葛洲坝电站变压器绝缘多特征量在线监测应用研究
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摘要
电力变压器绝缘在线监测是目前高电压绝缘检测与诊断领域研究的热点课题。变压器在绝缘故障之前大多具有一定的发展期和各种前期征兆,表现为设备的电气、物理、化学等特性有少量渐进的变化,如局部放电、油中溶解气体超标、铁芯接地电流异常等。本文以局部放电、油中溶解气体和铁芯电流作为多特征量对变压器进行在线监测和分析,对于及早发现故障,防止故障进一步扩大有着重大的作用,极大地提高变压器绝缘诊断的及时性和准确性。
本文围绕基于多特征量变压器绝缘在线监测系统的应用,分析了变压器局部放电、油中溶解气体、铁芯接地电流在线监测原理和方法,论述了高频电流传感器的原理并对其进行了特性测试。对于变压器局部放电在线监测中的周期性干扰,采用了相关函数频域分析法,并设计了IIR格形陷波滤波器进行抑制,对燃料电池气体传感器以及油气分离膜的优良性能进行了分析。
最后本文分析了葛洲坝电站251B变压器绝缘在线监测系统的实际运行情况,现场监测诊断实例表明:整个系统运行稳定,安全可靠,测试数据具有一定的准确性,能够完成局部放电、油色谱、铁芯接地电流的采集、分析、查询等功能,能够满足现场实际工程的需要。
Power transformer on-line monitoring is presently the research hotspot in the area of high-voltage insulation measurement and diagnosis. Before the transformer insulation fault, it most has a certain period of fault development and various signs of pre-performance of equipments' electrical, physical, chemical and other characteristics which have small gradual changes, such as partial discharge, oil-dissolved gas overproof, core earthing current abnormal . The paper based on partial discharge, oil-dissolved gas and core earthing current multi-characteristics vectors the transformer on-line monitoring and analysis for early detection of failure to prevent the further expansion of fault has a major role in, greatly improved the diagnosis of transformer insulating the timeliness and accuracy.
Bases on multi-characteristics vectors on-line monitoring system application in transformer insulation, the paper analysed on-line monitoring principle and method of transformer partial discharge, oil-dissolved gas and the core earthing current; discussed the principle of high frequency current sensor and tested the characteristics. The paper adoped the related functions of the frequency domain to identify periodic interference in transformer partial discharge on-line monitoring system, and designed of the IIR grid-shaped notch filter to inhibit it. A fuel gas sensor and the oil-gas separation membranes excellent performance is analyzed.
Finally, the paper analysed Gezhouba Power Station 251 B transformer insulation on-line monitoring system practical operation, on-site monitoring and diagnosis results show that: the whole system runs stable, safe and reliable, the testing data have a certain accuracy, which can complete the partial discharge, gas chromatography, core earthing current collection, analysis, query and other functions, it is satisfied with the demand of engineer application.
本文围绕基于多特征量变压器绝缘在线监测系统的应用,分析了变压器局部放电、油中溶解气体、铁芯接地电流在线监测原理和方法,论述了高频电流传感器的原理并对其进行了特性测试。对于变压器局部放电在线监测中的周期性干扰,采用了相关函数频域分析法,并设计了IIR格形陷波滤波器进行抑制,对燃料电池气体传感器以及油气分离膜的优良性能进行了分析。
最后本文分析了葛洲坝电站251B变压器绝缘在线监测系统的实际运行情况,现场监测诊断实例表明:整个系统运行稳定,安全可靠,测试数据具有一定的准确性,能够完成局部放电、油色谱、铁芯接地电流的采集、分析、查询等功能,能够满足现场实际工程的需要。
Power transformer on-line monitoring is presently the research hotspot in the area of high-voltage insulation measurement and diagnosis. Before the transformer insulation fault, it most has a certain period of fault development and various signs of pre-performance of equipments' electrical, physical, chemical and other characteristics which have small gradual changes, such as partial discharge, oil-dissolved gas overproof, core earthing current abnormal . The paper based on partial discharge, oil-dissolved gas and core earthing current multi-characteristics vectors the transformer on-line monitoring and analysis for early detection of failure to prevent the further expansion of fault has a major role in, greatly improved the diagnosis of transformer insulating the timeliness and accuracy.
