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考虑规模化电动汽车与风电接入的随机解耦协同调度
作者:
作者单位:

1.上海电力大学电气工程学院,上海市200090;2.国网江苏省电力有限公司盐城供电公司,江苏省盐城市 224005;3.上海市电力公司市北供电公司,上海市 200072

作者简介:

葛晓琳(1988—),女,通信作者,博士,副教授,主要研究方向:电力系统优化调度。E-mail:gexiaolin2005@126.com
郝广东(1992—),男,硕士研究生,主要研究方向:电力优化调度。E-mail:h_dean@163.com
夏 澍(1987—),男,高级工程师,主要研究方向:电力系统优化运行。E-mail:289709281@qq.com

通讯作者:

基金项目:

国家自然科学基金资助项目(51507100);上海市科委项目(18DZ1203200);上海市科委地方能力建设计划资助项目(16020500900)。


Stochastic Decoupling Collaborative Dispatch Considering Integration of Large-scale Electric Vehicles and Wind Power
Author:
Affiliation:

1.College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;2.Yancheng Power Supply Company of State Grid Jiangsu Electric Power Co., Ltd., Yancheng 224005, China;3.Shibei Power Supply Company of State Grid Shanghai Municipal Electric Power Company, Shanghai 200072, China

Fund Project:

This work is supported by National Natural Science Foundation of China (No. 51507100), Scientific Research Plan Project of Shanghai Science and Technology Commission (No. 18DZ1203200) and Local Capacity-building Plan of Shanghai Municipal Science and Technology Commission (No. 16020500900).

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    摘要:

    大规模电动汽车并网和风电出力的随机性增加了电力系统安全经济运行的难度。针对风电出力难以预测的特点,同时兼顾电网侧和电动汽车聚合商侧的运行效益,建立了风电、火电以及电动汽车鲁棒双层随机优化调度模型。为了提高求解效率,基于近似Benders算法构建了电动汽车与电网之间的互动关系。此外,针对规模化电动汽车之间难以协同优化的问题,运用辅助问题原理对电动汽车个体之间的耦合关系进行了解耦,将电动汽车群的联合优化转化成为单辆电动汽车调度的并行计算,实现了对电动汽车个体的调度。最后,针对改进的IEEE 39节点算例进行了仿真分析,验证了所提模型和算法的有效性。

    Abstract:

    The randomness of large-scale electric vehicles (EVs) connected to power grid and wind power output increases the difficulty of safe and economic operation of power system. In view of the unpredictable characteristics of wind power output and considering operational benefits of system and EV aggregators, a robust two-layer stochastic optimal dispatch model of wind power, thermal power and EVs is established. In order to improve the solution efficiency, the interaction between EVs and power grid is constructed based on the approximate Benders algorithm. In addition, in order to solve the problem of difficult coordination and optimization between large-scale EVs, the coupling relationship between individual EVs is coupled by the auxiliary problem principle, and the joint optimization of EV groups is transformed into the parallel computation of a single EV dispatch, which realizes the individual dispatch of EV. Finally, the simulation analysis of the improved IEEE 39-bus system is carried out to verify the effectiveness of the proposed model and algorithm.

    表 5 电动汽车群解耦对优化结果的影响Table 5 Influence of decoupling of EV group on optimization results
    表 3 2种模型的结果比较Table 3 Comparison of two models
    表 1 电动汽车类型分布Table 1 Distribution of EV types
    表 2 不同运行模式下的优化结果对比Table 2 Comparison of optimization results in different operation modes
    图1 电动汽车与风、火电协同调度Fig.1 Coordinated dispatch of EVs with wind power and thermal power
    图2 风电出力的预测值及出力上下界Fig.2 Prediction value and the upper/lower boundaries of wind power output
    图3 不同运行模式下的弃风量对比Fig.3 Comparison of curtailed wind power in different operation modes
    图4 误差变化曲线Fig.4 Curves of error variation
    图5 总成本变化曲线Fig.5 Curve of total cost variation
    图 算法流程图Fig. Flow chart of the proposed algorithm
    表 4 2种算法的计算性能Table 4 Calculation performance of two methods
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引用本文

葛晓琳,郝广东,夏澍,等.考虑规模化电动汽车与风电接入的随机解耦协同调度[J].电力系统自动化,2020,44(4):54-62. DOI:10.7500/AEPS20190227003.
GE Xiaolin,HAO Guangdong,XIA Shu,et al.Stochastic Decoupling Collaborative Dispatch Considering Integration of Large-scale Electric Vehicles and Wind Power[J].Automation of Electric Power Systems,2020,44(4):54-62. DOI:10.7500/AEPS20190227003.

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历史
  • 收稿日期:2019-02-27
  • 最后修改日期:2019-06-11
  • 录用日期:2019-07-11
  • 在线发布日期: 2020-02-16
  • 出版日期: