电压暂降可观约束下的定位监测点多目标优化配置

doi:10.19595/j.cnki.1000-6753.tces.180647

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摘要为有效监测电压暂降以及准确定位扰动源位置,提出了可观约束下的电压暂降定位监测点的多目标优化配置方法。基于测点间正序电压变化量的相关性,定义了暂降特征模式,通过寻找最优匹配模式进行故障定位,同时定义不确定区域指数作为测点集的定位准确性指标。以全网电压暂降可观为约束条件,以监测点数量最少和不确定区域指数最小为目标函数,建立监测点多目标优化模型。采用多目标离散粒子群算法求解模型,得到非劣解集。通过IEEE 39和IEEE 118节点系统验证了该方法的可行性和有效性。

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	张嫣
	林涌艺
	邵振国

关键词 ：电压暂降定位, 可观性, 优化配置, 多目标优化

Abstract：A multi-objective optimal method of monitors for voltage sag location under observability constraint is proposed. It uses positive sequence voltage variation as sag pattern and defines the distance of pattern to find the most likely fault location. Then the uncertainty region index is defined to measure the locating accuracy of the measuring set. Finally the multi-objective monitoring optimization model is established which takes the observability of voltage sag as the constraint condition and takes the minimum number of monitoring points and the minimum uncertainty index as the objective function. The multi-objective discrete particle swarm optimization algorithm is used to get the non-inferior solution set. The feasibility and validity of the method are verified by IEEE 39 and IEEE 118 node system.

Key words： Voltage sag location observability optimal allocation multi-objective optimization

收稿日期: 2018-04-19 出版日期: 2019-06-14

PACS:

TM711

基金资助:国家自然科学基金（51777035）和福建省自然科学基金（2016J01219）资助

通讯作者: 邵振国男,1970年生,教授,研究方向为电能质量及新能源发电优化运行等。E-mail：shao.zg@fzu.edu.cn

作者简介: 张嫣女,1979年生,硕士,讲师,研究方向为电能质量及电力系统稳定与控制等。E-mail：zyww@fzu.edu.cn

引用本文:

张嫣, 林涌艺, 邵振国. 电压暂降可观约束下的定位监测点多目标优化配置[J]. 电工技术学报, 2019, 34(11): 2375-2383. Zhang Yan, Lin Yongyi, Shao Zhenguo. Multi-Objective Optimal Allocation of Monitors for Voltage Sag Location under Observability Constraint. Transactions of China Electrotechnical Society, 2019, 34(11): 2375-2383.

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[1] 陈礼频, 杜新伟, 汪伟, 等. 考虑故障电阻随机不确定性的电压暂降监测点优化配置[J]. 电工技术学报, 2016, 31(23): 93-99.
Chen Linpin, Du Xinwei, Wang Wei, et al.Optimal voltage sag monitors placement considering randomness of fault resistance[J]. Transactions of China Electrotechnical Society, 2016, 31(23): 93-99.
[2] 程志友, 王雪菲, 徐佳. 一种基于复阻抗的电压暂降定位方法[J]. 电力系统保护与控制, 2016, 44(4): 149-154.
Cheng Zhiyou, Wang Xuefei, Xu Jia.A voltage sag detection method based on complex impedance[J]. Power System Protection and Control, 2016, 44(4): 149-154.
[3] 黄飞腾, 南余蓉, 翁国庆, 等. DG并网对暂态电压扰动方向判定的影响极其校正算法[J]. 电工技术学报, 2017, 32(23): 176-184.
Huang Feiteng, Nan Yurong, Weng Guoqing, et al.Correction algorithm of direction finding for transient voltage disturbance considering distributed generators[J]. Transactions of China Electrotechnical Society, 2017, 32(23): 176-184.
[4] 刘颖英, 王同勋, 冯丹丹, 等. 基于多重判据的电压暂降故障源定位方法[J]. 中国电机工程学报, 2015, 35(1): 103-111.
Liu Yingying, Wang Tongxun, Feng Dandan, et al.Multiple criterions based voltage sag location method[J]. Proceeding of the CSEE, 2015, 35(1): 103-111.
[5] Olguin G, Vuinovich F, Bollen M H J. An optimal monitoring program for obtaining Voltage sag system indexes[J]. IEEE Transactions on Power Systems, 2006, 21(1): 378-384.
[6] Espinosa-Juarez E, Hernandez A, Olguin G.An approach based on analytical expressions for optimal location of voltage sags monitors[J]. IEEE Transactions on Power Delivery, 2009, 24(4): 2034-2042.
[7] 郎福龙, 田立军, 王滕藤. 基于电压暂降监测点优化配置的同心松弛凹陷域分析[J]. 电力系统保护与控制, 2017, 45(18): 96-101.
Lang Fulong, Tian Lijun, Wang Tengteng.An analysis to the concentric relaxation vulnerability area of voltage sag based on optimal allocation of voltage sag monitors[J]. Power System Protection and Control, 2017, 45(18): 96-101.
[8] 周超, 田立军. 基于粒子群优化算法的电压暂降监测点优化配置[J]. 电工技术学报, 2014, 29(4): 181-187.
Zhou Chao, Tian Lijun.An optimum allocation method of voltage sag monitoring nodes based on particle swarm optimization algorithm[J]. Transactions of China Electrotechnical Society, 2014, 29(4): 181-187.
[9] 邱玉涛, 肖先勇, 熊茜, 等. 基于临界阻抗和广度优先-条件搜索的暂降监测装置优化配置[J]. 电力自动化设备, 2014, 34(10): 138-143.
Qiu Yutao, Xiao Xianyong, Xiong Qian, et al.Optimal sag monitor placement based on critical impedance and breadth first-condition search[J]. Electric Power Automation Equipment, 2014, 34(10): 138-143.
[10] 王东旭, 乐健, 刘开培, 等. 基于线路分段法的电压跌落监测网络优化布点策略[J]. 电工技术学报, 2011, 26(10): 31-38.
Wang Dongxu, Le Jian, Liu Kaipei, et al.Optimal location strategy of voltage dip monitoring network based on line sectionalizing method[J]. Transactions of China Electrotechnical Society, 2011, 26(10): 31-38.
[11] 唐琳, 肖先勇, 张逸, 等. 电压暂降状态和水平评估模式匹配法与监测装置多目标优化配置[J]. 中国电机工程学报, 2015, 35(13): 3264-3271.
Tang Lin, Xiao Xianyong, Zhang Yi, et al.Voltage sag state and level assessment based on pattern matching method and multi-objective optimal monitors allocation[J]. Proceedings of the CSEE, 2015, 35(13): 3264-3271.
[12] 周超, 田立军, 侯燕文, 等. 基于监测点优化配置的电压暂降故障点定位估计[J]. 电力系统自动化, 2012, 36(16): 102-107.
Zhou Chao, Tian Lijun, Hou Yanwen, et al.Fault location estimation based on optimal voltage sag monitoring program[J]. Automation of Electric Power Systems, 2012, 36(16): 102-107.
[13] 邱玉涛, 肖先勇, 赵恒, 等. 满足电压暂降与故障位置均可观的监测装置二阶段配置[J]. 电网技术, 2014, 38(11): 3171-3177.
Qiu Yutao, Xiao Xianyong, Zhao Heng, et al.A placement approach of two-stage monitors making both voltage sag and fault position observable[J]. Power System Technology, 2014, 38(11): 3171-3177.
[14] 陈礼频, 肖先勇, 张文海. 考虑扰动源定位的电压暂降监测点最优配置[J]. 电力自动化设备, 2014, 34(2): 79-84, 90.
Chen Lipin, Xiao Xianyong, Zhang Wenhai.Optimal allocation of voltage-sag monitors considering disturbance-source locating[J]. Electric Power Automation Equipment, 2014, 34(2): 79-84, 90.
[15] Liao Yuan.Fault location observability analysis and optimal meter placement based on voltage measurements[J]. Electric Power Systems Research, 2009, 79(7): 1062-1068.
[16] 谭丹, 杨洪耕. 基于故障识别法的电压暂降监测点的优化配置[J]. 电力系统保护与控制, 2013, 41(20): 7-12.
Tan Dan, Yang Honggeng.An optimum allocation of voltage sag monitor based on fault recognition method[J]. Power System Protection and Control, 2013, 41(20): 7-12.
[17] Avendano-Mora M, Milanovic J V.Monitor placement for reliable estimation of voltage sags in power networks[J]. IEEE Transactions on Power Delivery, 2012, 27(2): 936-944.
[18] 张利彪, 周春光, 马铭, 等. 基于粒子群算法求解多目标优化问题[J]. 计算机研究与发展, 2004, 41(7): 1286-1291.
Zhang Libiao, Zhou Chunguang, Ma Ming, et al.Solutions of multi objective optimization problems based on particle swarm optimization[J]. Journal of Computer Research and Development, 2004, 41(7): 1286-1291.
[19] 唐亚迪, 徐永海, 洪旺松. 基于模糊控制模型的电压暂降监测装置优化配置[J]. 电力自动化设备, 2015, 35(8): 65-71.
Tang Yadi, Xu Yonghai, Hong Wangsong.Allocation optimization based on fuzzy control model for voltage-sag monitors[J]. Electric Power Automation Equipment, 2015, 35(8): 65-71.
[20] 刘平, 欧阳森, 蔡东阳. 考虑变电站电压暂降严重性的暂降监测装置优化配置[J]. 电网技术, 2016, 40(2): 634-641.
Liu Ping, Ouyang Sen, Cai Dongyang.Research on the optimal configuration of sag monitoring devices by considering the voltage sag severity of substations[J]. Power System Technology, 2016, 40(2): 634-641.
[21] 林涌艺, 邵振国, 张嫣, 等. 基于多测点正序电压相关性与典型模式匹配寻优的电压暂降源定位[J]. 电工技术学报, 2017, 32(17): 35-46.
Lin Yongyi, Shao Zhenguo, Zhang Yan, et al.Voltage sag source location based on the correlation of multipoint positive sequence voltage and the typical pattern matching optimization[J]. Transactions of China Electrotechnical Society, 2017, 32(17): 35-46.
[22] Park C H, Jang G.Stochastic estimation of voltage sags in a large meshed network[J]. IEEE Transactions on Power Delivery, 2007, 22(3): 1655-1664.
[23] 孙国强, 卫志农, 唐利锋, 等. 多目标配电网故障定位的Pareto进化算法[J]. 电力自动化设备, 2012, 32(5): 57-61, 73.
Sun Guoqiang, Wei Zhinong, Tang Lifeng, et al.Pareto evolutionary algorithm for multi-objective fault location of distribution network[J]. Electric Power Automation Equipment, 2012, 32(5): 57-61, 73.
[24] Kennedy J, Eberhart R C.A discrete binary version of the particle swarm algorithm[J]. Computational Cybernetics and Simulation, 1997, 5: 4104-4108.
[25] 王荣海, 胥勋涛, 申慧. 基于粒子群优化算法的多目标搜索算法[J]. 兵工自动化, 2013, 32(1): 24-27.
Wang Ronghai, Xu Xuntao, Shen Hui.Multi-objective searching algorithm based on particle swarm optimization[J]. Ordnance Industry Automation, 2013, 32(1): 24-27.