输电线路状态检修专家系统的研究
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摘要
目前我国输电线路仍以定期检修为主。状态检修(Condition-based Maintenance,CBM)作为一种新发展起来的检修方式,已在电网企业中得到广泛认可和应用。状态检修是根据设备的运行状态来决定是否检修,能够有效和实时的保障设备安全。实现输电线路状态检修,可以减少检修的盲目性、提高输电线路的运行稳定性、节省电网开支、减轻工人劳动强度、促进电力系统信息化的发展。
输电线路状态检修工作开展进度远不及发电厂和变电站,针对这一现象,本文提出了提高输电线路状态检修工作效率的三个重要环节,即更客观的状态评价、更准确的预测判断和将输电检修平面从“面”过渡到“点”。针对这三点,设计并开发了一套立体专家系统,分别包括状态评价专家、预测判断专家和计算机处理专家。
本文以北京某单位“输电线路在线监测与状态检修系统”项目为依托,搭建了输电线路状态检修的信息管理平台,实现了对线路视频监控信息、绝缘子泄漏电流信息和导线温度信息的可视化管理；将地理信息系统(Geographic Information System, GIS)融入到了输电线路状态检修系统中,实现了监测杆塔优化选址、输电线路台账无纸化查询、污区等级划分和绝缘校验的功能；设计了一种基于层次分析法的输电线路状态模糊评价系统；提出了一种多方法组合的等值盐密模糊预测模型,并将预测结果作为GIS污区划分的主要依据。
At present, the main maintenance pattern of transmitting lines is still regular maintenance. As a new developing maintenance, CBM (Condition-based Maintenance) has been widely recognized and applied in the power grid. CBM decides whether to repair or not by equipments' conditions, and can provides an effective and real-time protection for facilities. Transmitting lines CBM can reduces the blindness of maintenance, improves the running stability, saves expenses, reduces the labor intensity, and promotes the development of information technology of the power system.
Transmitting lines CBM is far from power plants and substations. For this phenomenon, three important aspects for improving CBM's efficiency have been put forward in this paper. These aspects include a more objective state evaluation, a more accurate forecast judgment, and make transmission maintenance flat transform from "surface" to "point". For these three aspects, this paper proposes a set of three-dimensional expert system, including the state evaluation experts, prediction and judgment experts, and computer processing experts.
This paper depends on a project named "Online monitoring and condition based maintenance system of the transmission lines" of a company in Beijing, Builds a CBM information management system, which can monitor video information, leakage current and conductor temperature. Pull GIS in transmitting lines CBM information management system, which can optimize the location of monitoring tower, query transmission lines ledger in computer, divide polluted area level and check insulation. Put forward a fuzzy evaluation system based on the Analytic Hierarchy Process for transmitting lines. Promote a multi-method combination fuzzy prediction model for the prediction of ESDD, and use the forecast value as the as the main basis for drawing the polluted area map in GIS.
输电线路状态检修工作开展进度远不及发电厂和变电站,针对这一现象,本文提出了提高输电线路状态检修工作效率的三个重要环节,即更客观的状态评价、更准确的预测判断和将输电检修平面从“面”过渡到“点”。针对这三点,设计并开发了一套立体专家系统,分别包括状态评价专家、预测判断专家和计算机处理专家。
本文以北京某单位“输电线路在线监测与状态检修系统”项目为依托,搭建了输电线路状态检修的信息管理平台,实现了对线路视频监控信息、绝缘子泄漏电流信息和导线温度信息的可视化管理；将地理信息系统(Geographic Information System, GIS)融入到了输电线路状态检修系统中,实现了监测杆塔优化选址、输电线路台账无纸化查询、污区等级划分和绝缘校验的功能；设计了一种基于层次分析法的输电线路状态模糊评价系统；提出了一种多方法组合的等值盐密模糊预测模型,并将预测结果作为GIS污区划分的主要依据。
At present, the main maintenance pattern of transmitting lines is still regular maintenance. As a new developing maintenance, CBM (Condition-based Maintenance) has been widely recognized and applied in the power grid. CBM decides whether to repair or not by equipments' conditions, and can provides an effective and real-time protection for facilities. Transmitting lines CBM can reduces the blindness of maintenance, improves the running stability, saves expenses, reduces the labor intensity, and promotes the development of information technology of the power system.
Transmitting lines CBM is far from power plants and substations. For this phenomenon, three important aspects for improving CBM's efficiency have been put forward in this paper. These aspects include a more objective state evaluation, a more accurate forecast judgment, and make transmission maintenance flat transform from "surface" to "point". For these three aspects, this paper proposes a set of three-dimensional expert system, including the state evaluation experts, prediction and judgment experts, and computer processing experts.
