基于灰色理论的变压器状态维修决策研究
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摘要
电力变压器是电力系统中的重要设备之一，其运行的可靠性对电力系统安全稳定运行有着重要的影响。因此，对电力变压器的健康状态评价以及评价后的维修决策研究就显得尤为重要。长期以来，我国基本采用计划性定期维修，其不足主要在：不根据电力变压器的实际运行状况来确定维修，而是根据维修规程中的维修周期，以到期必修的维修原则进行，缺少明确的维修目标；同时，人力和财力资源无法有效配置，增加维修费用，造成资源浪费。而状态维修则从设备的实际运行状态出发，通过运行经验、在线监测和电气试验等来确定设备健康状态，针对性强，目标明确，该修则修；从维修费用来讲，状态维修具有一定的经济性。因此，在工业生产中，状态维修已得到较为广泛的认可，将会代替计划性定期维修而成为一种趋势。
根据状态维修的性质，必须根据在线数据以及运行经验等来进行健康状态评价，然后依据评价结论，制定相应的维修决策方案，这就是状态维修的基本过程。本文通过查阅大量国内外文献，结合变压器实际运行状态，对以下几个方面进行了研究：
提出了采用层次分析法的灰色聚类电力变压器状态评价方法。首先采用层次分析法把电力变压器的状态量进行分类，转化为定量指标，构造出层次判断矩阵，求出各指标在变压器中的组合权重；其次对电力变压器的健康状态进行优劣比较，得出五种设备状态并将其定义成五种灰类，建立相应的白化权函数；根据灰色聚类理论，把组合权重与白化权函数结合起来计算就可以得到变压器的状态。
将多目标智能加权灰靶理论引入到电力变压器的维修决策中，首先建立变压器的对策集，并从经济性和安全性等方面中选取决策目标，构造出局势集，然后对目标效果值进行中靶分析；同时给出其决策计算步骤，并应用实例加以分析。
根据决策局势效果向量与最优效果向量的关联度，在电力变压器中应用灰色关联决策来对其进行状态维修决策。建立变压器的对策集，并从经济性和安全性等方面中选取决策目标，构造出局势集，进行关联度分析，同时，采用定权和加权两种方法对决策目标进行对比研究；通过对比发现，加权决策更符合实际运行，使定性分析与定量分析互补，减少决策误差，优化维修决策结论。
The power transformer is one of the important equipment in the power system, theoperation reliability of the transformer take an important act on the security andstability of power system. Therefore, it is particularly important to access the healthstatus of power transformers and make maintenance decision. For a long time, theplanned regular maintenance has been become maintenance methods, its shortcomingsare not based on actual operating conditions of power transformers to determine themaintenance, but according to the maintenance cycle of the maintenance of order,making the compulsory maintenance principles, but it lack the clear maintenanceobjectives; and make no effective allocation of human and financial resources,increasing maintenance costs, resulting the waste of resources. But the statemaintenance of the equipment from the starting line monitoring and on-line test todetermine health status of the equipment, and the maintenance objectives are clear,maintenance is only in need of repair; in terms of maintenance costs, it is moreeconomic. The state maintenance has been more widely recognized in industrialproduction, therefore, it will become a trend instead of planned regular maintenance.
According to the nature of the status maintenance, the health assessment must bebased on online data and operating experience, and then in accordance with theconclusions of the assessment , making a maintenance decision , which is the basicprocess of the state of maintenance . Access to a large number of domestic and foreignliteratures , the following aspects have been studied in the paper. The paper introducesthe analytic hierarchy process and gray clustering methods to assess the powertransformer healthy state. Firstly, using the analytic hierarchy to classify the state ofthe power transformer, transforming the qualitative indicators into quantitativeindicators, and constructing a hierarchical judgment matrix to calculate the combinedweights of the various indicators in the transformer weight. Secondly, comparing theadvantages and disadvantages of the health status of the power transformer, fivedevice status are established, defining as five grey classes, then establishing thewhitenization weight function of the grey classes. According to the gray clustermethod, combining the combined weights with the whitenization weight, to calculatethe status of the transformer.
