基于运行状态和寿命评估的电力变压器全寿命周期检修决策研究
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摘要
当前电力企业对变压器检修策略制定的关注点多集中于变压器的可靠性，常出现过度维修的现象，导致了巨大的资源浪费。因此，需要综合考虑变压器运行的可靠性和经济性，对变压器进行运行状态和绝缘寿命评估，分析其全寿命周期成本和运行风险，进而制定恰当的运行维护和状态检修策略，以提高电力企业的精益化管理水平。
本文以油中溶解气体为特征量深入研究了基于殖民竞争法优化支持向量机参数的变压器故障诊断方法和基于云推理的变压器多故障诊断和故障预测方法；以绝缘状态为主体，建立了基于健康指数的变压器运行状态评估模型；对基于时温水叠加的电力变压器绝缘寿命评估模型进行了研究；在构建变压器风险评估模型和全寿命周期成本模型的基础上，根据变压器的运行状态和绝缘寿命，兼顾变压器运行的可靠性和经济性，制定了变压器维护和检修策略。论文取得的创新性成果和主要结论主要有：
①提出了一种基于健康指数的变压器运行状态评估模型。构建了基于云理论和证据推理融合的绝缘状态评估模型，利用证据推理决策准则进行绝缘状态评估。实例分析结果表明，得到的绝缘状态评估结论准确。进一步，以绝缘状态评估结果为主体，综合考虑变压器的运行时间、运行环境等因素，采用健康指数评估变压器的运行状态，实例验证表明，提出的变压器运行状态评估方法是有效可行的。
②首次提出并建立了一种考虑时间、温度、水分联合影响的绝缘寿命评估模型。综合考虑变压器纸中水分含量、负荷情况、平均热点温度、油纸绝缘老化状态，提出了一种考虑时间、温度、水分联合影响的绝缘寿命评估模型，改进了传统绝缘寿命评估模型未考虑纸中水分影响的不足。实例验证结果表明，提出的寿命评估模型是有效的。
③提出了一种基于风险评估与全寿命周期成本分析的变压器检修策略决策模型。针对现有变压器检修策略制定中仅考虑其可靠性运行，较少考虑经济性运行的问题，本文综合考虑变压器的运行可靠性与经济性，以变压器的绝缘寿命为影响因素，提出了一种基于风险评估与全寿命周期成本分析的变压器检修策略决策模型，该模型根据变压器的状态信息获得其故障概率，在保证变压器于寿命周期内可靠性指标大于可靠运行要求的基础上，制定了基于风险评估与全寿命周期成本分析的变压器检修策略决策模型。通过实例验证，该检修策略决策模型准确有效。
An oil filled power transformer is a core component of the power system forenergy transmission and conversion, and its operating status directly affects the securityand stability of the power grid. Once a transformer breaks down, it may cause hugeeconomic losses, and it even causes serious social impact. However, blind repairs willlead to a lot of waste of human and material resources. Therefore, researches oftransformer insulation condition assessment, insulation life prediction, life cycle costanalysis, operational risk of the transformer, and condition based maintenance decisionmaking of the transformer considering the reliability and economy of transformeroperation, which can choose an appropriate condition-based maintenance strategy toreduce accident probability and promote the economical efficiency of electricalcompanies.
Based on regulations, this thesis studies transformer fault diagnosis using ICAoptimized SVM model, fault forecasting using cloud model, insulation assessmentmodel using cloud model and evidential reasoning, insulation life assessment modelusing time, temperature, and water information, transformer risk assessment model, andlife cycle cost model. Based on the transformer risk assessment model and life cyclecost model, a maintenance decision is made considering the reliability and economy oftransformer operation for a running power transformer. The achievements are shown asfollows.
A decision-making assessment model based on transformer health index isproposed in this dissertation. A cloud and evidence reasoning model of transformerinsulation condition assessment is proposed. A cloud and evidence reasoning model isused to combine the evaluation layer. The assessing results show that the proposedmethod is effective. In addition, considering running time, operating environment,inspection record, and accessories condition, transformer condition assessment modelbased on health index is established in the paper. Cases study shows that the model iseffective.
To improve the existing thermal aging oil-paper insulation life assessment model,the influence of initial moisture content and temperature on aging properties ofoil-paper is investigated. Based on the time-temperature superposition (TTSP) method,a time-temperature-moisture superposition (TTSMP) method is proposed to improve the lifetime model. In order to get the water content in paper, a water content of paperassessment method is studied based on FDS and water balance curve. In order to obtainthe DP of the insulation, an insulation aging assessment model based on furfural contentin oil is studied. The transformer hot spot temperature calculation model based on LoadGuidelines is applied to obtain the average temperature of a transformer. Compared withthe previous lifetime models, the benefit derived from the improved method is that notonly temperature, but also initial moisture content in paper is considered, which ishelpful for more rational estimations of insulation lifetime during long-term aging.
Aiming at solving the problem that reliability and economy of power transformersare not reasonably considered in the condition based maintenance problem recently, amaintenance decision making model, considering reliability and economy, based ontransformer risk assessment and life cycle cost analysis, is established to select the bestmaintenance strategy of a transformer. The model assess the best ratio of the risk-benefitand the annual life cycle cost in order to obtain the best maintenance decision making.The case study shows that the proposed maintenance decision making model canprovide effective advice to electrical companies.
本文以油中溶解气体为特征量深入研究了基于殖民竞争法优化支持向量机参数的变压器故障诊断方法和基于云推理的变压器多故障诊断和故障预测方法；以绝缘状态为主体，建立了基于健康指数的变压器运行状态评估模型；对基于时温水叠加的电力变压器绝缘寿命评估模型进行了研究；在构建变压器风险评估模型和全寿命周期成本模型的基础上，根据变压器的运行状态和绝缘寿命，兼顾变压器运行的可靠性和经济性，制定了变压器维护和检修策略。论文取得的创新性成果和主要结论主要有：
①提出了一种基于健康指数的变压器运行状态评估模型。构建了基于云理论和证据推理融合的绝缘状态评估模型，利用证据推理决策准则进行绝缘状态评估。实例分析结果表明，得到的绝缘状态评估结论准确。进一步，以绝缘状态评估结果为主体，综合考虑变压器的运行时间、运行环境等因素，采用健康指数评估变压器的运行状态，实例验证表明，提出的变压器运行状态评估方法是有效可行的。
②首次提出并建立了一种考虑时间、温度、水分联合影响的绝缘寿命评估模型。综合考虑变压器纸中水分含量、负荷情况、平均热点温度、油纸绝缘老化状态，提出了一种考虑时间、温度、水分联合影响的绝缘寿命评估模型，改进了传统绝缘寿命评估模型未考虑纸中水分影响的不足。实例验证结果表明，提出的寿命评估模型是有效的。
③提出了一种基于风险评估与全寿命周期成本分析的变压器检修策略决策模型。针对现有变压器检修策略制定中仅考虑其可靠性运行，较少考虑经济性运行的问题，本文综合考虑变压器的运行可靠性与经济性，以变压器的绝缘寿命为影响因素，提出了一种基于风险评估与全寿命周期成本分析的变压器检修策略决策模型，该模型根据变压器的状态信息获得其故障概率，在保证变压器于寿命周期内可靠性指标大于可靠运行要求的基础上，制定了基于风险评估与全寿命周期成本分析的变压器检修策略决策模型。通过实例验证，该检修策略决策模型准确有效。
An oil filled power transformer is a core component of the power system forenergy transmission and conversion, and its operating status directly affects the securityand stability of the power grid. Once a transformer breaks down, it may cause hugeeconomic losses, and it even causes serious social impact. However, blind repairs willlead to a lot of waste of human and material resources. Therefore, researches oftransformer insulation condition assessment, insulation life prediction, life cycle costanalysis, operational risk of the transformer, and condition based maintenance decisionmaking of the transformer considering the reliability and economy of transformeroperation, which can choose an appropriate condition-based maintenance strategy toreduce accident probability and promote the economical efficiency of electricalcompanies.
Based on regulations, this thesis studies transformer fault diagnosis using ICAoptimized SVM model, fault forecasting using cloud model, insulation assessmentmodel using cloud model and evidential reasoning, insulation life assessment modelusing time, temperature, and water information, transformer risk assessment model, andlife cycle cost model. Based on the transformer risk assessment model and life cyclecost model, a maintenance decision is made considering the reliability and economy oftransformer operation for a running power transformer. The achievements are shown asfollows.
A decision-making assessment model based on transformer health index isproposed in this dissertation. A cloud and evidence reasoning model of transformerinsulation condition assessment is proposed. A cloud and evidence reasoning model isused to combine the evaluation layer. The assessing results show that the proposedmethod is effective. In addition, considering running time, operating environment,inspection record, and accessories condition, transformer condition assessment modelbased on health index is established in the paper. Cases study shows that the model iseffective.
To improve the existing thermal aging oil-paper insulation life assessment model,the influence of initial moisture content and temperature on aging properties ofoil-paper is investigated. Based on the time-temperature superposition (TTSP) method,a time-temperature-moisture superposition (TTSMP) method is proposed to improve the lifetime model. In order to get the water content in paper, a water content of paperassessment method is studied based on FDS and water balance curve. In order to obtainthe DP of the insulation, an insulation aging assessment model based on furfural contentin oil is studied. The transformer hot spot temperature calculation model based on LoadGuidelines is applied to obtain the average temperature of a transformer. Compared withthe previous lifetime models, the benefit derived from the improved method is that notonly temperature, but also initial moisture content in paper is considered, which ishelpful for more rational estimations of insulation lifetime during long-term aging.
