您的位置：山东大学 -> 科技期刊社 -> 《山东大学学报（工学版）》

山东大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (5): 118-122.doi: 10.6040/j.issn.1672-3961.0.2017.183

• • 上一篇    下一篇

基于小波奇异熵和SOM神经网络的微电网系统故障诊断

邱路1,叶银忠2*,姜春娣3   

  1. 1. 上海海事大学物流工程学院, 上海 201306;2. 上海应用技术大学电气与电子工程学院, 上海 201418;3. 衢州学院电气与信息工程学院, 浙江 衢州 324000
  • 收稿日期:2017-02-10 出版日期:2017-10-20 发布日期:2017-02-10
  • 通讯作者: 叶银忠(1964— )男,浙江建德人,教授,博士,主要研究方向为故障诊断与容错控制技术.E-mail: yzye@sit.edu.cn E-mail:qiuluchn@163.com
  • 作者简介:邱路(1986— ),男,福建武夷山人,博士研究生,主要研究方向为变拓扑系统的故障诊断技术.E-mail: qiuluchn@163.com
  • 基金资助:
    国家自然科学基金资助项目(61374132);浙江省公益基金资助项目(2016C31SA901322);上海海事大学研究生创新基金资助项目(2014ycx057)

Fault diagnostic method for micro-grid based on wavelet singularity entropy and SOM neural network

QIU Lu1, YE Yinzhong2*, JIANG Chundi3   

  1. 1. Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China;
    2. School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 201418, China;
    3. College of Electrical and Information Engineering, Quzhou University, Quzhou 324000, Zhejiang, China
  • Received:2017-02-10 Online:2017-10-20 Published:2017-02-10

PDF (PC)

618

摘要： 针对微电网系统运行方式灵活、拓扑结构多样的特点,基于对小波变换、奇异值分解和泛化信息熵基本理论的分析,揭示了小波奇异熵能够对故障信号给出确定的量度,将小波奇异熵与自组织特征映射(self-organizing feature map, SOM)神经网络相结合,提出一种能够适应微电网系统拓扑结构变化情况的故障诊断方法。 利用PSCAD4.2建立了微电网故障仿真系统,进行故障诊断仿真试验。 试验结果表明:该方法不受故障位置、故障时刻等因素的影响,在微电网系统拓扑结构发生变化的情况下,能实现有效的故障诊断。

关键词: 小波奇异熵, 微电网, 拓扑结构, 故障诊断, SOM神经网络

Abstract: According to the diversity of micro grids topology, through analyzing the theories of wavelet transform, singular value decomposition and extended shannon-entropy, the wavelet singular entropy could measure the fault signal. A fault diagnosis method for the micro grid system was proposed by integrating the wavelet singular entropy with the self organizing feature map(SOM)neural network. A micro grid fault simulation system was established by PSCAD4.2. The simulation results proved that the proposed diagnosis method was insensitive to the location and the time fault occurs, which had strong adaptability to the variation in structure topology.

Key words: SOM neural network, fault diagnosis, micro-grid, wavelet singular entropy, topology structure

中图分类号: 