The multi-attribute intelligent grey target decision model apply to the maintenance decision of the power transformer, establishing a set of countermeasures of thetransformer, and selecting the decision-making target from the economic and securityaspects., The case of hit the bull’s eye of the objective effect value is fully considered;its decision-making calculation steps are given, and apply examples to analyze themethod.
In accordance with the relational degree of the decision-making situation effectvector and the optimal effect vector, apply the grey relation decision-making to themaintenance decision-making of the power transformer, establishing a set ofcountermeasures of the transformer, and selecting the decision-making target from theeconomic and security aspects, and apply fixed weight and variable weight to studycomparatively to the decision objective, By comparison, the variable weighteddecision-making is more realistic , to make qualitative analysis and quantitativeanalysis be complementary , and reduce the decision-making errors.
根据状态维修的性质，必须根据在线数据以及运行经验等来进行健康状态评价，然后依据评价结论，制定相应的维修决策方案，这就是状态维修的基本过程。本文通过查阅大量国内外文献，结合变压器实际运行状态，对以下几个方面进行了研究：
提出了采用层次分析法的灰色聚类电力变压器状态评价方法。首先采用层次分析法把电力变压器的状态量进行分类，转化为定量指标，构造出层次判断矩阵，求出各指标在变压器中的组合权重；其次对电力变压器的健康状态进行优劣比较，得出五种设备状态并将其定义成五种灰类，建立相应的白化权函数；根据灰色聚类理论，把组合权重与白化权函数结合起来计算就可以得到变压器的状态。
将多目标智能加权灰靶理论引入到电力变压器的维修决策中，首先建立变压器的对策集，并从经济性和安全性等方面中选取决策目标，构造出局势集，然后对目标效果值进行中靶分析；同时给出其决策计算步骤，并应用实例加以分析。
根据决策局势效果向量与最优效果向量的关联度，在电力变压器中应用灰色关联决策来对其进行状态维修决策。建立变压器的对策集，并从经济性和安全性等方面中选取决策目标，构造出局势集，进行关联度分析，同时，采用定权和加权两种方法对决策目标进行对比研究；通过对比发现，加权决策更符合实际运行，使定性分析与定量分析互补，减少决策误差，优化维修决策结论。
The power transformer is one of the important equipment in the power system, theoperation reliability of the transformer take an important act on the security andstability of power system. Therefore, it is particularly important to access the healthstatus of power transformers and make maintenance decision. For a long time, theplanned regular maintenance has been become maintenance methods, its shortcomingsare not based on actual operating conditions of power transformers to determine themaintenance, but according to the maintenance cycle of the maintenance of order,making the compulsory maintenance principles, but it lack the clear maintenanceobjectives; and make no effective allocation of human and financial resources,increasing maintenance costs, resulting the waste of resources. But the statemaintenance of the equipment from the starting line monitoring and on-line test todetermine health status of the equipment, and the maintenance objectives are clear,maintenance is only in need of repair; in terms of maintenance costs, it is moreeconomic. The state maintenance has been more widely recognized in industrialproduction, therefore, it will become a trend instead of planned regular maintenance.
According to the nature of the status maintenance, the health assessment must bebased on online data and operating experience, and then in accordance with theconclusions of the assessment , making a maintenance decision , which is the basicprocess of the state of maintenance . Access to a large number of domestic and foreignliteratures , the following aspects have been studied in the paper. The paper introducesthe analytic hierarchy process and gray clustering methods to assess the powertransformer healthy state. Firstly, using the analytic hierarchy to classify the state ofthe power transformer, transforming the qualitative indicators into quantitativeindicators, and constructing a hierarchical judgment matrix to calculate the combinedweights of the various indicators in the transformer weight. Secondly, comparing theadvantages and disadvantages of the health status of the power transformer, fivedevice status are established, defining as five grey classes, then establishing thewhitenization weight function of the grey classes. According to the gray clustermethod, combining the combined weights with the whitenization weight, to calculatethe status of the transformer.
The multi-attribute intelligent grey target decision model apply to the maintenance decision of the power transformer, establishing a set of countermeasures of thetransformer, and selecting the decision-making target from the economic and securityaspects., The case of hit the bull’s eye of the objective effect value is fully considered;its decision-making calculation steps are given, and apply examples to analyze themethod.