Bases on multi-characteristics vectors on-line monitoring system application in transformer insulation, the paper analysed on-line monitoring principle and method of transformer partial discharge, oil-dissolved gas and the core earthing current; discussed the principle of high frequency current sensor and tested the characteristics. The paper adoped the related functions of the frequency domain to identify periodic interference in transformer partial discharge on-line monitoring system, and designed of the IIR grid-shaped notch filter to inhibit it. A fuel gas sensor and the oil-gas separation membranes excellent performance is analyzed.
Finally, the paper analysed Gezhouba Power Station 251 B transformer insulation on-line monitoring system practical operation, on-site monitoring and diagnosis results show that: the whole system runs stable, safe and reliable, the testing data have a certain accuracy, which can complete the partial discharge, gas chromatography, core earthing current collection, analysis, query and other functions, it is satisfied with the demand of engineer application.
引文
[1]王昌长,李福琪,高胜友.电力设备的在线监测与故障诊断.北京:清华大学出版社,2006.
[2]黄盛洁等.电气设备绝缘在线监测和状态维修.北京:中国水利电力出版社,2004.
[3]金显贺.大型电力变压器局部放电声发射在线监测的研究.清华大学硕士论文,1988.
[4]王国利,袁鹏等.变压器超高频局部放电自动识别系统.电工电能新术,Vol.22,No.1,Jan,2003.
[5]Caixin Sun,Ruijin Liao.On-line detection of Gases Dissolved in Transformer Oil and the Faults Diagnosis.30~(th) sysposium on Electrical Insulation Materials,1998:1109-1112.
[6]孙才新,罗兵,顾乐观等.自适应数字滤波在局部放电在线监测信号处理中应用研究,变压器.Vol.34,No.7,July,1997:19-23.
[7]陈伟根,大容量高电压变压器油中气体色谱在线监测原理及方法的研究.重庆大学硕士论文,1993.
[8]P.candela,G.Mirelli,R.Schifani.PD recognition by means of statistical and fractal parameters and aneural network.IEEE Trans.on Dielectrics and Electrial Insulation.2000,7(1):87-94.
[9]C.Boisseau Instrument transformers on line Momitoring by Means of Partial Discharge Measurement.7~(th) ISH,August 1991.
[10]司文荣;李军浩;袁鹏;李彦明.局部放电超高频窄带信号监测技术.电工技术学报.Vol.23,No.7,Jan,2008:7-12.
[11]V.Nagesh and B.I.Gururaj "Evaluation of Digital Filters for Rejepting Discrete Spectral Interference in On-site PD Measurements",IEEE Transactions on Electrical Insulation,Vol.28No.1,Februry 1993:73-85.
[12]Yasuo,Kimio,Masaru et al.Development of oil-dissalved Hydrogen gas detector for diagnosis of transformers.IEEE Transcations on Power Delivery,Vol.5,No.1,1990.
[13]孙才新,陈伟根,李俭.电气设备中气体在线监测及故障诊断技术,科学技术出版社,2003.
[14]李娟.电力变压器状态检测与故障诊断的研究南京.河海大学硕士论文 2003.
[15]肖燕彩,朱衡君,张霄元,陈秀海基于溶解气体分析的电力变压器在线监测与诊断技术[J]电力自动化设备,2006(6):93-96.
[16]苏羽,赵海,苏威积,张晓丹基于模糊专家系统的评估诊断方法[J]东北大学学报(自然科学版),2004,(7):653-656.
[17]P.Purkait et al.Investigations on the useulness of an expert system for impulse fault analysis in distribution transformers[J].Electric Power Systems Research 65(2003):149-157.
[18]E.A.Mohamed et al.A neural network-based scheme for fault disgnosis of power transformers[J].Electric Power Systems Research 75(2005):29-39.
[19]Hsing-Chia Kuo et al Symbiotic evolution-based design of fuzzy-nenral transformer diagnostic system[J].Electric Power Systems Research 72(2004):235-244.
[20]邓宏贵,罗安,曹建灰关联度在变压器故障诊断中的应用[J]电力系统自动化,2005(18):73-75,89.
[21]M.H.Wang et al.Novel grey model for the prediction of trend of dissolved gases in oil-filled power apparatus[J].Electric Power Systems Research 67(2003):53-58.
[22]项新建 粗糙集理论在变压器故障诊断专家系统中的应用研究[J]科技通报 2003(4):288-291.
[23]王蓓蓓,郭基伟,谢敬东,唐国庆 基于模糊网的知识表示方法在变压器故降诊断专家系统中的应用[J]电力系统及其自动化学报,2003,15(1):74-77.