Aiming at solving the problem that reliability and economy of power transformersare not reasonably considered in the condition based maintenance problem recently, amaintenance decision making model, considering reliability and economy, based ontransformer risk assessment and life cycle cost analysis, is established to select the bestmaintenance strategy of a transformer. The model assess the best ratio of the risk-benefitand the annual life cycle cost in order to obtain the best maintenance decision making.The case study shows that the proposed maintenance decision making model canprovide effective advice to electrical companies.
引文
[1]国家电网公司.110(66)kV~500kV油浸式变压器(电抗器)检修规范[S].2005.
[2] G. Beck, D. Povh, D. Retzmann, E. Teltsch.全球大停电的经验教训[J].中国电力,2007,40(10):75-81.
[3]李春艳,孙元章,陈向宜,邓桂平.西欧“11.4”大停电事故的初步分析及防止我国大面积停电事故的措施[J].电网技术,2006,30(24):16-21.
[4]胡超凡,陈刚,朱伟江,赵玉柱.2005年国家电网安全运行情况分析[J].中国电力,2006,39(5):1-4.
[5]胡超凡,董昱,王轶禹,赵玉柱.2006年国家电网安全运行情况分析[J].中国电力,2007,40(5):23-27.
[6]赵晔,罗治强,赵玉柱.2007年国家电网安全运行情况分析[J].中国电力,2008,41(5):65-69.
[7]罗治强,董昱,胡超凡.2008年国家电网安全运行情况分析[J].中国电力,2009,42(5):8-12.
[8]马珂,王轶禹,董昱.2009年国家电网安全运行情况分析[J].中国电力,2010,43(11):1-4.
[9]孙建锋,葛睿,郑力,胡超凡.2010年国家电网安全运行情况分析[J].中国电力,2011,44(5):1-4.
[10]郑含博.电力变压器状态评估及故障智能分析研究[D].重庆大学,2012.
[11]孙才新.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.
[12]胡文唐,余绍峰,鲁宗相,等.输变电设备风险评估与检修策略优化[M].北京：中国电力出版社,2011.
[13] Yasuo Inoue, Kimio Suganuma, Masaru Kamba, et al. Development of oil-dissolved hydrogengas detector for diagnosis[J]. IEEE Trans. on Power Delivery,1990,5(1):226-232.
[14] Ekard Grossmann, Kurt Feser. Sensitive online PD-measurements of onsite oil/paper-insulateddevices by means of optimized acoustic emission techniques (AET)[J]. IEEE Trans. on PowerDelivery,2005,20(1):158-162.
[15] B. Ward. A survey of New Techniques in Insulation Monitoring of Power Transformers[J].IEEE Electrical Insulation Magazine,2001,17(3):16-23.
[16]王国利,郑毅,郝艳棒,等.用于变压器局部放电检测的超高频传感器的初步研究[J].中国电机工程学报,2002,22(4):154-160.
[17]应勇,刘富家.变压器绕组热点温度在线测量方法的研究[J].东北电力技术,2002,9:17-19.
[18] M.S. Sachdev, T.S. Sidhu, M.C. Wood. A Digital Relaying Algorithm for Deteting TransformerWinding Faults[J]. IEEE Transactions on Power Delivery,1989,4(3):1638-148.
[19] V. Sokolov, Z. Berler, V. Rashkes. Effective methods of assessment of insulation systemconditions in power transformers: a view based on practical experience[C]. ElectricalInsulation Conference and Electrical Manufacturing&Coil Winding Conference, Cincinnati,Oct.1999:659-667.
[20]程崯,王宇,余轩,毛志强.电力变压器运行状态综合评判指标的权重确定[J].中国电力,2011,44(4):26-30.
[21]黄华,傅晨钊.大型电力变压器状态分析综述[J].华东电力,2004,32(3):24-26.
[22]廖瑞金,黄飞龙,杨丽君,等.多信息量融合的电力变压器状态评估模型[J].高电压技术,2010,36(6):1455-1460.
[23] Y.Han, Y.H.Song. Condition monitoring techniques for electrical equipment－a literaturesurvey[J]. IEEE Trans. on Power Delivery,1998,13(4):1214-1223.
[24] Hong-Tzer Yang, Chiung-Chou Liao, and Jeng-Hong Chou. Fuzzy Learning VectorQuantization Networks for Power Transformer Condition Assessment[J]. IEEE Trans. onDielectrics and Electrical Insulation,2001,8(1):143-149.
[25]熊浩,孙才新,杜鹏,等.基于物元理论的电力变压器状态综合评估[J].重庆大学学报(自然科学版),2006,29(10):24-28.
[26]廖瑞金,王谦,骆思佳,等.基于模糊综合评判的电力变压器运行状态评估模型[J].电力系统自动化,2008,32(3):70-75.
[27]赵文清,朱永利,姜波,等.基于贝叶斯网络的电力变压器状态评估[J].高电压技术,2008,34(5):1032-1039.
[28] Ruijin Liao, Hanbo Zheng, Stanislaw Grzybowski, et al. An integrated decision-making modelfor condition assessment of power transformers using fuzzy approach and evidentialreasoning[J]. IEEE Transac-tions on Power Delivery,2011,26(2):1111-1118.
[29]高文胜,严璋,谈克雄.基于油中溶解气体分析的电力变压器绝缘故障诊断方法[J].电工电能新技术,2000,(1):22-26.
[30]熊浩.电力变压器绝缘状态综合评估方法研究[D].重庆大学博士学位论文,2003.
[31] R.R.Rogers, IEEE and IEC Codes to Interpret Incipient Faults in Transformer, Using Gas inOil Analysis,” IEEE Trans. on Dielectrics and Electrical Insulation, Vol.E1-13,1978,pp349-354.
[32] M.Duval, Fault Gases Formed in Oil-filed Breathing E.H.V. Power Transformer—theInterpretation of Gas Analysis data[C], in Proc. IEEE Power ENG.Soc. Conf., paperC74-476-8.
[33] Mineral Oil-Impregnated Electrical Equipment in Service–Guide to the Interpretation ofDissolved and Free Gases Analysis, IEC Std.60599.
[34]王财胜,孙才新,廖瑞金.变压器色谱监测中的BPNN故障诊断法[J].电网技术,1997,17(5)：323-325.
[35]梁永春,李彦明.改进型组合RBF神经网络的变压器故障诊断[J].高电压技术.2005,31(9):31-33.
[36] Q.Su, C.Mi, L.L.Lai, and P.Austin. A Fuzzy Dissolved Gas Analysis Method for the Diagnosisof Multiple Incipient Faults in a Transformer[J]. IEEE Trans. on Power Systems,2000,15(2):593-598.
[37]蔡金锭,王少芳.粗糙集理论在IEC-60599三比值故障诊断决策规则中的应用[J].中国电机工程学报,2005,25(11):134-139.
[38] W. G. Chen, C. Pan, Y. X. Yun and Y. L. Liu. Wavelet networks in power transformersdiagnosis using dissolved gas analysis[J]. IEEE Trans. on Power Delivery,2009,24(1):187-194.
[39]李明华,屈彦明,周孟戈,董明,等.基于多Agent及Petri网的变压器故障诊断系统[J].西安交通大学学报,2006,40(2)：223-227.
[40]廖瑞金.变压器绝缘故障诊断黑板型专家系统和基于遗传算法的故障预测研究[D].重庆：重庆大学,2003.
[41]赵文清.基于数据挖掘的变压器故障诊断和预测研究[D].北京：华北电力大学,2009.
[42]廖瑞金,廖玉祥,杨丽君,等.多神经网络与证据理论整合的变压器故障综合诊断方法的研究[J].中国电机工程学报,2006,26(3)：119-124.
[43] C. C. Chang and C. J. Lin, LIBSVM–A library for support vector machines.[Online]. Available:http://www.csie.ntu.edu.tw/~cjlin/libsvm.2001
[44]吕干云,程浩忠,董立新,等.基于多级支持向量机分类器的电力变压器故障识别[J].电力系统自动化学报,2005,17(1)：19-22.
[45] M.H. Wang. A novel extension method for transformer fault diagnosis [J], IEEE Trans. PowerDel.,2003,18(1):164-169.
[46] Z. Yang, W.H. Tang, A. Shintemirov, et al. Association rule mining-based dissolved gasanalysis for fault diagnosis of power transformers [J], IEEE Trans. Syst. Man Cybern. C, Appl.,2009,39(6):597-610.
[47] A. Shintemirov, W.H. Tang, Q.H. Wu. Power transformer fault classification based ondissolved gas analysis by implementing bootstrap and genetic programming [J], IEEE Trans.Syst. Man Cybern. C, Appl.,2009,39(1):69-79.
[48]邓宏贵,罗安,曹建,等.基因多点交叉遗传算法在变压器故障诊断中的应用[J].电网技术,2004,28(24):1-4.
[49]李中,苑津莎,张利伟.基于自组织抗体网络的电力变压器故障诊断[J].电工技术学报,2010,25(10):200-206.
[50]孙才新,李俭,郑海平,等.基于面积关联度分析的电力变压器绝缘故障诊断方法[J].电网技术,2002,26(7):24-29.
[51]杨廷方,李景禄,曾祥君,等.基于多种方法组合诊断模型的大型变压器故障诊断[J].电力系统自动化,2009,33(20):92-95.
[52]尚勇,闫春江,严璋,等.基于信息融合的大型油浸电力变压器故障诊断[J].中国电机工程学报,2002,22(7):115-118.
[53]莫娟,王雪,董明,等.基于粗糙集理论的电力变压器故障诊断方法[J].中国电机工程学报,2004,24(7):162-167.
[54]董明,屈彦明,周孟戈,等.基于组合决策树的油浸式电力变压器故障诊断[J].中国电机工程学报,2005,25(16):35-41.