In accordance with the relational degree of the decision-making situation effectvector and the optimal effect vector, apply the grey relation decision-making to themaintenance decision-making of the power transformer, establishing a set ofcountermeasures of the transformer, and selecting the decision-making target from theeconomic and security aspects, and apply fixed weight and variable weight to studycomparatively to the decision objective, By comparison, the variable weighteddecision-making is more realistic , to make qualitative analysis and quantitativeanalysis be complementary , and reduce the decision-making errors.
引文
[1] J.C.Steed.Condition monitoring applied to power transformer an RECexperience.Second International Conference on the Reliablity of Transimissionand Distribution Equipment,1995,(1): 109-114.
[2]廖瑞金，廖玉祥，杨丽君等.多神经网络与证据理论融合的变压器故障综合诊断方法研究.中国电机工程学报, 2006,26(3):119-124.
[3] A.S.Farag, M.Mohandes, Ali Al-Shaikh. Diagnosing failed distributiontransformers using neural networks.IEEE Tran- sactions on Power Delivery,2001,16(4):631-636.
[4] C.Pan, W.G.Chen, Y.X.Yun.Fault diagnostic method of power transformers basedon hybrid genetic algorithm evolving wavelet neural net.Electric PowerApplications, IET.2008,2(1):71-76.
[5]骆思佳，廖瑞金，王有元等.带变权的电力变压器状态模糊综合评判.高电压技术.2007,33(08):106-110.
[6]许婧,王晶,高峰等.电力设备状态检修技术研究综述.电网技术,2000,24(8):48-52.
[7]严璋.电力设备绝缘的状态维修.电力设备状态检修和在线监测论文集.江苏省电力公司，江苏省电机工程学会.2001.
[8]李昌.宁夏大坝发电厂主变压器绝缘多参量故障诊断[重庆大学硕士学位论文].重庆大学，2009.
[9]袁志坚.电力变压器状态维修决策方法的研究[重庆大学博士学位论文].重庆大学，2004.
[10]刘有为，李光范等.制定《电气设备状态维修导则》的原则框架.电网技术,2003,27(6):64-67.
[11]国家电网公司.DL/T 573-2010电力变压器检修导则.北京:中国电力出版社,2010.
[12]刘娜,梁国栋,王刘芳等.电力变压器故障模式的分析及危害评估.高电压技术，2003,29(2):3-5,8.
[13]杨良军，熊小伏,张媛.基于灰色关联度和理想解法的电力设备状态维修策略.电力系统保护与控制.2009,37(18):74-78.
[14]袁志坚，孙才新，李爱华等.模糊多属性决策方法评价变压器状态维修策略.高电压技术.2004,30(8):33-35.
[15]顾煜炯,陈昆亮,杨昆.基于熵权和层次分析的电站设备维修方式决策.华北电力大学学报.2008,35(6):72-76,82.
[16]潘乐真,鲁国起,张焰等.基于风险综合评判的设备状态检修决策优化.电力系统自动化.2010,34(11):28-32.
[17]李明,韩学山,杨明等.电网状态检修概念与理论基础研究.中国电机工程学报.2011,31(34):43-52.
[18]王进才,曹学峰.基于马尔可夫决策过程的维修决策模型研究.电子产品可靠性与环境试验.2011,29(2):1-6.
[19]高萍，吴甦.基于蒙特卡罗方法的设备维修决策模型.系统仿真学报.2007,19(22),5112-5114.
[20]王有元,徐海霞,陈伟根,周军,袁园.电力变压器状态维修策略的灰局势决策方法.重庆大学学报.2009,32(12):1421-1424.
[21]徐玖平,李军.多目标决策的理论与方法.北京:清华大学出版社,2005.
[22]徐玖平.运筹学.北京：科学出版社，2010.
[23]李荣钧.模糊多准则决策理论与应用.北京：科学出版社,2002.
[24]李登峰.模糊多目标多人决策与对策.北京：国防工业出版社,2003.
[25]谢季坚，刘承平.模糊数学方法及其应用(第二版).武汉：华中科技大学,2002.
[26]刘克.实用马尔可夫决策过程.北京：清华大学出版社,2004.