[24]尚勇,闰春江,严璋,曹俊岭基于信息融合的大型油浸电力变压器故障诊断,中国电机工程学报,2002,22(7):115-118.
[25]王丰华,朱子述.新技术在电力变压器状态监测中的应用[J]高电压技术,2003(11):31-34.
[26]孙波涛,郭忠田,马超.变压器铁芯多点接地故障分析判断及处理.冶金动力.2001,(4):21-22.
[27]王胜辉.变压器局部放电在线监测高速数据采集系统的研究.硕士学位论文.保定:华北电力大学电力工程系,2003.
[28]张柯,律方成,王永强.基于MAX125/126的电气设备在线检测数据采集单元设计.电气自动化设备.2003,23(4):49-50.
[29]龚细秀 变压器局部放电高频和特高频联合监测法的研究[D]北京清华大学硕士论文,2005.
[30]罗日成,李卫国,李成榕,熊浩,畅广辉 基于改进PSO算法的变压器局部放电超声定位方法[J]电力系统自动化,2005(18):66-69.
[31]徐岩 电力变压器内部故障数字仿真及其保护新原理的研究[D]保定:华北电力大学博士论文,2005.
[32]王世山,汲胜昌,李彦明 利用振动法进行变压器在线监测的应用研究[J].变压器,2002(S1):73-76.
[33]张洪涛,王福忠,王晓丹 基于综合参数的电力变压器故障在线诊断装置的硬件设计[J]河南理工大学学报,2005(6):462-465.
[34]赵大光,王泽文,董连文 用系统辨识方法确定变压器的故障诊断模型[J]高压电器1999(1):30-33.
[35]罗锡梁,杨世锡,蔡清华,焦卫东 基于姗以的电力变压器故障诊断系统软件设计与实现[J] 工业控制计算机,2006(4):36-38.
[36]陈婷,李朝晖 基于的变压器在线监测系统水电自动化与大坝监测,2006(4):30-35.
[37]B.Georges,J.Aubin.Application of PLC for on-line monitoring of power transformers.Power Engineering SocietyWinterMeeting,2001.IEEE,Vol.2,2001:483-486.
[38]Yasuo Inoue,Kimio Suganuma,Masaru,et al.Development of oil-dissolved Hydrogen gas detector for diagnosis of transformers.IEEE Transformer on Power Delivery,Vol.5,No.1,Jan,1990:226-232.
[39]T.Leibfried.On-line monitoring of power transformers-system technology and data evaluation,High Voltage Engineering,1999.Eleventh International Symposium on(Conf.Publ.No.467),Vol.5,1999:184-187.
[40]王晓英等.变压器故障与监测.北京:机械工业出版社,2004.
[2]黄盛洁等.电气设备绝缘在线监测和状态维修.北京:中国水利电力出版社,2004.
[3]金显贺.大型电力变压器局部放电声发射在线监测的研究.清华大学硕士论文,1988.
[4]王国利,袁鹏等.变压器超高频局部放电自动识别系统.电工电能新术,Vol.22,No.1,Jan,2003.
[5]Caixin Sun,Ruijin Liao.On-line detection of Gases Dissolved in Transformer Oil and the Faults Diagnosis.30~(th) sysposium on Electrical Insulation Materials,1998:1109-1112.
[6]孙才新,罗兵,顾乐观等.自适应数字滤波在局部放电在线监测信号处理中应用研究,变压器.Vol.34,No.7,July,1997:19-23.
[7]陈伟根,大容量高电压变压器油中气体色谱在线监测原理及方法的研究.重庆大学硕士论文,1993.
[8]P.candela,G.Mirelli,R.Schifani.PD recognition by means of statistical and fractal parameters and aneural network.IEEE Trans.on Dielectrics and Electrial Insulation.2000,7(1):87-94.
[9]C.Boisseau Instrument transformers on line Momitoring by Means of Partial Discharge Measurement.7~(th) ISH,August 1991.
[10]司文荣;李军浩;袁鹏;李彦明.局部放电超高频窄带信号监测技术.电工技术学报.Vol.23,No.7,Jan,2008:7-12.
[11]V.Nagesh and B.I.Gururaj "Evaluation of Digital Filters for Rejepting Discrete Spectral Interference in On-site PD Measurements",IEEE Transactions on Electrical Insulation,Vol.28No.1,Februry 1993:73-85.
[12]Yasuo,Kimio,Masaru et al.Development of oil-dissalved Hydrogen gas detector for diagnosis of transformers.IEEE Transcations on Power Delivery,Vol.5,No.1,1990.