[55]王永强,律方成,李和明.基于贝叶斯网络和油中溶解气体分析的变压器故障诊断算法[J].电工技术学报,2004,19(12):74-77.
[56]王永强,律方成,李和明.基于粗糙集理论和贝叶斯网络的电力变压器故障诊断方法[J].中国电机工程学报,2006,26(8):137-141.
[57]周爱华,张彼德,张厚宣.基于人工免疫分类算法的电力变压器故障诊断[J].高电压技术,2007,33(8):77-80.
[58]陈江波,文习山,蓝磊,等.基于新径向基函数网络的变压器故障诊断法[J].高电压技术,2007,33(3):140-143.
[59] J. S. Chou, M. Y. Cheng, Y. W. Wu, et al. Optimizing parameters of support vector machineusing fast messy genetic algorithm for dispute classification [J]. Expert Systems WithApplications.2014,41(8):3955-3964.
[60] S. W. Fei, M. J. Wang, Y. B. Miao, et al. Particle swarm optimization-based support vectormachine for forecasting dissolved gases content in power transformer oil[J]. EnergyConversion and Management.2009,50(6):1604-1609.
[61] H. R. L. Azad. An Application of Opposition Based Colonial Competitive Algorithm to SolveNetwork Count Location Problem [J]. I.J. Intelligent Systems and Applications,2014,01:29-35.
[62] R. E. James, Q. Su. Condition Assessment of High Voltage Insulation in Power SystemEquipment[M]. London, The Institution of Engineering and Technology,2008.
[63]罗运柏,于萍,宁斌,等.用灰色模型预测变压器油中溶解气体的含量[J].中国电机工程学报,2001,21(3):65-69.
[64]赵文清.基于数据挖掘的变压器故障诊断和预测研究[D].华北电力大学博士学位论文,2009.
[65]费胜巍,孙宇.融合粗糙集与灰色理论的电力变压器故障预测[J].中国电机工程学报,2008,28(16):154-160.
[66]杨廷方,刘沛,李浙,等.应用新型多方法组合预测模型估计变压器油中溶解气体深度[J].中国电机工程学报,2008,28(31):108-113.
[67]费胜巍,孙宇.融合粗糙集与灰色理论的电力变压器故障预测[J].中国电机工程学报,2008,28(16):154-160.
[68]杨廷方,刘沛,李浙,等.应用新型多方法组合预测模型估计变压器油中溶解气体深度[J].中国电机工程学报,2008,28(31):108-113.
[69]谢道文,施式亮.基于云理论与加权马尔可夫模型的矿井涌水量预测[J].中南大学学报,2012,43(6)：2308-2315.
[70]杨薛明,苑津莎,王剑锋,等.基于云理论的配电网空间负荷预测方法研究[J].中国电机工程学报,2006,26(6):30-36.
[71]雷铭.电力设备诊断手册[M].北京:中国电力出版社,2001.
[72] G. C. Stone. Use of partial discharge measurements to assess the condition of rotating machineinsulation [J]. IEEE Electrical Insulation Magazine,1996,12(4):23-27.
[73] G. C. Stone, V. Warren. Effect of manufacturer, winding age and insulation type on statorwinding partial discharge levels [J]. IEEE Electrical Insulation Magazine,2004,20(5):13-17.
[74] N. C. Sahoo, M. M. A. Salama, R. Bartnikas. Trends in partial discharge pattern classification:a survey [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2005,12(2):248-264.
[75] T. K. Saha,P. Purkait. Investigation of an expert system for the condition assessment oftransformer insulation based on dielectric response measurements [J]. IEEE Transactions onPower Delivery,2004,19(3):1127-1134.
[76] J. Blennow, C. Ekanayake, K. Walczak, B. A. Garcia. Field experiences with measurements ofdielectric response in frequency domain for power transformer diagnostics [J]. IEEETransactions on Power Delivery,2006,21(2):681-688.
[77] A. M. Emsley. Kinetics and mechanisms of degradation of cellulosic insulation in powertransformers [J]. Polymer Degradation and Stability,1994,44(3):343-349.
[78] X. Zou,T. Uesaka,N. Gurnagul. Prediction of paper permanence by accelerated aging I. Kineticanalysis of the aging process [J]. Cellulose,1996,3(1):243-267.
[79] D. M. Allan. Practical life-assessment technique for aged transformer insulation [J]. IEEProceedings-A: Physical Science,1993,140(5):404-408.
[80] P. J. Burton, M. Carballeira, C. W. Fuller, Application of liquid chromatography to the analysisof electrical insulating materials [C].CIGRE, Intern. Conf. Large High Voltage ElectricSystems, Paris, France,1988.12.
[81]薛辰东.用油中糠醛含量估计变压器绝缘老化故障[R].电力部电力科学研究院,1990.12.
[82] IEEE Std. C57.91-1995. IEEE Guide for Loading Mineral-Oil-Immersed Transformers [S].June14,1995.
[83] Load guide for oil-immersed power transformers [S]. IEC Std.354-1991-09, Sept.1991.
[84] PT Load Version6.1Users Manual: Power Transformer Loading Program [M], EPRI, PaloAlto, CA:2002.1007083.
[85]王有元,周婧婧,陈伟根,等.基于模糊决策的电力变压器风险评估方法[J].仪器仪表学报,2009,30(8):1662-1667.
[86]白翠粉,高文胜,丁登伟.利用小世界网络的电力变压器风险评估方法[J].高电压技术,2010,36(4):869-872.
[87] T. Hjartarson, B. Jesus, D. T. Hughes, et al. Development of health indices for asset conditionassessment[C]. Transmission and Distribution Conference and Exposition,2003,2:541-544.
[88] F. Backlund. Managing the introduction of RCM experiences from a Swedish hydropowercompany[C]. IEEE Power Engineering Society General Meeting.2005,6(3):2646-2648.
[89] G. M Hardwick. Reliability centered maintenance at Florida Power Corporation[C]. IEEEPower Engineering Society Summer Meeting,1999,6(2):1169-1170
[90]陈志林.以可靠性为中心的维修体系在大亚湾核电站的应用[J].中国设备工程,2006,6:13-14
[91]王爱华,李志刚.以可靠性为中心的检修在淄博供电公司的应用[J].山东电力技术,2006,4:11-13。
[92]杨杰以可靠性为中心的检修在电力系统的应用[J]山西电力技术,1999,10:34-36
[93]余绍峰,胡文堂,陈金法,等.输变电设备风险评估与维修决策[J],浙江电力,2009,3:1-5.
[94]许蜻,王晶,高峰等.电力设备状态检修技术研究综述[J].电网技术.2000(8):48-52.
[95] G. W. David. Life Cycle Costing-Theory Information Acquisition and Application[J].International Journal of Project Management,1997,15(6):335-344.
[96] M. J. Ki., P. Minjae, H. P. Dong. System Maintenance Cost Dependent on Life Cycle underRenewing Warranty Policy[J]. Reliability Engineering and System Safety,2010.02.
[97] I. A. Eleftherios, A. T. Marina, S. G. Pavlos. et al. Energy Efficient Transformer SelectionImplementing Life Cycle Cost and Environment Externalities[C].9th International Conference:Electrical and Power Quality and Utilisation,2007.
[98]何剑,程林,孙元章,等.条件相依的输变电设备短期可靠性模型[J].中国电机工程学报,2009,29(7):39-46.
[99] N. Julia, B. Lina. Maintenance Management of Wind Power Systems Using ConditionMonitoring Systems-Life Cycle Cost Analysis for Two Case Studies[J]. IEEE Translation onEnergy Conversion,2007.
[100]S. Khaled, Z. Tarek. Simulation as a Tool for Life Cycle Cost Analysis[C]. Proceedings of the2008Winter Simulation Conference.
[101]梅志农,袁思吟,韩天祥,李莉华.上海世博变电站工程中的LCC实践[J].上海电力,2009,(3):242-244.
[102]曾庆禹.变电站的寿命周期成本与新技术发展分析[J].中国电力,2000,33(12):35-38
[103]T. Shimakage, K. Wu, T. Kato, T. Okamoto, Y. Suzuoki. Life-Cycle-Cost Comparison ofDifferent Degradation Diagnosis Methods for Cables[J]. Electrical Insulation Materials,2005,3(6):737-740.
[104]赵宏,卢永平,马维清,张勇,杜永平.基于LCC的断路器可靠性分析[J].现代电力,2009,26(5):89-92.
[105]任玉珑,王建,牟刚,王恒炎.基于CA模型的电力设备全寿命周期成本研究[J].工业工程与管理,2008,(5):63-66.
[106]J. M. Brophy, L. J. Erickson. Cost-effectiveness of Drug-eluting Coronary Stents in Quebec[J].Canada, International Journal of Technology Assessment in Health Care,2005,21(3):326-333.
[107]W. E. Walker. POLSSS: Overview and Cost-effectiveness Analysis[J]. Safety Science.2000,35(1):105-121.
[108]李凡,姚光仑.最优线性分派法的防空武器系统费效分析[J].火力与指挥控制,2005,(30):95－97.
[109]A. Amirteimoori, S. Kordrostami, A. Rezaitabar. An Improvement to the Cost EfficiencyInterval: A DEA-based Approach[J]. Applied Mathematics and Computation,2006,181(1):775-781.
[110]GB/T7252-2001.变压器油中溶解气体分析和判断导则.2001.
[111]国家电网公司生产技术部.设备状态检修规章制度和技术标准汇编[S].北京:中国电力出版社,2008.
[112]孙永奎.基于支持向量机的模拟电路故障诊断方法研究[D].电子科学大学博士学位论文,2009.
