A Fault Diagnosis Method of Power Grid Based on Time Series Matching with Multi-Source Information

doi:10.3969/j.issn.1000－7229.2016.12.018

Abstract

Abstract: With the improvement of automation level of power dispatching and control center, measurement information from multiple sources, such as supervisory control and data acquisition (SCADA), wide-area measurement system (WAMS), relay protection information system, et al, is gathered to the unified database in the power dispatching and control center. In order to dig out several application scenarios of multi-source information in power dispatching and operation, this paper applies multi-source information in grid fault diagnosis and proposes a fault diagnosis method for power grid based on time series matching with multi-source information. Firstly, we introduce the database construction of multi-source information, the structure of power grid time series and the corresponding generative rules for different data sources. Then the suspicious fault areas and the power grid time series of the unknown fault are determined by sequence of event (SOE) information, protection operation information and electric measurements of phasor measurement unit (PMU) when the fault occurs. After that, the power grid time series of the unknown fault are matched with the standard time series sets that are produced according to the suspicious element's configuration information of protective relays in the suspicious fault areas. Then the detailed fault information is obtained, including fault elements, fault type, fault time, fault procedures and so on. Finally, the feasibility and effectiveness of the proposed method are validated by practical calculation example.

Key words: power system, multi-source information, time series, fault diagnosis

CLC Number:

TM 755

CHEN Weibiao, CHEN Yiping, YAO Wei, SUN Yanbin, WEN Jinyu. A Fault Diagnosis Method of Power Grid Based on Time Series Matching with Multi-Source Information [J]. Electric Power Construction, 2016, 37(12): 134-.

References

［1］唐斯庆, 张弥, 李建设, 等. 海南电网9.26大面积停电事故的分析与总结［J］. 电力系统自动化, 2006, 30(1): 1-7, 16.

TANG Siqing, ZHANG Mi, LI Jianshe, et al. Review of blackout in Hainan on September 26th-causes and recommendations［J］. Automation of Electric Power Systems, 2006, 30(1): 1-7, 16.

［2］宋晓喆, 汪震, 甘德强, 等. 台风天气条件下的电网暂态稳定风险评估［J］. 电力系统保护与控制, 2012, 40(24): 1-8.

SONG Xiaozhe, WANG Zhen, GAN Deqiang, et al．Transient stability risk assessment of power grid under typhoon weather［J］. Power System Protection and Control, 2012, 40(24): 1-8.

［3］陈亦平, 洪军. 巴西“11.10”大停电原因分析及对我国南方电网的启示［J］. 电网技术, 2010, 34(5): 77-82.

CHEN Yiping, HONG Jun. Analysis on causes of blackout occurred in Brazilian Power Grid on Nov. 11, 2009 and lessons drawn from it to China Southern Power Grid［J］. Power System Technology, 2010, 34(5): 77-82.

［4］廖志伟, 岳苓, 文福拴, 等. 基于规则网的高压输电线路故障诊断与保护动作性能评价［J］. 电力建设, 2016, 37(2): 34-41.

LIAO Zhiwei, YUE Ling, WEN Fushuan, et al. A rule network based approach for fault diagnosis of HV transmission lines and protection action performance evaluation［J］. Electric Power Construction, 2016, 37(2): 34-41.

［5］闪鑫, 赵家庆, 张剑, 等. 基于三态数据的电网在线综合故障诊断［J］. 电力系统自动化, 2012, 36(23): 78-91.

SHAN Xin, ZHAO Jiaqing, ZHANG Jian, et al. On-line comprehensive fault diagnosis of power grid basedon three-state data［J］. Automation of Electric Power Systems, 2012, 36(23): 78-91.

［6］杨健维, 何正友. 基于时序模糊Petri网的电力系统故障诊断［J］. 电力系统自动化, 2011, 35(15): 46-51.

YANG Jianwei, HE Zhengyou.Power system fault diagnosis approach based on time sequence fuzzy petri net［J］. Automation of Electric Power Systems, 2011, 35(15): 46-51.

