS. The upper-level model takes the minimum grid load variation and the minimum dispatch deviation between two levels as its objectives and lets the upper-level dispatch center determine the real-time charging / discharging schedule for every BSS,while the lower-level model takes the response of every charging / discharging device to the schedule of upper-level dispatch and the battery swapping needs of customers as its objectives and converts the large-scale mixed-integer nonlinear programming into a nonlinear multi-objective programming and a large-scale MILP(Mixed Integer Linear Programming). Improved NSGA-Ⅱ based on Zaslavskii chaotic map and YALMIP / CPLEX are employed to solve two models respectively. The IEEE 30-bus system is employed to demonstrate the feasibility and efficiency of the proposed models.
Key words: electric vehicles; battery swapping stations; BSS to grid; charging and discharging receding horizon optimization; Zaslavskii chaotic map; multi-objective bi-level optimization; models; optimization; dispatch

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