[27]邓聚龙.灰理论基础.武汉：华中科技大学出版社,2002,2.
[28]刘思峰,党耀国,方志耕等.灰色系统理论及其应用(第5版).北京：科学出版社,2010,5.
[29]张金萍,刘国贤,袁泉,等.变电设备健康状态评估系统的设计与实现.现代电力,2004, 21(4): 45-49.
[30]苏丹．OLAM技术在变压器状态评估系统中的应用．北京：华北电力大学．2006．
[31]许树柏.层次分析法原理.天津:天津大学出版社,1988.
[32]王俊良,白慧芳,宋斌.基于层次分析的变压器故障诊断决策支持系统.武汉大学学报(工学版).2008,41(6):91-94.
[33]王莲芬,许树柏.层次分析法引论.北京:中国人民大学出版社,1990.
[34]中华人民共和国国家质量监督检验检疫总局.GB/T 7252-2001变压器油中溶解气体分析和判断导则.北京:中国电力出版社,2002.
[35]中华人民共和国建设部.GB 50150-2006.电气装置安装工程电气设备交接试验标准.北京：中国计划出版社，2006.
[36]国家电网公司.Q/GDW 169-2008油浸式变压器(电抗器)状态评价导则.北京:中国电力出版社,2008.
[37]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.北京:中国电力出版社,1996.
[38]梁冰，秦冰，孙维吉.基于灰靶决策模型的煤瓦斯突出可能性评价.煤炭学报，2011，36(12)：1974-1978.
[39]钟铭，吕媛媛.基于灰靶模型的港口效率评价.大连海事大学学报，2007,33(增刊)：130-133.
[40]刘思峰，袁文峰，盛克勤.一种新型多目标智能加权灰靶决策模型.控制与决策，2010，25(8)：1159-1163.
[41] Chen Farnshing,Chang Tachun,Liao Hsiuhsiang.The application of the greyrelation analysis on teacher appraisal. IEEE International Conference on Systems,Man, and Cybernetics, 2000,5(8): 3366-3371.
[42] Song Bin,Yu Ping,Luo Yunbai,et al.Study on the fault diagnosis of transformerbased on the grey relational analysis.Power System Technology,2002，Proceedings,International Conference on PowerCom,2002,4(6):2231-2234.
[43]吕干云，程浩忠，翟海保，董立新.基于改进灰色关联分析的变压器故障识别.中国电机工程学报，2004,24(10):121-126.
[2]廖瑞金，廖玉祥，杨丽君等.多神经网络与证据理论融合的变压器故障综合诊断方法研究.中国电机工程学报, 2006,26(3):119-124.
[3] A.S.Farag, M.Mohandes, Ali Al-Shaikh. Diagnosing failed distributiontransformers using neural networks.IEEE Tran- sactions on Power Delivery,2001,16(4):631-636.
[4] C.Pan, W.G.Chen, Y.X.Yun.Fault diagnostic method of power transformers basedon hybrid genetic algorithm evolving wavelet neural net.Electric PowerApplications, IET.2008,2(1):71-76.
[5]骆思佳，廖瑞金，王有元等.带变权的电力变压器状态模糊综合评判.高电压技术.2007,33(08):106-110.
[6]许婧,王晶,高峰等.电力设备状态检修技术研究综述.电网技术,2000,24(8):48-52.
[7]严璋.电力设备绝缘的状态维修.电力设备状态检修和在线监测论文集.江苏省电力公司，江苏省电机工程学会.2001.
[8]李昌.宁夏大坝发电厂主变压器绝缘多参量故障诊断[重庆大学硕士学位论文].重庆大学，2009.
[9]袁志坚.电力变压器状态维修决策方法的研究[重庆大学博士学位论文].重庆大学，2004.
[10]刘有为，李光范等.制定《电气设备状态维修导则》的原则框架.电网技术,2003,27(6):64-67.
[11]国家电网公司.DL/T 573-2010电力变压器检修导则.北京:中国电力出版社,2010.
[12]刘娜,梁国栋,王刘芳等.电力变压器故障模式的分析及危害评估.高电压技术，2003,29(2):3-5,8.