［7］郭文鑫, 文福拴, 廖志伟, 等. 计及保护和断路器误动与拒动的电力系统故障诊断解析模型［J］. 电力系统自动化, 2009, 33(24): 6-10.

GUO Wenxin, WEN Fushuan, LIAO Zhiwei, et al. An analytic model for power system fault diagnosis with malfunctions of protective relays and circuit breakers taken into account［J］. Automation of Electric Power Systems, 2009, 33(24): 6-10.

［8］朱添益, 蒋铁铮, 罗杰, 等. 一种基于电气量数据的输电线路故障诊断方法［J］. 电力建设, 2014, 35(10): 74-78.

ZHU Tianyi, JIANG Tiezheng, LUO Jie, et al. Fault diagnosis method of transmission lines based on Electric quantity data［J］. Electric Power Construction, 2014, 35(10): 74-78.

［9］周子冠, 白晓民, 李文锋, 等. 基于广域测量系统的电网故障在线智能化诊断与分析方法［J］. 中国电机工程学报, 2009, 29(13): 1-7.

ZHOU Ziguan, BAI Xiaomin, LI Wenfeng, et al. A novel smart on-line fault diagnosis and analysis approach of power grid based on WAMS［J］. Proceedings of the CSEE, 2009, 29(13): 1-7.

［10］苏广宁, 张沛超, 胡炎, 等. 基于多源信息的电网故障诊断新方法［J］. 电力系统自动化, 2012, 36(1): 61-65.

SU Guangning, ZHANG Peichao, HU Yan, et al. A novel fault diagnosis method based on information fusion of multi-resources for power grids［J］. Automation of Electric Power Systems, 2012, 36(1): 61-65.

［11］吴文可, 文福拴, 薛禹胜, 等. 基于多源信息的延时约束加权模糊Petri网故障诊断模型［J］. 电力系统自动化, 2013,37(24): 43-53.

WU Wenke, WEN Fushuan, XUE Yusheng, et al. A weighted fuzzy petri net based model with time-delay constraints for power system fault diagnosis employing information from multiple sources［J］. Automation of Electric Power Systems, 2013, 37(24): 43-53.

［12］钟锦源, 张岩, 文福拴, 等. 基于时间序列相似性匹配的输电系统故障诊断方法［J］. 电力系统自动化, 2015, 39(6): 60-67.

ZHONG Jinyuan, ZHANG Yan, WEN Fushuan, et al. Afault diagnosing method in power transmission systems based on time series similarity matching［J］. Automation of Electric Power Systems, 2015, 39(6): 60-67.

［13］ KEOGH E, RATANAMAHATANA C A. Exact indexing of dynamic time warping［J］. Knowledge and Information Systems, 2005, 7(3): 358-386.

［14］ GOLAY X, KOLLIAS S, STOLL G, et al. A new correlation-based fuzzy logic clustering algorithm for fMRI［J］. Magnetic Resonance in Medicine, 1998, 40(2): 249-260.

［15］ MLLER-LEVET C S, KLAWONN F, CHOK H, et al. Fuzzy clustering of short time-series and unevenly distributed sampling points［C］ //International Symposium on Intelligent Data Analysis. Berlin. Germany: Springer Berlin Heidelberg, 2003: 330-340.

［16］ XI X, KEOGH E, SHELTON C, et al. Fast time series classification using numerosity reduction［C］//Proceedings of the 23rd International Conference on Machine Learning. Pittsburgh, Pennsylvania, USA:ACM, 2006: 1033-1040.

［17］王达, 荣冈. 时间序列的模式距离［J］．浙江大学学报(工学版), 2004, 38 (7)：795-798.

WANG Da, RONG Gang. Pattern distance of time series［J］. Journal of Zhejiang University（Engineering Science）, 2004, 38 (7)：795-798.

［18］国宏伟, 梁合兰, 刘燕驰, 等. 不规则时间序列距离的度量［J］. 计算机工程与应用, 2008, 44(35): 155-157.

GUO Hongwei, LIANG Helan, LIU Yanchi, et a1. Measurement of nonuniform time series distances［J］. Computer Engineering and Applications, 2008, 44(35): 155-157.