[113]W. S. Sarle. Neural Network FAQ.[Online]. Available:ftp://ftp.sas.com/pub/neural/FAQ2.html.
[114]李烨.基于支持向量机的集成学习研究[D].上海交通大学博士学位论文,2007.
[115]S. S. Keerthi, C. J. Lin. Asymptotic behaviors of support vector machines with Gaussiankernel[J]. Neural Computation,2003,15(7):1667-1689.
[116]C. C. Chang, C. J. Lin. LIBSVM–A library for support vector machines.[Online]. Available:http://www.csie.ntu.edu.tw/~cjlin/libsvm.2001.
[117]E. Atashpaz-Gargari, C. Lucas. Imperialist competitive algorithm: An algorithmforoptimization inspired by imperialistic competition[C]. In: Evolutionary Computation.CEC2007. IEEE Congress on,2007:4661-4667.
[118]E. Atashpaz-Gargari, L. Caro. Designing an optimal PID controller using Colonial CompetitiveAlgorithm[C]. In: First Iranian Joint Congress on Intelligent and FuzzySystems,2007.
[119]E. Atashpaz-Gargari, F. Hashemzadeh, C. Lucas. Designing MIMO PIID controllerusingcolonial competitive algorithm: Applied to distillation column process[C]. In:EvolutionaryComputation, CEC.(IEEE World Congress on ComputationalIntelligence). IEEE Congress on,2008:1929-1934.
[120]EA. Gargari, F. Hashemzadeh, R. Rajabioun, C. Lucas. Colonial competitive algorithm:A novelapproach for PID controller design in MIMO distillation column process[J]. InternationalJournal of Intelligent Computing and Cybernetics,2008,1(3):337-355.
[121]R. Rajabioun, E. Atashpaz-Gargari, C. Lucas.(2008)Colonial Competitive Algorithm asa Toolfor Nash Equilibrium Point Achievement Computational Science and Its Applications–ICCSA2008.[C]. In: Gervasi O, Murgante B, Laganà A, Taniar D, Mun Y,Gavrilova M (eds), vol5073.Lecture Notes in Computer Science. Springer Berlin/Heidelberg:680-695.
[122]A. Khabbazi, EA. Gargari, C. Lucas. Imperialist competitive algorithm for minimum biterrorrate beamforming[J]. International Journal of Bio-Inspired Computation,2009,1(1/2):125-133.
[123]S. Forouharfard, M. Zandieh. An imperialist competitive algorithm to schedule ofreceiving andshipping trucks in cross-docking systems[J]. The International Journal ofAdvancedManufacturing Technology,2010,51(9):1179-1193.
[124]A. Kaveh, S. Talatahari. Optimum design of skeletal structures using imperialistcompetitivealgorithm[J]. Computers&Structures,2010,88(21-22):1220-1229.
[125]J.L. Lin, C.W. Cho, and H.C. Chuan, Imperialist Competitive Algorithms with PerturbedMoves for Global Optimization[J]. Applied Mechanics and Materials,2013,284-287:3135-3139.
[126]S. Nazari-Shirkouhi, H. Eivazy, R. Ghodsi, K. Rezaie, E. Atashpaz-Gargari. Solvingtheintegrated product mix-outsourcing problem using the Imperialist CompetitiveAlgorithm[J].Expert Systems with Applications,2010,37(12):7615-7626.
[127]F. Sarayloo, R. Tavakkoli-Moghaddam. Imperialistic Competitive Algorithm forSolving aDynamic Cell Formation Problem with Production Planning. In: Huang D-S,Zhao Z,Bevilacqua V, Figueroa J (eds) Advanced Intelligent Computing Theories andApplications, vol6215. Lecture Notes in Computer Science. Springer Berlin/Heidelberg,2010:266-276.
[128]M. H. Sayadnavard, AT. Haghighat, M. Abdechiri. Wireless sensor network localizationusingImperialist Competitive Algorithm[C]. In: Computer Science and InformationTechnology(ICCSIT),20103rd IEEE International Conference on,9-11July2010:818-822.
[129]M. Moghimi Hadji, B. Vahidi. A Solution to the Unit Commitment Problem Using ImperialisticCompetition Algorithm[J]. IEEE Transactions on Power Systems,2011,1(1):99.
[130]M. Bagher, M.Zandieh, H. Farsijani. Balancing of stochastic U-type assembly lines:animperialist competitive algorithm[J]. The International Journal of Advanced ManufacturingTechnology,2011,54:271-285.
[131] T. Niknam, Fard. E. aherian, N. Pourjafarian, A. Rousta. An efficient hybrid algorithmbasedon modified imperialist competitive algorithm and K-means for data clustering[J]. EngineeringApplications of Artificial Intelligence,2011,24(2):306-317.
[132]段华.支持向量机的增量学习算法研究[D].上海交通大学博士学位论文,2008.
[133]J. Weston, C. Watkins. Multi-class support vector machines[C]. Proc. ESANN99, M. Verleysen,Ed., Brussels, Belgium,1999.
[134]T. VAN. Gestel, J. A. K. Suykens, B. Baesens, et al. Benchmarking least squares support vectormachine classifiers[J]. Machine Learning,2004,54,(1):5-32.
[135]A. Mathur, G. M. Foody. Multiclass and binary SVM classification: Implications for trainingand classification users[J]. IEEE Geos. Remote Sens. Letters,2008,5,(2):241-245.
[136]A. Passerini, M. Pontil, P. Frasconi. New results on error correcting output codes of kernelmachines[J]. IEEE Trans. Neural Networks,2004,15,(1):45-54.
[137]C. W. Hsu, C. J. LIN. A comparison of methods for multiclass support vector machines[J].IEEE Trans. Neural Networks,2002,13,(2):415-425.
[138]T. G. Dietterich, G. Bakiri. Solving multiclass learning problems via error-correcting outputcodes[J]. Journal of Artificial Intelligence Research,1995,2:263-286.
[139]T. Van Gestel, J. A. K. Suykens, G. Lanckriet. Multiclass LS-SVMs: moderated outputs andcoding-decoding schemes[J]. Neural Processing Letters,2002,15(1):45-48.
[140]R. Liao, H. B. Zheng, et al. A multiclass SVM-based classifier for transformer fault diagnosisusing a particle swarm optimizer with time-varying acceleration coefficients[J]. EuropeanTransactions on Electrical Power,(Article first published online:10NOV2011,DOI:10.1002/etep.651).
[141]A. Frank, A. Asuncion. UCI machine learning repository.[Online]. Available:http://archive.ics.uci.edu/ml.2010.
[142]K. Meng, Z. Y. Dong, D. H. Wang, et al. A self-adaptive RBF neural network classifier fortransformer fault analysis[J]. IEEE Trans. Power Syst.,2010,25,(3):1350-1360.
[143]李德毅.不确定性人工智能[M].北京：国防工业出版社,2005.
[144]郑海平,孙才新,李俭,等.诊断电力变压器故障的一种灰色关联度分析模式及方法[J].中国电机工程学报,2001,21(10):106-109.
[145]秦昆,王佩.基于云变换的曲线拟合新方法[J].计算机工程与应用,2008,44(23):56-58.
[146]丁月华,文贵华,郭炜强.基于云X信息的逆向云新算法[J].系统仿真学报,2004,16(11)：2417-2420.
[147]冯兴杰,周谆. Apriori算法的改进[J].计算机工程,2005,31:172-173.
[148]李德毅,刘常昱.论正态云模型的普适性[J].中国工程科学,2004,6(8)：28-34.
[149]蒋嵘,李德毅,陈晖.基于云模型的时间序列预测[J].解放军理工大学学报,2000,1(5)：13-18.
[150]陈昊,李兵.云推理方法及其在预测中的应用[J].计算机科学,2011,38(7):209-211.
[151]J. B. Yang, M. G. Singh. An evidential reasoning approach for multiple-attribute decisionmaking with uncertainty[J]. IEEE Trans. Syst., Man, Cybern.,1994,24(1):1-18.
[152]IEEE Std.637-1985. IEEE Guide for the Reclamation of Insulating Oil and Criteria for Its Use.1985.
[153]IEEE Std. C57.125-1991. IEEE Guide for Failure Investigation, Documentation, and Analysisfor Power Transformers and Shunt Reactors.1991.
[154]IEEE Std. C57.106-2006. IEEE Guide for Acceptance and Maintenance of Insulating Oil inEquipment.2006.
[155]T. L. Saaty. The Analytic Hierarchy Process[M]. McGraw-Hill, New York,1980.
[156]梁梁,盛昭翰,徐南荣.一种改进的层次分析法[J].系统工程,1989,7(3):5-7.
[157]梁梁,余磊.对《一种改进的AHP法》的补注[J].系统工程,1991,9(3):64-65.
[158]Ruijin Liao, Yiyi Zhang, Lijun Yang, Hanbo Zheng, Xu She. A cloud and evidential reasoningintegrated model for insulation condition assessment of high voltage transformers[J].International Transactions on Electrical Energy Systems, Article first published online:23APR2013.
[159]张镱议,廖瑞金,杨丽君,郑含博,孙才新.基于云理论的电力变压器绝缘状态评估方法[J].电工技术学报,2012,05:13-20.
[160]刘常昱,李德毅,杜鹢,等.正态云模型的统计分析[J].信息与控制,2005,34(2):236-239.
[161]张峰,张鹏林,吕志勇,等.云模型在城镇空气质量评价中的应用[J].环境科学与技术,2009,32(6):160-164.
[162]W. H. Tang, K. Spurgeon, Q. H. Wu, Z. J. Richardson. An evidential reasoning approach totransformer condition assessments[J]. IEEE Trans. Power Del.,2004,19(4):1696-1703.