[13]杨良军，熊小伏,张媛.基于灰色关联度和理想解法的电力设备状态维修策略.电力系统保护与控制.2009,37(18):74-78.
[14]袁志坚，孙才新，李爱华等.模糊多属性决策方法评价变压器状态维修策略.高电压技术.2004,30(8):33-35.
[15]顾煜炯,陈昆亮,杨昆.基于熵权和层次分析的电站设备维修方式决策.华北电力大学学报.2008,35(6):72-76,82.
[16]潘乐真,鲁国起,张焰等.基于风险综合评判的设备状态检修决策优化.电力系统自动化.2010,34(11):28-32.
[17]李明,韩学山,杨明等.电网状态检修概念与理论基础研究.中国电机工程学报.2011,31(34):43-52.
[18]王进才,曹学峰.基于马尔可夫决策过程的维修决策模型研究.电子产品可靠性与环境试验.2011,29(2):1-6.
[19]高萍，吴甦.基于蒙特卡罗方法的设备维修决策模型.系统仿真学报.2007,19(22),5112-5114.
[20]王有元,徐海霞,陈伟根,周军,袁园.电力变压器状态维修策略的灰局势决策方法.重庆大学学报.2009,32(12):1421-1424.
[21]徐玖平,李军.多目标决策的理论与方法.北京:清华大学出版社,2005.
[22]徐玖平.运筹学.北京：科学出版社，2010.
[23]李荣钧.模糊多准则决策理论与应用.北京：科学出版社,2002.
[24]李登峰.模糊多目标多人决策与对策.北京：国防工业出版社,2003.
[25]谢季坚，刘承平.模糊数学方法及其应用(第二版).武汉：华中科技大学,2002.
[26]刘克.实用马尔可夫决策过程.北京：清华大学出版社,2004.
[27]邓聚龙.灰理论基础.武汉：华中科技大学出版社,2002,2.
[28]刘思峰,党耀国,方志耕等.灰色系统理论及其应用(第5版).北京：科学出版社,2010,5.
[29]张金萍,刘国贤,袁泉,等.变电设备健康状态评估系统的设计与实现.现代电力,2004, 21(4): 45-49.
[30]苏丹．OLAM技术在变压器状态评估系统中的应用．北京：华北电力大学．2006．
[31]许树柏.层次分析法原理.天津:天津大学出版社,1988.
[32]王俊良,白慧芳,宋斌.基于层次分析的变压器故障诊断决策支持系统.武汉大学学报(工学版).2008,41(6):91-94.
[33]王莲芬,许树柏.层次分析法引论.北京:中国人民大学出版社,1990.
[34]中华人民共和国国家质量监督检验检疫总局.GB/T 7252-2001变压器油中溶解气体分析和判断导则.北京:中国电力出版社,2002.
[35]中华人民共和国建设部.GB 50150-2006.电气装置安装工程电气设备交接试验标准.北京：中国计划出版社，2006.
[36]国家电网公司.Q/GDW 169-2008油浸式变压器(电抗器)状态评价导则.北京:中国电力出版社,2008.
[37]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.北京:中国电力出版社,1996.
[38]梁冰，秦冰，孙维吉.基于灰靶决策模型的煤瓦斯突出可能性评价.煤炭学报，2011，36(12)：1974-1978.
[39]钟铭，吕媛媛.基于灰靶模型的港口效率评价.大连海事大学学报，2007,33(增刊)：130-133.
[40]刘思峰，袁文峰，盛克勤.一种新型多目标智能加权灰靶决策模型.控制与决策，2010，25(8)：1159-1163.
[41] Chen Farnshing,Chang Tachun,Liao Hsiuhsiang.The application of the greyrelation analysis on teacher appraisal. IEEE International Conference on Systems,Man, and Cybernetics, 2000,5(8): 3366-3371.
[42] Song Bin,Yu Ping,Luo Yunbai,et al.Study on the fault diagnosis of transformerbased on the grey relational analysis.Power System Technology,2002，Proceedings,International Conference on PowerCom,2002,4(6):2231-2234.
[43]吕干云，程浩忠，翟海保，董立新.基于改进灰色关联分析的变压器故障识别.中国电机工程学报，2004,24(10):121-126.
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