This paper depends on a project named "Online monitoring and condition based maintenance system of the transmission lines" of a company in Beijing, Builds a CBM information management system, which can monitor video information, leakage current and conductor temperature. Pull GIS in transmitting lines CBM information management system, which can optimize the location of monitoring tower, query transmission lines ledger in computer, divide polluted area level and check insulation. Put forward a fuzzy evaluation system based on the Analytic Hierarchy Process for transmitting lines. Promote a multi-method combination fuzzy prediction model for the prediction of ESDD, and use the forecast value as the as the main basis for drawing the polluted area map in GIS.
引文
[1]李景禄,李青山等.电力系统状态检修技术[M].中国水利水电出版社,2011.
[2]陈安伟.输变电设备状态检修的应用[J].电网技术,2009,33(27):215-218.
[3]王计朝.输电线路状态检修技术的研究[D].北京：华北电力大学,2009.
[4]安玲.架空输电线路状态检修技术[D].上海：上海交通大学,2002.
[5]宋华松.平面镜法测量杆塔倾斜率[J].安徽建筑,2008,6:196-197.
[6]国家电网公司企业标准,Q/GDW 173,架空输电线路状态评价导则,2008.
[7]陆佳政,蒋正龙,雷红才等.湖南电网2008年冰灾事故分析[J].电力系统自动化,2008,32(11)：16-19.
[8]中华人民共和国电力行业标准,DL/T 741-2001,架空送电线路运行规程,2001.
[9]中华人民共和国国家标准,GB/T2314-2008,电力金具通用技术条件,2008.
[10]黄新波等.输电线路在线监测与故障诊断[M].中国电力出版社,2008.
[11]中华人民共和国电力工业部,DL/T 596-1996,电力设备预防性试验规程,1996.
[12]蔡自兴,徐光佑.人工智能及其应用[M].清华大学出版社,2010.
[13]李国勇.智能预测控制及其MATLAB实现[M].电子工业出版社,2009.
[14]敖志刚.人工智能及专家系统[M].机械工业出版社,2010.
[15]尉敏.基于模糊神经网络的绝缘子状态检测新方法的研究[D].南京：东南大学,2006.
[16]史兴华等.电网GIS及其应用[M].中国电力出版社,2010.
[17]陈雄波,孟遂民,秦红玲.基于GIS的输电线路运行管理系统数据库设计[J].电力建设,2005,26(8)：65-68.
[18]黄新波,孙钦东,张冠军等.在线监测和GIS用于输电线路管理系统[J].高电压技术,2007,33(6)：118-122.
[19]孟遂民,李光辉.架空输电线路设计[M].中国三峡出版社,2000.
[20]王密,龚健雅,李德仁.大型遥感影像数据库的空间无缝数据组织[J].武汉大学学报·信息科学版,2001,26(5)：419-424
[21]王伟.河南省电网污秽区域分布自动生成系统的研究[D].北京：华北电力大学,2009.
[22]中华人民共和国国家标准,GB/T 16434,高压架空线路和发电厂、变电所环境污区分级及外绝缘选择标准,1996.
[23]刘诣,罗滇生,姚建刚等.电网污区分布图的计算机自动绘制方法研究[J].高电压技术,2007,33(5)：143-147.
[24]黎夏,刘小平,李少英.智能式GIS与空间优化[M].科学出版社,2010.
[25]孙新才.输变电设备状态在线监测与诊断技术现状和前景[J].中国电力,2005,38(2):1-7.
[26]樊昌信,曹丽娜.通信原理[M].国防工业出版社,2006.
[27]俞乾,李卫国,罗日成.基于层次分析法的大型变压器状态评价量化方法研究[J].湖南大学学报·自然科学版,2011,38(10)：56-60.
[28]张蓬鹤,张丹丹,饶章权,韩鹏博.基于模糊层次分析法的接地网状态评估研究[J].电测与仪表,2011,48(12)：5-8.
[29]张继胜,王学峰.模糊综合评价在配电网设备状态检修研究中的应用[J].电子世界·电工研究,2012,2:28-30.
[30]国家电网公司企业标准,Q/GDW 174,架空输电线路状态检修导则,2008.
[31]胡毅.“2.22电网大面积污闪”原因分析及防污闪对策探讨[J].国家电力公司武汉高压研究,2001,4(182)：3-6.
[32]ALMAD A S, AHMAD H, et al. Regression Technology for Prediction of Salt Contamination Severity on High Voltage Insulators[C]. Annual Report Conference on Electrical Insulation and Dielectric Phenomenon,2000,1(10):218-221.