[163]龚本刚.基于证据理论的不完全信息多属性决策方法研究[D].中国科学技术大学博士学位论文,2007.
[164]肖明珠.基于证据理论的不确定性处理研究及其在测试中的应用[D].电子科技大学博士学位论文,2008.
[165]H.W. Guo, W.K. Shi, Y. Deng. Evaluating Sensor Reliability in Classification Problems Basedon Evidence Theory. Systems[J], IEEE Transactions on Man, and Cybernetics.2006,36,(5):970-981.
[166]Y. Deng, W.K. Shi, Z.F. Zhu, Q. Liu. Combining belief functions based on distance ofevidence[J]. Decision Support Systems.2004,38,(3):489-493.
[167]Y. Deng, D. Wang, Q. Liu, Y.J. Zhang. A new method to analyze evidence conflict[J]. ControlTheory&Applications.2011,6,6-13.
[168]廖玉祥.一种电力变压器运行状态综合评估模型的研究[D].重庆大学硕士学位论文,2006.
[169]廖瑞金,肖中男,巩晶,等.应用马尔科夫模型评估电力变压器可靠性[J].高电压技术，2010,36(2):322-328.
[170]Hu Ghes D, G. Dennis, J. Walker, et al. Condition based risk management (CBRM) enablingasset condition information to be central to corporate decision making[C]. Proceedings of the1st World Congress on Engineering Asset Management, July11-14,2006, Gold Coast,Australia：1212-1217.
[171]马志钦.变压器油纸绝缘的频域介电响应特性与绝缘状态评估方法研究[D].重庆大学,2012.
[172]杨丽君.变压器油纸绝缘老化特征量与寿命评估方法研究[D].重庆大学,2009.
[173]郝建.变压器油纸绝缘热老化的时频域介电和空间电荷特性研究[D].重庆大学,2012.
[174]朱恒宣.油浸式变压器绕组热点预测及光纤测温[D].河北工业大学,2011.
[175]陈培伟,陈涛.变压器绕组温度计的原理及其应用[J].华电技术,2008,10:14-15+21.
[176]黄勇.电力变压器故障的红外诊断技术应用研究[D].重庆大学,2001.
[177]J. Jalbert, M. C. Lessard, M. Ryadi."Cellulose Chemical Markers in Transformer OilInsulation Part1: Temperature Correction Factors", IEEE Transactions on Dielectrics andElectrical Insulation,2013,20(6):2287-2291.
[178]J.M.K.MacAlpine,张潮海.糠醛浓度判断变压器绝缘纸寿命的综述[J].高电压技术,2001,04:63-64+67.
[179]www.pecj.or.jp/japanese/report/2001report/2001.an1-1.pdf
[180]杨丽君,邓帮飞,廖瑞金,等.应用时–温–水分叠加方法改进油纸绝缘热老化寿命模型[J],中国电机工程学报,2011,31(31):196-203.
[181]Urzhumtsev, Y.S. Time-temperature superposition[J]. Review, Mechanics of CompositeMaterials,1975,11(1):57-72.
[182]L. Yang, R. Liao, and C. Sun. Influence of Natural Ester on Thermal Aging Characteristics ofOil-paper in Power Transformer[J]. European Transactions on Electrical Power,2010,20:1223-1236.
[183]刘玉仙.油纸绝缘变压器中水分的聚积及其对热老化寿命的影响[J].变压器,2004,41(2)：8-12.
[184]Shroff, D.H., and Stannett, A.W. A review of paper aging in power transformers[J]. IEEProceedings of generation, transmission and distribution,1985,132(6):312-319.
[185]Pahlavanpour, M. Martins and Eklund, Study of Moisture Equilibrium in Oil-Paper Systemwith Temperature Variation[C]. Proceedings of the7th International Conference on Propertiesand Applications of Dielectric Materials, June1-52003Nagoya,1124-1129.
[186]王有元.基于可靠性和风险评估的电力变压器状态维修决策方法研究[D].重庆大学,2008.
[187]帅军庆.资产全寿命周期管理理论、方法及应用[M]北京：中国电力出版社,2010.4.
[188]陈绍辉.基于全寿命周期成本的变电设备状态维修策略研究[D].华北电力大学,2012.
[189]王一,王慧芳,张亮,等.基于效用和成本的状态检修维修方式选择研究[J].电力系统保护与控制,2010,38(19):39-45.
[190]潘乐真.基于设备及电网风险综合评判的输变电设备状态检修决策优化[D].上海交通大学,2010.
[191]许珂.大型电力变压器故障实例统计分析[J].华章,2008,10：162-163.
[192]中华人民共和国国家统计局.2012年国内生产总值(GDP)初步核算情况http：//www.stats.gov.cn/tjfx/jdfx/t20130119_402867380.htm.北京,2013.
[193]中华人民共和国国家能源局.国家能源局发布2012年全社会用电量http：//www.nea.gov.cn/2013-01/14/c_132100340.htm.北京,2013.
[194]方大千.变压器速算速查手册[M].北京：中国水利水电出版社,2004.
[195]夏成军,邱桂华,黄冬燕,等.电力变压器全寿命周期成本模型及灵敏度分析[J].华东电力,2012,40(1):26-30.
[2] G. Beck, D. Povh, D. Retzmann, E. Teltsch.全球大停电的经验教训[J].中国电力,2007,40(10):75-81.
[3]李春艳,孙元章,陈向宜,邓桂平.西欧“11.4”大停电事故的初步分析及防止我国大面积停电事故的措施[J].电网技术,2006,30(24):16-21.
[4]胡超凡,陈刚,朱伟江,赵玉柱.2005年国家电网安全运行情况分析[J].中国电力,2006,39(5):1-4.
[5]胡超凡,董昱,王轶禹,赵玉柱.2006年国家电网安全运行情况分析[J].中国电力,2007,40(5):23-27.
[6]赵晔,罗治强,赵玉柱.2007年国家电网安全运行情况分析[J].中国电力,2008,41(5):65-69.
[7]罗治强,董昱,胡超凡.2008年国家电网安全运行情况分析[J].中国电力,2009,42(5):8-12.
[8]马珂,王轶禹,董昱.2009年国家电网安全运行情况分析[J].中国电力,2010,43(11):1-4.
[9]孙建锋,葛睿,郑力,胡超凡.2010年国家电网安全运行情况分析[J].中国电力,2011,44(5):1-4.
[10]郑含博.电力变压器状态评估及故障智能分析研究[D].重庆大学,2012.
[11]孙才新.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.
[12]胡文唐,余绍峰,鲁宗相,等.输变电设备风险评估与检修策略优化[M].北京：中国电力出版社,2011.
[13] Yasuo Inoue, Kimio Suganuma, Masaru Kamba, et al. Development of oil-dissolved hydrogengas detector for diagnosis[J]. IEEE Trans. on Power Delivery,1990,5(1):226-232.
[14] Ekard Grossmann, Kurt Feser. Sensitive online PD-measurements of onsite oil/paper-insulateddevices by means of optimized acoustic emission techniques (AET)[J]. IEEE Trans. on PowerDelivery,2005,20(1):158-162.
[15] B. Ward. A survey of New Techniques in Insulation Monitoring of Power Transformers[J].IEEE Electrical Insulation Magazine,2001,17(3):16-23.
[16]王国利,郑毅,郝艳棒,等.用于变压器局部放电检测的超高频传感器的初步研究[J].中国电机工程学报,2002,22(4):154-160.
[17]应勇,刘富家.变压器绕组热点温度在线测量方法的研究[J].东北电力技术,2002,9:17-19.
[18] M.S. Sachdev, T.S. Sidhu, M.C. Wood. A Digital Relaying Algorithm for Deteting TransformerWinding Faults[J]. IEEE Transactions on Power Delivery,1989,4(3):1638-148.
[19] V. Sokolov, Z. Berler, V. Rashkes. Effective methods of assessment of insulation systemconditions in power transformers: a view based on practical experience[C]. ElectricalInsulation Conference and Electrical Manufacturing&Coil Winding Conference, Cincinnati,Oct.1999:659-667.
[20]程崯,王宇,余轩,毛志强.电力变压器运行状态综合评判指标的权重确定[J].中国电力,2011,44(4):26-30.
[21]黄华,傅晨钊.大型电力变压器状态分析综述[J].华东电力,2004,32(3):24-26.
[22]廖瑞金,黄飞龙,杨丽君,等.多信息量融合的电力变压器状态评估模型[J].高电压技术,2010,36(6):1455-1460.
[23] Y.Han, Y.H.Song. Condition monitoring techniques for electrical equipment－a literaturesurvey[J]. IEEE Trans. on Power Delivery,1998,13(4):1214-1223.
[24] Hong-Tzer Yang, Chiung-Chou Liao, and Jeng-Hong Chou. Fuzzy Learning VectorQuantization Networks for Power Transformer Condition Assessment[J]. IEEE Trans. onDielectrics and Electrical Insulation,2001,8(1):143-149.
[25]熊浩,孙才新,杜鹏,等.基于物元理论的电力变压器状态综合评估[J].重庆大学学报(自然科学版),2006,29(10):24-28.
[26]廖瑞金,王谦,骆思佳,等.基于模糊综合评判的电力变压器运行状态评估模型[J].电力系统自动化,2008,32(3):70-75.
[27]赵文清,朱永利,姜波,等.基于贝叶斯网络的电力变压器状态评估[J].高电压技术,2008,34(5):1032-1039.
[28] Ruijin Liao, Hanbo Zheng, Stanislaw Grzybowski, et al. An integrated decision-making modelfor condition assessment of power transformers using fuzzy approach and evidentialreasoning[J]. IEEE Transac-tions on Power Delivery,2011,26(2):1111-1118.