  • TP18
[1] HATZIARGYRIOU N, ASAND H, ITAVANI R, et al. Microgrids[J]. IEEE Power and Energy Magazine, 2007, 5(4):78-94.
[2] 苏玲,张建华,王利,等.微电网相关问题及技术研究[J].电力系统保护与控制,2010,38(19):235-238. SU Ling, ZHANG Jianhua, WANG Li, et al. Study on some key problems and technique related to microgrid[J]. Power System Protection and Control, 2010, 38(19): 235-238.
[3] LI Y W, VILATHGAMUWA D M, POH C L. Micro grid power quality enhancement using a three-phase four-wire grid-interfacing compensator industry applications[J]. IEEE Transactions on Industry Applications, 2005, 41(6):1707-1719.
[4] 王成山,肖朝霞,王守相.微网综合控制与分析[J].电力系统自动化,2008,32(7):98-103. WANG Chengshan, XIAO Zhaoxia, WANG Shouxiang. Synthetical control and analysis of microgrid[J]. Automation of Electric Power Systems, 2008, 32(7): 98-103.
[5] 杨新法,苏剑,吕志鹏,等.微电网技术综述[J].中国电机工程学报,2014,34(1):57-70. YANG Xinfa, SU Jian, LYU Zhipeng, et al. Overview on micro-grid technology[J]. Proceedings of the CSEE, 2014, 34(1): 57-70.
[6] 肖宏飞,刘士荣,郑凌蔚,等.微型电网技术研究初探[J].电力系统保护与控制,2009,37(8):114-118. XIAO Hongfei, LIU Shirong, ZHENG Lingwei, et a1. A preliminary research on microgrid technology[J]. Power System Protection and Control, 2009, 37(8): 114-118.
[7] ZENG Z, YANG H, ZHAO R X, et al. Topologies and control strategies of multi-functional grid-connected inverters for power quality enhancement: A comprehensive review[J]. Renewable and Sustainable Energy Reviews, 2013, 24:223-270.
[8] WU T F, NIEN H S, CHEN C L. A single-phase inverter system for PV power injection and active power filtering with nonlinear inductor consideration[J]. IEEE Transactions on Industry Applications, 2005, 41(4): 1075-1081.
[9] ACHERMANN T, GARNER K, GARDINER A. Embedded wind generation in weak grids-economic optimization and power quality simulation[J]. Renewable Energy, 1999, 18(2): 205-221.
[10] MURAKAMIA A, YOKOYAMA A, TADA Y. Basic study on battery capacity evaluation for load frequency control(LFC)in power system with a large penetration of wind power generation[J]. IEEE Trans on Power and Energy, 2006, 126(2): 236-241.
[11] SORTOMME E, VENKATA S S, MITRA J. Microgrid protection using communication-assisted digital relays[J]. IEEE Transactions on Power Delivery, 2012, 25(4): 2789-2796.
[12] VENKATARAMANAN G, MARNAY C. A larger role for micro-grids[J]. IEEE Power and Energy Magazine, 2008, 6(3): 78-82.
[13] CORNFORTH D. Role of microgrids in the smartgrid[J]. Power, 2011, 40: 9-16.
[14] VILATHGAMUWA D M, LOH P C, LI Y. Protection of microgrids during utility voltage sags[J]. IEEE Transactions on Industrial Electronics, 2006, 53: 1427-1436.
[15] 张晗.基于模糊petri网的微电网故障诊断技术研究[D].北京:北京理工大学, 2015. ZHANG Han. Micro-grid fault diagnosis technology research based on fuzzy petri net[D]. Beijing: Beijing Institute of Technology, 2015.
[16] 王文瑞.基于解析模型的微电网故障诊断方法的研究[D].上海:上海应用技术学院, 2015. WANG Wenrui. Research on fault diagnosis method for micro-grid based on analytic model[D]. Shanghai: Shanghai Institute of Technology, 2015.