[33]张寒,文习山,丁辉.用神经网络预测基于气象因素的绝缘子等值附盐密度[J].高压电器,2003,39(6)：31-35.
[34]张建兴.悬式瓷质绝缘子表面污秽程度预测方法的研究.吉林：东北电力大学,2005.
[35]石岩,蒋兴良,黄欢.污秽瓷绝缘子泄漏电流的估算方法[J].高电压技术,2009,35(6):1350-1355.
[36]吴军,帅海燕.一种基于多方法组合的新型等值附盐密度预测模型[J].陕西电力,2011,8：13-17.
[37]周富臣,王生辉,易英等.常用数理统计方法及应用实例[M].北京：中国计量出版社,2006.
[38]毛颖科,关志成,王黎明,乐波.基于BP人工神经网络的绝缘子泄漏电流预测[J].中国电机工程学报,2007,27(27)：7-12.
[39]陈哲.一种基于BP算法学习的小波神经网络[J].控制工程,2006,13(1):122-128.
[40]史峰,王小川,李洋等MATLAB神经网络30个案例分析[M].北京航天航空大学出版社,2010.
[41]李波,刘念等.高压电网绝缘子在线绝缘性能的多级模糊综合评判[J].电网技术,2007,31(15)：75-79.
[42]Chris Richards, Carl Benner, Karell Buffer-Furry, eml. Electrical behavior of contaminated distribution insulators exposed to natural wetting[J]. IEEE Transactions On Power Defivery,2003, 18(2):551-558.
[43]G Montoya, Lamirez Montoya. Correlation among ESDD, NSDD and Leakage Current in Distribution Insulators[J]. IEE Proceedings Generation Transmission Distribution,2004,151(3): 334-340.
[44]Yong Zhu, Masahisa Otsubo, Chikahisa Honda. Mechanism for Change in Leakage Current Waveform on a Wet Silicone Rubber Surface—A Study using a Dynamic 3-D Model[J]. IEEE Transactions On Dielectrics and Electrical Insulation,2005,12(3):556-565.
[45]Y Suzuki, R Fukuta, Z Mizuno. Probabilistic Assessment of Flashover Performance of Transmission Lines in Contaminated Areas[J]. IEEE Transactions on Dielectrics and electrical Insulation,1999,6(31):337-341.
[46]Prof. Dr. Ali Hamzeh, Dr. K. Zaidan. Development of an Expert System for Off-and On-Line Faults Diagnosis in Electric Power Systems [J]. IEEE Transactions on Dielectrics and electrical Insulation,2004,14(21:135-138.
[47]YANG Qi-ping, XU Dan-feng, Li Meng-qun. Development of an Power Transmission Line Online Monitoring System[J]. Power and Energy Engineering Conference (APPEEC),2011,25-28.
[2]陈安伟.输变电设备状态检修的应用[J].电网技术,2009,33(27):215-218.
[3]王计朝.输电线路状态检修技术的研究[D].北京：华北电力大学,2009.
[4]安玲.架空输电线路状态检修技术[D].上海：上海交通大学,2002.
[5]宋华松.平面镜法测量杆塔倾斜率[J].安徽建筑,2008,6:196-197.
[6]国家电网公司企业标准,Q/GDW 173,架空输电线路状态评价导则,2008.
[7]陆佳政,蒋正龙,雷红才等.湖南电网2008年冰灾事故分析[J].电力系统自动化,2008,32(11)：16-19.
[8]中华人民共和国电力行业标准,DL/T 741-2001,架空送电线路运行规程,2001.
[9]中华人民共和国国家标准,GB/T2314-2008,电力金具通用技术条件,2008.
[10]黄新波等.输电线路在线监测与故障诊断[M].中国电力出版社,2008.
[11]中华人民共和国电力工业部,DL/T 596-1996,电力设备预防性试验规程,1996.
[12]蔡自兴,徐光佑.人工智能及其应用[M].清华大学出版社,2010.
[13]李国勇.智能预测控制及其MATLAB实现[M].电子工业出版社,2009.
[14]敖志刚.人工智能及专家系统[M].机械工业出版社,2010.
[15]尉敏.基于模糊神经网络的绝缘子状态检测新方法的研究[D].南京：东南大学,2006.
[16]史兴华等.电网GIS及其应用[M].中国电力出版社,2010.
[17]陈雄波,孟遂民,秦红玲.基于GIS的输电线路运行管理系统数据库设计[J].电力建设,2005,26(8)：65-68.
[18]黄新波,孙钦东,张冠军等.在线监测和GIS用于输电线路管理系统[J].高电压技术,2007,33(6)：118-122.
[19]孟遂民,李光辉.架空输电线路设计[M].中国三峡出版社,2000.