[29]高文胜,严璋,谈克雄.基于油中溶解气体分析的电力变压器绝缘故障诊断方法[J].电工电能新技术,2000,(1):22-26.
[30]熊浩.电力变压器绝缘状态综合评估方法研究[D].重庆大学博士学位论文,2003.
[31] R.R.Rogers, IEEE and IEC Codes to Interpret Incipient Faults in Transformer, Using Gas inOil Analysis,” IEEE Trans. on Dielectrics and Electrical Insulation, Vol.E1-13,1978,pp349-354.
[32] M.Duval, Fault Gases Formed in Oil-filed Breathing E.H.V. Power Transformer—theInterpretation of Gas Analysis data[C], in Proc. IEEE Power ENG.Soc. Conf., paperC74-476-8.
[33] Mineral Oil-Impregnated Electrical Equipment in Service–Guide to the Interpretation ofDissolved and Free Gases Analysis, IEC Std.60599.
[34]王财胜,孙才新,廖瑞金.变压器色谱监测中的BPNN故障诊断法[J].电网技术,1997,17(5)：323-325.
[35]梁永春,李彦明.改进型组合RBF神经网络的变压器故障诊断[J].高电压技术.2005,31(9):31-33.
[36] Q.Su, C.Mi, L.L.Lai, and P.Austin. A Fuzzy Dissolved Gas Analysis Method for the Diagnosisof Multiple Incipient Faults in a Transformer[J]. IEEE Trans. on Power Systems,2000,15(2):593-598.
[37]蔡金锭,王少芳.粗糙集理论在IEC-60599三比值故障诊断决策规则中的应用[J].中国电机工程学报,2005,25(11):134-139.
[38] W. G. Chen, C. Pan, Y. X. Yun and Y. L. Liu. Wavelet networks in power transformersdiagnosis using dissolved gas analysis[J]. IEEE Trans. on Power Delivery,2009,24(1):187-194.
[39]李明华,屈彦明,周孟戈,董明,等.基于多Agent及Petri网的变压器故障诊断系统[J].西安交通大学学报,2006,40(2)：223-227.
[40]廖瑞金.变压器绝缘故障诊断黑板型专家系统和基于遗传算法的故障预测研究[D].重庆：重庆大学,2003.
[41]赵文清.基于数据挖掘的变压器故障诊断和预测研究[D].北京：华北电力大学,2009.
[42]廖瑞金,廖玉祥,杨丽君,等.多神经网络与证据理论整合的变压器故障综合诊断方法的研究[J].中国电机工程学报,2006,26(3)：119-124.
[43] C. C. Chang and C. J. Lin, LIBSVM–A library for support vector machines.[Online]. Available:http://www.csie.ntu.edu.tw/~cjlin/libsvm.2001
[44]吕干云,程浩忠,董立新,等.基于多级支持向量机分类器的电力变压器故障识别[J].电力系统自动化学报,2005,17(1)：19-22.
[45] M.H. Wang. A novel extension method for transformer fault diagnosis [J], IEEE Trans. PowerDel.,2003,18(1):164-169.
[46] Z. Yang, W.H. Tang, A. Shintemirov, et al. Association rule mining-based dissolved gasanalysis for fault diagnosis of power transformers [J], IEEE Trans. Syst. Man Cybern. C, Appl.,2009,39(6):597-610.
[47] A. Shintemirov, W.H. Tang, Q.H. Wu. Power transformer fault classification based ondissolved gas analysis by implementing bootstrap and genetic programming [J], IEEE Trans.Syst. Man Cybern. C, Appl.,2009,39(1):69-79.
[48]邓宏贵,罗安,曹建,等.基因多点交叉遗传算法在变压器故障诊断中的应用[J].电网技术,2004,28(24):1-4.
[49]李中,苑津莎,张利伟.基于自组织抗体网络的电力变压器故障诊断[J].电工技术学报,2010,25(10):200-206.
[50]孙才新,李俭,郑海平,等.基于面积关联度分析的电力变压器绝缘故障诊断方法[J].电网技术,2002,26(7):24-29.
[51]杨廷方,李景禄,曾祥君,等.基于多种方法组合诊断模型的大型变压器故障诊断[J].电力系统自动化,2009,33(20):92-95.
[52]尚勇,闫春江,严璋,等.基于信息融合的大型油浸电力变压器故障诊断[J].中国电机工程学报,2002,22(7):115-118.
[53]莫娟,王雪,董明,等.基于粗糙集理论的电力变压器故障诊断方法[J].中国电机工程学报,2004,24(7):162-167.
[54]董明,屈彦明,周孟戈,等.基于组合决策树的油浸式电力变压器故障诊断[J].中国电机工程学报,2005,25(16):35-41.
[55]王永强,律方成,李和明.基于贝叶斯网络和油中溶解气体分析的变压器故障诊断算法[J].电工技术学报,2004,19(12):74-77.
[56]王永强,律方成,李和明.基于粗糙集理论和贝叶斯网络的电力变压器故障诊断方法[J].中国电机工程学报,2006,26(8):137-141.
[57]周爱华,张彼德,张厚宣.基于人工免疫分类算法的电力变压器故障诊断[J].高电压技术,2007,33(8):77-80.
[58]陈江波,文习山,蓝磊,等.基于新径向基函数网络的变压器故障诊断法[J].高电压技术,2007,33(3):140-143.
[59] J. S. Chou, M. Y. Cheng, Y. W. Wu, et al. Optimizing parameters of support vector machineusing fast messy genetic algorithm for dispute classification [J]. Expert Systems WithApplications.2014,41(8):3955-3964.
[60] S. W. Fei, M. J. Wang, Y. B. Miao, et al. Particle swarm optimization-based support vectormachine for forecasting dissolved gases content in power transformer oil[J]. EnergyConversion and Management.2009,50(6):1604-1609.
[61] H. R. L. Azad. An Application of Opposition Based Colonial Competitive Algorithm to SolveNetwork Count Location Problem [J]. I.J. Intelligent Systems and Applications,2014,01:29-35.
[62] R. E. James, Q. Su. Condition Assessment of High Voltage Insulation in Power SystemEquipment[M]. London, The Institution of Engineering and Technology,2008.
[63]罗运柏,于萍,宁斌,等.用灰色模型预测变压器油中溶解气体的含量[J].中国电机工程学报,2001,21(3):65-69.
[64]赵文清.基于数据挖掘的变压器故障诊断和预测研究[D].华北电力大学博士学位论文,2009.
[65]费胜巍,孙宇.融合粗糙集与灰色理论的电力变压器故障预测[J].中国电机工程学报,2008,28(16):154-160.
[66]杨廷方,刘沛,李浙,等.应用新型多方法组合预测模型估计变压器油中溶解气体深度[J].中国电机工程学报,2008,28(31):108-113.
[67]费胜巍,孙宇.融合粗糙集与灰色理论的电力变压器故障预测[J].中国电机工程学报,2008,28(16):154-160.
[68]杨廷方,刘沛,李浙,等.应用新型多方法组合预测模型估计变压器油中溶解气体深度[J].中国电机工程学报,2008,28(31):108-113.
[69]谢道文,施式亮.基于云理论与加权马尔可夫模型的矿井涌水量预测[J].中南大学学报,2012,43(6)：2308-2315.
[70]杨薛明,苑津莎,王剑锋,等.基于云理论的配电网空间负荷预测方法研究[J].中国电机工程学报,2006,26(6):30-36.
[71]雷铭.电力设备诊断手册[M].北京:中国电力出版社,2001.
[72] G. C. Stone. Use of partial discharge measurements to assess the condition of rotating machineinsulation [J]. IEEE Electrical Insulation Magazine,1996,12(4):23-27.
[73] G. C. Stone, V. Warren. Effect of manufacturer, winding age and insulation type on statorwinding partial discharge levels [J]. IEEE Electrical Insulation Magazine,2004,20(5):13-17.
[74] N. C. Sahoo, M. M. A. Salama, R. Bartnikas. Trends in partial discharge pattern classification:a survey [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2005,12(2):248-264.
[75] T. K. Saha,P. Purkait. Investigation of an expert system for the condition assessment oftransformer insulation based on dielectric response measurements [J]. IEEE Transactions onPower Delivery,2004,19(3):1127-1134.
[76] J. Blennow, C. Ekanayake, K. Walczak, B. A. Garcia. Field experiences with measurements ofdielectric response in frequency domain for power transformer diagnostics [J]. IEEETransactions on Power Delivery,2006,21(2):681-688.
[77] A. M. Emsley. Kinetics and mechanisms of degradation of cellulosic insulation in powertransformers [J]. Polymer Degradation and Stability,1994,44(3):343-349.
[78] X. Zou,T. Uesaka,N. Gurnagul. Prediction of paper permanence by accelerated aging I. Kineticanalysis of the aging process [J]. Cellulose,1996,3(1):243-267.
[79] D. M. Allan. Practical life-assessment technique for aged transformer insulation [J]. IEEProceedings-A: Physical Science,1993,140(5):404-408.
[80] P. J. Burton, M. Carballeira, C. W. Fuller, Application of liquid chromatography to the analysisof electrical insulating materials [C].CIGRE, Intern. Conf. Large High Voltage ElectricSystems, Paris, France,1988.12.
[81]薛辰东.用油中糠醛含量估计变压器绝缘老化故障[R].电力部电力科学研究院,1990.12.
[82] IEEE Std. C57.91-1995. IEEE Guide for Loading Mineral-Oil-Immersed Transformers [S].June14,1995.
[83] Load guide for oil-immersed power transformers [S]. IEC Std.354-1991-09, Sept.1991.
[84] PT Load Version6.1Users Manual: Power Transformer Loading Program [M], EPRI, PaloAlto, CA:2002.1007083.