[13]孙才新,陈伟根,李俭.电气设备中气体在线监测及故障诊断技术,科学技术出版社,2003.
[14]李娟.电力变压器状态检测与故障诊断的研究南京.河海大学硕士论文 2003.
[15]肖燕彩,朱衡君,张霄元,陈秀海基于溶解气体分析的电力变压器在线监测与诊断技术[J]电力自动化设备,2006(6):93-96.
[16]苏羽,赵海,苏威积,张晓丹基于模糊专家系统的评估诊断方法[J]东北大学学报(自然科学版),2004,(7):653-656.
[17]P.Purkait et al.Investigations on the useulness of an expert system for impulse fault analysis in distribution transformers[J].Electric Power Systems Research 65(2003):149-157.
[18]E.A.Mohamed et al.A neural network-based scheme for fault disgnosis of power transformers[J].Electric Power Systems Research 75(2005):29-39.
[19]Hsing-Chia Kuo et al Symbiotic evolution-based design of fuzzy-nenral transformer diagnostic system[J].Electric Power Systems Research 72(2004):235-244.
[20]邓宏贵,罗安,曹建灰关联度在变压器故障诊断中的应用[J]电力系统自动化,2005(18):73-75,89.
[21]M.H.Wang et al.Novel grey model for the prediction of trend of dissolved gases in oil-filled power apparatus[J].Electric Power Systems Research 67(2003):53-58.
[22]项新建 粗糙集理论在变压器故障诊断专家系统中的应用研究[J]科技通报 2003(4):288-291.
[23]王蓓蓓,郭基伟,谢敬东,唐国庆 基于模糊网的知识表示方法在变压器故降诊断专家系统中的应用[J]电力系统及其自动化学报,2003,15(1):74-77.
[24]尚勇,闰春江,严璋,曹俊岭基于信息融合的大型油浸电力变压器故障诊断,中国电机工程学报,2002,22(7):115-118.
[25]王丰华,朱子述.新技术在电力变压器状态监测中的应用[J]高电压技术,2003(11):31-34.
[26]孙波涛,郭忠田,马超.变压器铁芯多点接地故障分析判断及处理.冶金动力.2001,(4):21-22.
[27]王胜辉.变压器局部放电在线监测高速数据采集系统的研究.硕士学位论文.保定:华北电力大学电力工程系,2003.
[28]张柯,律方成,王永强.基于MAX125/126的电气设备在线检测数据采集单元设计.电气自动化设备.2003,23(4):49-50.
[29]龚细秀 变压器局部放电高频和特高频联合监测法的研究[D]北京清华大学硕士论文,2005.
[30]罗日成,李卫国,李成榕,熊浩,畅广辉 基于改进PSO算法的变压器局部放电超声定位方法[J]电力系统自动化,2005(18):66-69.
[31]徐岩 电力变压器内部故障数字仿真及其保护新原理的研究[D]保定:华北电力大学博士论文,2005.
[32]王世山,汲胜昌,李彦明 利用振动法进行变压器在线监测的应用研究[J].变压器,2002(S1):73-76.
[33]张洪涛,王福忠,王晓丹 基于综合参数的电力变压器故障在线诊断装置的硬件设计[J]河南理工大学学报,2005(6):462-465.
[34]赵大光,王泽文,董连文 用系统辨识方法确定变压器的故障诊断模型[J]高压电器1999(1):30-33.
[35]罗锡梁,杨世锡,蔡清华,焦卫东 基于姗以的电力变压器故障诊断系统软件设计与实现[J] 工业控制计算机,2006(4):36-38.
[36]陈婷,李朝晖 基于的变压器在线监测系统水电自动化与大坝监测,2006(4):30-35.
[37]B.Georges,J.Aubin.Application of PLC for on-line monitoring of power transformers.Power Engineering SocietyWinterMeeting,2001.IEEE,Vol.2,2001:483-486.
[38]Yasuo Inoue,Kimio Suganuma,Masaru,et al.Development of oil-dissolved Hydrogen gas detector for diagnosis of transformers.IEEE Transformer on Power Delivery,Vol.5,No.1,Jan,1990:226-232.
[39]T.Leibfried.On-line monitoring of power transformers-system technology and data evaluation,High Voltage Engineering,1999.Eleventh International Symposium on(Conf.Publ.No.467),Vol.5,1999:184-187.
[40]王晓英等.变压器故障与监测.北京:机械工业出版社,2004.