[20]王密,龚健雅,李德仁.大型遥感影像数据库的空间无缝数据组织[J].武汉大学学报·信息科学版,2001,26(5)：419-424
[21]王伟.河南省电网污秽区域分布自动生成系统的研究[D].北京：华北电力大学,2009.
[22]中华人民共和国国家标准,GB/T 16434,高压架空线路和发电厂、变电所环境污区分级及外绝缘选择标准,1996.
[23]刘诣,罗滇生,姚建刚等.电网污区分布图的计算机自动绘制方法研究[J].高电压技术,2007,33(5)：143-147.
[24]黎夏,刘小平,李少英.智能式GIS与空间优化[M].科学出版社,2010.
[25]孙新才.输变电设备状态在线监测与诊断技术现状和前景[J].中国电力,2005,38(2):1-7.
[26]樊昌信,曹丽娜.通信原理[M].国防工业出版社,2006.
[27]俞乾,李卫国,罗日成.基于层次分析法的大型变压器状态评价量化方法研究[J].湖南大学学报·自然科学版,2011,38(10)：56-60.
[28]张蓬鹤,张丹丹,饶章权,韩鹏博.基于模糊层次分析法的接地网状态评估研究[J].电测与仪表,2011,48(12)：5-8.
[29]张继胜,王学峰.模糊综合评价在配电网设备状态检修研究中的应用[J].电子世界·电工研究,2012,2:28-30.
[30]国家电网公司企业标准,Q/GDW 174,架空输电线路状态检修导则,2008.
[31]胡毅.“2.22电网大面积污闪”原因分析及防污闪对策探讨[J].国家电力公司武汉高压研究,2001,4(182)：3-6.
[32]ALMAD A S, AHMAD H, et al. Regression Technology for Prediction of Salt Contamination Severity on High Voltage Insulators[C]. Annual Report Conference on Electrical Insulation and Dielectric Phenomenon,2000,1(10):218-221.
[33]张寒,文习山,丁辉.用神经网络预测基于气象因素的绝缘子等值附盐密度[J].高压电器,2003,39(6)：31-35.
[34]张建兴.悬式瓷质绝缘子表面污秽程度预测方法的研究.吉林：东北电力大学,2005.
[35]石岩,蒋兴良,黄欢.污秽瓷绝缘子泄漏电流的估算方法[J].高电压技术,2009,35(6):1350-1355.
[36]吴军,帅海燕.一种基于多方法组合的新型等值附盐密度预测模型[J].陕西电力,2011,8：13-17.
[37]周富臣,王生辉,易英等.常用数理统计方法及应用实例[M].北京：中国计量出版社,2006.
[38]毛颖科,关志成,王黎明,乐波.基于BP人工神经网络的绝缘子泄漏电流预测[J].中国电机工程学报,2007,27(27)：7-12.
[39]陈哲.一种基于BP算法学习的小波神经网络[J].控制工程,2006,13(1):122-128.
[40]史峰,王小川,李洋等MATLAB神经网络30个案例分析[M].北京航天航空大学出版社,2010.
[41]李波,刘念等.高压电网绝缘子在线绝缘性能的多级模糊综合评判[J].电网技术,2007,31(15)：75-79.
[42]Chris Richards, Carl Benner, Karell Buffer-Furry, eml. Electrical behavior of contaminated distribution insulators exposed to natural wetting[J]. IEEE Transactions On Power Defivery,2003, 18(2):551-558.
[43]G Montoya, Lamirez Montoya. Correlation among ESDD, NSDD and Leakage Current in Distribution Insulators[J]. IEE Proceedings Generation Transmission Distribution,2004,151(3): 334-340.
[44]Yong Zhu, Masahisa Otsubo, Chikahisa Honda. Mechanism for Change in Leakage Current Waveform on a Wet Silicone Rubber Surface—A Study using a Dynamic 3-D Model[J]. IEEE Transactions On Dielectrics and Electrical Insulation,2005,12(3):556-565.
[45]Y Suzuki, R Fukuta, Z Mizuno. Probabilistic Assessment of Flashover Performance of Transmission Lines in Contaminated Areas[J]. IEEE Transactions on Dielectrics and electrical Insulation,1999,6(31):337-341.
[46]Prof. Dr. Ali Hamzeh, Dr. K. Zaidan. Development of an Expert System for Off-and On-Line Faults Diagnosis in Electric Power Systems [J]. IEEE Transactions on Dielectrics and electrical Insulation,2004,14(21:135-138.
[47]YANG Qi-ping, XU Dan-feng, Li Meng-qun. Development of an Power Transmission Line Online Monitoring System[J]. Power and Energy Engineering Conference (APPEEC),2011,25-28.