[85]王有元,周婧婧,陈伟根,等.基于模糊决策的电力变压器风险评估方法[J].仪器仪表学报,2009,30(8):1662-1667.
[86]白翠粉,高文胜,丁登伟.利用小世界网络的电力变压器风险评估方法[J].高电压技术,2010,36(4):869-872.
[87] T. Hjartarson, B. Jesus, D. T. Hughes, et al. Development of health indices for asset conditionassessment[C]. Transmission and Distribution Conference and Exposition,2003,2:541-544.
[88] F. Backlund. Managing the introduction of RCM experiences from a Swedish hydropowercompany[C]. IEEE Power Engineering Society General Meeting.2005,6(3):2646-2648.
[89] G. M Hardwick. Reliability centered maintenance at Florida Power Corporation[C]. IEEEPower Engineering Society Summer Meeting,1999,6(2):1169-1170
[90]陈志林.以可靠性为中心的维修体系在大亚湾核电站的应用[J].中国设备工程,2006,6:13-14
[91]王爱华,李志刚.以可靠性为中心的检修在淄博供电公司的应用[J].山东电力技术,2006,4:11-13。
[92]杨杰以可靠性为中心的检修在电力系统的应用[J]山西电力技术,1999,10:34-36
[93]余绍峰,胡文堂,陈金法,等.输变电设备风险评估与维修决策[J],浙江电力,2009,3:1-5.
[94]许蜻,王晶,高峰等.电力设备状态检修技术研究综述[J].电网技术.2000(8):48-52.
[95] G. W. David. Life Cycle Costing-Theory Information Acquisition and Application[J].International Journal of Project Management,1997,15(6):335-344.
[96] M. J. Ki., P. Minjae, H. P. Dong. System Maintenance Cost Dependent on Life Cycle underRenewing Warranty Policy[J]. Reliability Engineering and System Safety,2010.02.
[97] I. A. Eleftherios, A. T. Marina, S. G. Pavlos. et al. Energy Efficient Transformer SelectionImplementing Life Cycle Cost and Environment Externalities[C].9th International Conference:Electrical and Power Quality and Utilisation,2007.
[98]何剑,程林,孙元章,等.条件相依的输变电设备短期可靠性模型[J].中国电机工程学报,2009,29(7):39-46.
[99] N. Julia, B. Lina. Maintenance Management of Wind Power Systems Using ConditionMonitoring Systems-Life Cycle Cost Analysis for Two Case Studies[J]. IEEE Translation onEnergy Conversion,2007.
[100]S. Khaled, Z. Tarek. Simulation as a Tool for Life Cycle Cost Analysis[C]. Proceedings of the2008Winter Simulation Conference.
[101]梅志农,袁思吟,韩天祥,李莉华.上海世博变电站工程中的LCC实践[J].上海电力,2009,(3):242-244.
[102]曾庆禹.变电站的寿命周期成本与新技术发展分析[J].中国电力,2000,33(12):35-38
[103]T. Shimakage, K. Wu, T. Kato, T. Okamoto, Y. Suzuoki. Life-Cycle-Cost Comparison ofDifferent Degradation Diagnosis Methods for Cables[J]. Electrical Insulation Materials,2005,3(6):737-740.
[104]赵宏,卢永平,马维清,张勇,杜永平.基于LCC的断路器可靠性分析[J].现代电力,2009,26(5):89-92.
[105]任玉珑,王建,牟刚,王恒炎.基于CA模型的电力设备全寿命周期成本研究[J].工业工程与管理,2008,(5):63-66.
[106]J. M. Brophy, L. J. Erickson. Cost-effectiveness of Drug-eluting Coronary Stents in Quebec[J].Canada, International Journal of Technology Assessment in Health Care,2005,21(3):326-333.
[107]W. E. Walker. POLSSS: Overview and Cost-effectiveness Analysis[J]. Safety Science.2000,35(1):105-121.
[108]李凡,姚光仑.最优线性分派法的防空武器系统费效分析[J].火力与指挥控制,2005,(30):95－97.
[109]A. Amirteimoori, S. Kordrostami, A. Rezaitabar. An Improvement to the Cost EfficiencyInterval: A DEA-based Approach[J]. Applied Mathematics and Computation,2006,181(1):775-781.
[110]GB/T7252-2001.变压器油中溶解气体分析和判断导则.2001.
[111]国家电网公司生产技术部.设备状态检修规章制度和技术标准汇编[S].北京:中国电力出版社,2008.
[112]孙永奎.基于支持向量机的模拟电路故障诊断方法研究[D].电子科学大学博士学位论文,2009.
[113]W. S. Sarle. Neural Network FAQ.[Online]. Available:ftp://ftp.sas.com/pub/neural/FAQ2.html.
[114]李烨.基于支持向量机的集成学习研究[D].上海交通大学博士学位论文,2007.
[115]S. S. Keerthi, C. J. Lin. Asymptotic behaviors of support vector machines with Gaussiankernel[J]. Neural Computation,2003,15(7):1667-1689.
[116]C. C. Chang, C. J. Lin. LIBSVM–A library for support vector machines.[Online]. Available:http://www.csie.ntu.edu.tw/~cjlin/libsvm.2001.
[117]E. Atashpaz-Gargari, C. Lucas. Imperialist competitive algorithm: An algorithmforoptimization inspired by imperialistic competition[C]. In: Evolutionary Computation.CEC2007. IEEE Congress on,2007:4661-4667.
[118]E. Atashpaz-Gargari, L. Caro. Designing an optimal PID controller using Colonial CompetitiveAlgorithm[C]. In: First Iranian Joint Congress on Intelligent and FuzzySystems,2007.
[119]E. Atashpaz-Gargari, F. Hashemzadeh, C. Lucas. Designing MIMO PIID controllerusingcolonial competitive algorithm: Applied to distillation column process[C]. In:EvolutionaryComputation, CEC.(IEEE World Congress on ComputationalIntelligence). IEEE Congress on,2008:1929-1934.
[120]EA. Gargari, F. Hashemzadeh, R. Rajabioun, C. Lucas. Colonial competitive algorithm:A novelapproach for PID controller design in MIMO distillation column process[J]. InternationalJournal of Intelligent Computing and Cybernetics,2008,1(3):337-355.
[121]R. Rajabioun, E. Atashpaz-Gargari, C. Lucas.(2008)Colonial Competitive Algorithm asa Toolfor Nash Equilibrium Point Achievement Computational Science and Its Applications–ICCSA2008.[C]. In: Gervasi O, Murgante B, Laganà A, Taniar D, Mun Y,Gavrilova M (eds), vol5073.Lecture Notes in Computer Science. Springer Berlin/Heidelberg:680-695.
[122]A. Khabbazi, EA. Gargari, C. Lucas. Imperialist competitive algorithm for minimum biterrorrate beamforming[J]. International Journal of Bio-Inspired Computation,2009,1(1/2):125-133.
[123]S. Forouharfard, M. Zandieh. An imperialist competitive algorithm to schedule ofreceiving andshipping trucks in cross-docking systems[J]. The International Journal ofAdvancedManufacturing Technology,2010,51(9):1179-1193.
[124]A. Kaveh, S. Talatahari. Optimum design of skeletal structures using imperialistcompetitivealgorithm[J]. Computers&Structures,2010,88(21-22):1220-1229.
[125]J.L. Lin, C.W. Cho, and H.C. Chuan, Imperialist Competitive Algorithms with PerturbedMoves for Global Optimization[J]. Applied Mechanics and Materials,2013,284-287:3135-3139.
[126]S. Nazari-Shirkouhi, H. Eivazy, R. Ghodsi, K. Rezaie, E. Atashpaz-Gargari. Solvingtheintegrated product mix-outsourcing problem using the Imperialist CompetitiveAlgorithm[J].Expert Systems with Applications,2010,37(12):7615-7626.
[127]F. Sarayloo, R. Tavakkoli-Moghaddam. Imperialistic Competitive Algorithm forSolving aDynamic Cell Formation Problem with Production Planning. In: Huang D-S,Zhao Z,Bevilacqua V, Figueroa J (eds) Advanced Intelligent Computing Theories andApplications, vol6215. Lecture Notes in Computer Science. Springer Berlin/Heidelberg,2010:266-276.
[128]M. H. Sayadnavard, AT. Haghighat, M. Abdechiri. Wireless sensor network localizationusingImperialist Competitive Algorithm[C]. In: Computer Science and InformationTechnology(ICCSIT),20103rd IEEE International Conference on,9-11July2010:818-822.
[129]M. Moghimi Hadji, B. Vahidi. A Solution to the Unit Commitment Problem Using ImperialisticCompetition Algorithm[J]. IEEE Transactions on Power Systems,2011,1(1):99.
[130]M. Bagher, M.Zandieh, H. Farsijani. Balancing of stochastic U-type assembly lines:animperialist competitive algorithm[J]. The International Journal of Advanced ManufacturingTechnology,2011,54:271-285.
[131] T. Niknam, Fard. E. aherian, N. Pourjafarian, A. Rousta. An efficient hybrid algorithmbasedon modified imperialist competitive algorithm and K-means for data clustering[J]. EngineeringApplications of Artificial Intelligence,2011,24(2):306-317.
[132]段华.支持向量机的增量学习算法研究[D].上海交通大学博士学位论文,2008.
[133]J. Weston, C. Watkins. Multi-class support vector machines[C]. Proc. ESANN99, M. Verleysen,Ed., Brussels, Belgium,1999.
[134]T. VAN. Gestel, J. A. K. Suykens, B. Baesens, et al. Benchmarking least squares support vectormachine classifiers[J]. Machine Learning,2004,54,(1):5-32.