[17] WU H X, YANG G M, ZHANG A L, et al. Fault diagnosis of micro-grid based on petri net[C] //Proceedings of the 2012 International Conference on Electrical and Electronics Engineering. Shanghai, China: IEEE, 2012: 475-482.
[18] SHI J Y, SUN W S, LI C L. Fault diagnosis of micro-grid based on advanced petri net[C] //Proceeding of the 3rd International Conference on Mechanical and Electronics Engineering 2011. Hefei, China: IEEE, 2011: 3015-3018.
[19] HAN J Y, LIU H D. Fault detection method in micro-grid multi-pulse thyristor rectifier circuit[C] //Power and Energy Engineering Conference. Shanghai, China: IEEE, 2012: 1-4.
[20] HARE, JAMES, SHI X F, et al. A review of faults and fault diagnosis in micro-grids electrical energy infrastructure[C] //2014 IEEE Energy Conversion Congress and Exposition. Vienna, Austria: IEEE, 2014: 3325-3332.
[21] 李梦男.基于MAS的微电网拓扑识别研究[D].上海:上海应用技术学院, 2015. LI Mengnan. An investigetion on topology identification of microgrid based on MAS[D]. Shanghai:Shanghai Institute of Technology, 2015.
[22] 何正友,蔡玉梅,钱清泉.小波熵理论及其在电力系统故障检测中的应用研究[J].中国电机工程学报,2005,25(5):38-43. HE Zhengyou, CAI Yumei, QIAN Qingquan. A study of wavelet entropy theory and its application in power system fault detection[J]. Proceedings of the CSEE, 2005, 25(5): 38-43.
[23] 何正友,刘志刚,钱清泉.小波熵理论及其在电力系统中应用的可行性探讨[J].电网技术,2004,28(21):17-21. HE Zhengyou, LIU Zhigang, QIAN Qingquan. Study on wavelet entropy theory and adaptability of its application in power system[J]. Power System Technology, 2004, 28(21): 17-21.
[1] 程鑫,张林,胡业发,陈强,梁典. 基于电流特性的主动磁轴承电磁线圈故障诊断[J]. 山东大学学报(工学版), 2018, 48(4): 94-101.
[2] 程鑫,刘晗,王博,梁典,陈强. 基于双核处理器的主动磁悬浮轴承容错控制架构[J]. 山东大学学报(工学版), 2018, 48(2): 72-80.
[3] 王士柏,杜恒,武勇,刘洪正,程艳. 两级市场运行环境下微电网经济调度[J]. 山东大学学报(工学版), 2017, 47(6): 32-38.
[4] 王秀青,曾慧,解飞,吕峰. 基于Spiking神经网络的机械臂故障诊断[J]. 山东大学学报(工学版), 2017, 47(5): 15-21.
[5] 宋洋,钟麦英. 基于改进距离相似度的故障可分离性分析方法[J]. 山东大学学报(工学版), 2017, 47(5): 103-109.
[6] 李炜,王可宏,曹慧超. 基于新型ESF的一类非线性系统故障滤波方法[J]. 山东大学学报(工学版), 2017, 47(5): 7-14.
[7] 毛海杰,李炜,王可宏,冯小林. 基于自抗扰的多电机转速同步系统传感器故障切换容错策略[J]. 山东大学学报(工学版), 2017, 47(5): 64-70.
[8] 谢晓龙,姜斌,刘剑慰,蒋银行. 基于滑模观测器的异步电动机速度传感器故障诊断及容错控制[J]. 山东大学学报(工学版), 2017, 47(5): 210-214.
[9] 王梦园,张雄,马亮,彭开香. 基于因果拓扑图的工业过程故障诊断[J]. 山东大学学报(工学版), 2017, 47(5): 187-194.
[10] 孙源呈,姚利娜. 不确定奇异随机分布系统的故障诊断和容错控制[J]. 山东大学学报(工学版), 2017, 47(5): 238-245.
[11] 李明虎,李钢,钟麦英. 动态核主元分析在无人机故障诊断中的应用[J]. 山东大学学报(工学版), 2017, 47(5): 215-222.
[12] 刘卓,王天真,汤天浩,冯页帆,姚君琦,高迪驹. 一种多电平逆变器故障诊断与容错控制策略[J]. 山东大学学报(工学版), 2017, 47(5): 229-237.
[13] 吴建萍,姜斌,刘剑慰. 基于小波包信息熵和小波神经网络的异步电机故障诊断[J]. 山东大学学报(工学版), 2017, 47(5): 223-228.
[14] 崔阳,张柯,姜斌. 具有切换拓扑结构的多智能体系统故障估计[J]. 山东大学学报(工学版), 2017, 47(5): 263-270.
[15] 李静立,王谦,张军,李磊磊. 基于阶次分析的风电机组在线模态参数识别与故障诊断[J]. 山东大学学报(工学版), 2017, 47(4): 96-102.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 2018 《山东大学学报(工学版)》编辑部　
地址: 济南市山大南路27号（250100）　 电话: 0531-88366735　 E-mail: xbgxb@sdu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发