[1]	ZHENG TAO，ZHANG Zihang. Research on Internal Fault Diagnosis and Countermeasure of Modular Multilevel Converter Based on Half Bridge Sub-modules [J]. Electric Power Construction, 2018, 39(6): 42-.
[2]	ZHANG Yan, WEN Fushuan, XIONG Wen, NIU Zhenyong, ZHAO Hongwei, SHANG Huiyu . Wide Area Measurements Based Analytic Model for Power System Fault Diagnosis [J]. Electric Power Construction, 2018, 39(5): 10-.
[3]	ZHANG Yong1，LI Dan1，WEN Fushuan2，ZHANG Yan3，DONG Yi1，ZHENG Jianzi1. Process Level Fault Diagnosis in IEC 61850 Based Smart Substations [J]. Electric Power Construction, 2018, 39(3): 42-.
[4]	LIANG Rong, YANG Bo, MA Runze, WU Jian, WU Kuihua, LIN Zhenzhi, WEN Fushuan. Spatial Electric Load Forecasting for Distribution Systems Using Multi-source Information and Deep Belief Network-Deep Neural Network [J]. Electric Power Construction, 2018, 39(10): 12-19.
[5]	SHANG Huiyu, WANG Chongyu, CHEN Minghui, YANG Zeng, XIONG Wen, WEN Fushuan. A Feature Matching Based Method for Fault Diagnosis in Power Systems Under Disaster Weather [J]. Electric Power Construction, 2018, 39(10): 37-43.
[6]	JIANG Xuechen，ZHU Junpeng，YUAN Yue，WANG Yuefeng，HUANG Ruanming. Simulation Method Based on Improved Scenario Division Considering Temporal Correlation for PV Output Time Series [J]. Electric Power Construction, 2018, 39(10): 63-70.
[7]	WENG Yixuan, ZHAO Jie, CHENG Renli, LIU Dichen, XU Junru, ZHANG Shengfeng, HE Xiaofeng. Network-Reconfiguration Scheme Based on Node Search [J]. Electric Power Construction, 2018, 39(1): 76-.
[8]	ZHAO Yu，XIAO Bai，GU Bing，WANG Xiaoyi，ZHANG Yu，WANG Chenglong. Wind Power Time Series Model Based on Improved Markov Chain [J]. Electric Power Construction, 2017, 38(7): 18-.
[9]	WANG Shoupeng, ZHAO Dongmei . A Design Method for Power Grid Fault Diagnosis Model Based on Humoral Immunity Principle [J]. Electric Power Construction, 2017, 38(7): 131-.
[10]	ZHANG Wei，WANG Yingjie，WU Rongrong. An Improved Method for Compressing Time Series Data of Dissolved Gas Monitoring in Oil [J]. Electric Power Construction, 2017, 38(5): 98-.
[11]	PEI Tian, QI Donglian . Outlier Detection Method Based on Compressed Time Series and Voronoi Diagram for Power Data [J]. Electric Power Construction, 2017, 38(5): 105-.
[12]	YANG Yinguo,　TAN Yan, LIN Zhenzhi, WEN Fushuan. Black-Start Zoning Strategy Based Semi-Supervised Spectral Clustering Algorithm [J]. Electric Power Construction, 2017, 38(4): 9-.
[13]	QIAN Feng, FENG Changsen, WEN Fushuan, LI Li, TAN Yan, LIANG Yongqing. Robust Optimization Based Security-Constrained Unit Commitment [J]. Electric Power Construction, 2017, 38(4): 18-.
[14]	LAN Xiaoming, WANG Ying, ZHAO Hongshan, MI Zengqiang. Nonlinear Voltage Prediction Control of Power System Based on Dynamic Reduced Model [J]. Electric Power Construction, 2017, 38(3): 34-.
[15]	CHENG Lin, WANG Ying, SONG Fulong, LUO Jinshan, LIU Manjun. Reliability Evaluation of Flexible AC/DC Hybrid Power Grid [J]. Electric Power Construction, 2017, 38(3): 55-.