[135]A. Mathur, G. M. Foody. Multiclass and binary SVM classification: Implications for trainingand classification users[J]. IEEE Geos. Remote Sens. Letters,2008,5,(2):241-245.
[136]A. Passerini, M. Pontil, P. Frasconi. New results on error correcting output codes of kernelmachines[J]. IEEE Trans. Neural Networks,2004,15,(1):45-54.
[137]C. W. Hsu, C. J. LIN. A comparison of methods for multiclass support vector machines[J].IEEE Trans. Neural Networks,2002,13,(2):415-425.
[138]T. G. Dietterich, G. Bakiri. Solving multiclass learning problems via error-correcting outputcodes[J]. Journal of Artificial Intelligence Research,1995,2:263-286.
[139]T. Van Gestel, J. A. K. Suykens, G. Lanckriet. Multiclass LS-SVMs: moderated outputs andcoding-decoding schemes[J]. Neural Processing Letters,2002,15(1):45-48.
[140]R. Liao, H. B. Zheng, et al. A multiclass SVM-based classifier for transformer fault diagnosisusing a particle swarm optimizer with time-varying acceleration coefficients[J]. EuropeanTransactions on Electrical Power,(Article first published online:10NOV2011,DOI:10.1002/etep.651).
[141]A. Frank, A. Asuncion. UCI machine learning repository.[Online]. Available:http://archive.ics.uci.edu/ml.2010.
[142]K. Meng, Z. Y. Dong, D. H. Wang, et al. A self-adaptive RBF neural network classifier fortransformer fault analysis[J]. IEEE Trans. Power Syst.,2010,25,(3):1350-1360.
[143]李德毅.不确定性人工智能[M].北京：国防工业出版社,2005.
[144]郑海平,孙才新,李俭,等.诊断电力变压器故障的一种灰色关联度分析模式及方法[J].中国电机工程学报,2001,21(10):106-109.
[145]秦昆,王佩.基于云变换的曲线拟合新方法[J].计算机工程与应用,2008,44(23):56-58.
[146]丁月华,文贵华,郭炜强.基于云X信息的逆向云新算法[J].系统仿真学报,2004,16(11)：2417-2420.
[147]冯兴杰,周谆. Apriori算法的改进[J].计算机工程,2005,31:172-173.
[148]李德毅,刘常昱.论正态云模型的普适性[J].中国工程科学,2004,6(8)：28-34.
[149]蒋嵘,李德毅,陈晖.基于云模型的时间序列预测[J].解放军理工大学学报,2000,1(5)：13-18.
[150]陈昊,李兵.云推理方法及其在预测中的应用[J].计算机科学,2011,38(7):209-211.
[151]J. B. Yang, M. G. Singh. An evidential reasoning approach for multiple-attribute decisionmaking with uncertainty[J]. IEEE Trans. Syst., Man, Cybern.,1994,24(1):1-18.
[152]IEEE Std.637-1985. IEEE Guide for the Reclamation of Insulating Oil and Criteria for Its Use.1985.
[153]IEEE Std. C57.125-1991. IEEE Guide for Failure Investigation, Documentation, and Analysisfor Power Transformers and Shunt Reactors.1991.
[154]IEEE Std. C57.106-2006. IEEE Guide for Acceptance and Maintenance of Insulating Oil inEquipment.2006.
[155]T. L. Saaty. The Analytic Hierarchy Process[M]. McGraw-Hill, New York,1980.
[156]梁梁,盛昭翰,徐南荣.一种改进的层次分析法[J].系统工程,1989,7(3):5-7.
[157]梁梁,余磊.对《一种改进的AHP法》的补注[J].系统工程,1991,9(3):64-65.
[158]Ruijin Liao, Yiyi Zhang, Lijun Yang, Hanbo Zheng, Xu She. A cloud and evidential reasoningintegrated model for insulation condition assessment of high voltage transformers[J].International Transactions on Electrical Energy Systems, Article first published online:23APR2013.
[159]张镱议,廖瑞金,杨丽君,郑含博,孙才新.基于云理论的电力变压器绝缘状态评估方法[J].电工技术学报,2012,05:13-20.
[160]刘常昱,李德毅,杜鹢,等.正态云模型的统计分析[J].信息与控制,2005,34(2):236-239.
[161]张峰,张鹏林,吕志勇,等.云模型在城镇空气质量评价中的应用[J].环境科学与技术,2009,32(6):160-164.
[162]W. H. Tang, K. Spurgeon, Q. H. Wu, Z. J. Richardson. An evidential reasoning approach totransformer condition assessments[J]. IEEE Trans. Power Del.,2004,19(4):1696-1703.
[163]龚本刚.基于证据理论的不完全信息多属性决策方法研究[D].中国科学技术大学博士学位论文,2007.
[164]肖明珠.基于证据理论的不确定性处理研究及其在测试中的应用[D].电子科技大学博士学位论文,2008.
[165]H.W. Guo, W.K. Shi, Y. Deng. Evaluating Sensor Reliability in Classification Problems Basedon Evidence Theory. Systems[J], IEEE Transactions on Man, and Cybernetics.2006,36,(5):970-981.
[166]Y. Deng, W.K. Shi, Z.F. Zhu, Q. Liu. Combining belief functions based on distance ofevidence[J]. Decision Support Systems.2004,38,(3):489-493.
[167]Y. Deng, D. Wang, Q. Liu, Y.J. Zhang. A new method to analyze evidence conflict[J]. ControlTheory&Applications.2011,6,6-13.
[168]廖玉祥.一种电力变压器运行状态综合评估模型的研究[D].重庆大学硕士学位论文,2006.
[169]廖瑞金,肖中男,巩晶,等.应用马尔科夫模型评估电力变压器可靠性[J].高电压技术，2010,36(2):322-328.
[170]Hu Ghes D, G. Dennis, J. Walker, et al. Condition based risk management (CBRM) enablingasset condition information to be central to corporate decision making[C]. Proceedings of the1st World Congress on Engineering Asset Management, July11-14,2006, Gold Coast,Australia：1212-1217.
[171]马志钦.变压器油纸绝缘的频域介电响应特性与绝缘状态评估方法研究[D].重庆大学,2012.
[172]杨丽君.变压器油纸绝缘老化特征量与寿命评估方法研究[D].重庆大学,2009.
[173]郝建.变压器油纸绝缘热老化的时频域介电和空间电荷特性研究[D].重庆大学,2012.
[174]朱恒宣.油浸式变压器绕组热点预测及光纤测温[D].河北工业大学,2011.
[175]陈培伟,陈涛.变压器绕组温度计的原理及其应用[J].华电技术,2008,10:14-15+21.
[176]黄勇.电力变压器故障的红外诊断技术应用研究[D].重庆大学,2001.
[177]J. Jalbert, M. C. Lessard, M. Ryadi."Cellulose Chemical Markers in Transformer OilInsulation Part1: Temperature Correction Factors", IEEE Transactions on Dielectrics andElectrical Insulation,2013,20(6):2287-2291.
[178]J.M.K.MacAlpine,张潮海.糠醛浓度判断变压器绝缘纸寿命的综述[J].高电压技术,2001,04:63-64+67.
[179]www.pecj.or.jp/japanese/report/2001report/2001.an1-1.pdf
[180]杨丽君,邓帮飞,廖瑞金,等.应用时–温–水分叠加方法改进油纸绝缘热老化寿命模型[J],中国电机工程学报,2011,31(31):196-203.
[181]Urzhumtsev, Y.S. Time-temperature superposition[J]. Review, Mechanics of CompositeMaterials,1975,11(1):57-72.
[182]L. Yang, R. Liao, and C. Sun. Influence of Natural Ester on Thermal Aging Characteristics ofOil-paper in Power Transformer[J]. European Transactions on Electrical Power,2010,20:1223-1236.
[183]刘玉仙.油纸绝缘变压器中水分的聚积及其对热老化寿命的影响[J].变压器,2004,41(2)：8-12.
[184]Shroff, D.H., and Stannett, A.W. A review of paper aging in power transformers[J]. IEEProceedings of generation, transmission and distribution,1985,132(6):312-319.
[185]Pahlavanpour, M. Martins and Eklund, Study of Moisture Equilibrium in Oil-Paper Systemwith Temperature Variation[C]. Proceedings of the7th International Conference on Propertiesand Applications of Dielectric Materials, June1-52003Nagoya,1124-1129.
[186]王有元.基于可靠性和风险评估的电力变压器状态维修决策方法研究[D].重庆大学,2008.
[187]帅军庆.资产全寿命周期管理理论、方法及应用[M]北京：中国电力出版社,2010.4.
[188]陈绍辉.基于全寿命周期成本的变电设备状态维修策略研究[D].华北电力大学,2012.
[189]王一,王慧芳,张亮,等.基于效用和成本的状态检修维修方式选择研究[J].电力系统保护与控制,2010,38(19):39-45.
[190]潘乐真.基于设备及电网风险综合评判的输变电设备状态检修决策优化[D].上海交通大学,2010.
[191]许珂.大型电力变压器故障实例统计分析[J].华章,2008,10：162-163.
[192]中华人民共和国国家统计局.2012年国内生产总值(GDP)初步核算情况http：//www.stats.gov.cn/tjfx/jdfx/t20130119_402867380.htm.北京,2013.
[193]中华人民共和国国家能源局.国家能源局发布2012年全社会用电量http：//www.nea.gov.cn/2013-01/14/c_132100340.htm.北京,2013.
[194]方大千.变压器速算速查手册[M].北京：中国水利水电出版社,2004.
[195]夏成军,邱桂华,黄冬燕,等.电力变压器全寿命周期成本模型及灵敏度分析[J].华东电力,2012,40(1):26-30.
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