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A Condition Assessment Model of Oil-immersed Transformers Using Cloud and Matter Element Integrated Method

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Warianty tytułu
PL
Ocena stanu technicznego transformatora olejowego na podstawie modelu szacunkowego – wykorzystanie metod elementów chmury i materii
Języki publikacji
EN
Abstrakty
EN
High voltage oil-immersed transformers are the most important components in the power system. If there is a potential fault in the transformer it may cause a power failure even a catastrophe. Therefore, it is important to assess the condition of the transformer accurately and to make some relative maintenance to minimize the risk of premature failure. However, condition assessment of transformers can be considered as a multiple-attribute decision-making (MADM) problem which is full of uncertain, fuzzy and randomness information. Aiming at this intricate problem, this paper presents a cloud and matter element integrated approach for assessing the condition of transformers. An assessing index system is established, which includes dissolved gas analysis (DGA), electrical testing and oil testing. An integrated model based on matter element approach and cloud approach is applied to assess the condition of the transformer. Cases study show that the proposed approach is practical and effective. The assessing result can be regarded as a useful suggestion to condition based maintenance of high voltage oil-immersed transformers.
PL
W artykule przedstawiono metodę oceny stanu technicznego transformatora olejowego, opartą na analizie elementów chmury oraz tzw. Matter-Element Analysis. Opracowany został zintegrowany model oraz wskaźnik szacujący stan transformatora, uwzględniający czynniki takie jak: analiza rozpuszczonych gazów (DGA), testy elektryczne i olejowe. Przeprowadzone badania potwierdziły skuteczność metody.
Rocznik
Strony
142--146
Opis fizyczny
Bibliogr. 23 poz., rys., tab., wykr.
Twórcy
autor
  • State Key Laboratory of Power Transmission Equipment & System Security and New Technology, University of Chongqing
autor
  • State Key Laboratory of Power Transmission Equipment & System Security and New Technology, University of Chongqing
autor
  • Henan Electric Power Research Institute
autor
  • State Key Laboratory of Power Transmission Equipment & System Security and New Technology, University of Chongqing
autor
  • State Key Laboratory of Power Transmission Equipment & System Security and New Technology, University of Chongqing
autor
  • State Key Laboratory of Power Transmission Equipment & System Security and New Technology, University of Chongqing
Bibliografia
  • [1] Wang M., Vandermaar A.J., Srivastava K.D., Review of condition assessment of power transformers in service, IEEE Elect. Insul. Mag., 18(2002), No. 6, 12–25
  • [2] Singh J., Sood Y.R., Jarial R.K., Verma P., Condition monitoring of power transformers—bibliography survey, IEEE Elect. Insul. Mag. 24(2008), No. 3, 11–25
  • [3] Muthanna K.T., Sarkar A., Das K., Waldner K., Transformer insulation life assessment, IEEE Trans. Power Del., 21(2006), No. 1,150–156
  • [4] James R.E., Su Q., Condition assessment of high voltage insulation in power system equipment, The Institution of Engineering and Technology: London, 2008
  • [5] Zhang M., Li K., Tian H.X., Multiple SVMs Modelling Method for Fault Diagnosis of Power Transformers, Przegląd Elektrotechniczny, 88(2012), No.7, 232-234
  • [6] Szczepaniak P.S., Klosinski, M., Maximal margin classifiers applied to DGA-based diagnosis of power transformers, Przegląd Elektrotechniczny, 88(2012),No. 2,100-104
  • [7] Piotrowski T., Application of ANN for the diagnosis of transformers based on the analysis of gases dissolved in oil, Przegląd Elektrotechniczny, 86(2010),No.11,158-161
  • [8] Walczak, K., Pruchnicki M., Przybylek, P., Result interpretation of dissolved gas in oil analysis using artificial neuronal network in aspect of power transformer state assessment, Przegląd Elektrotechniczny, 86(2010), No.11, 275-278
  • [9] Piotrowski, T., Ratio methods used in the diagnosis of gases dissolved in transformer oil, 10th International School on Nonsinusoidal Currents and Compensation, Katowice, JUN, 2010, Przegląd Elektrotechniczny, 86(2010), No.6, 175-178
  • [10] Fei S.W., Zhang X.B., Fault diagnosis of power transformer based on support vector machine with genetic algorithm, Expert Systems with Applications, 36(2009), No. 8, 11352–11357
  • [11] Ji S.Q., Luo Y.F., Ji H.Y., Application of Time Series Used on Recognition of Partial Discharge in Oil-Paper Insulation, Przegląd Elektrotechniczny, 88(2012), No.5B, 202-205
  • [12] Liao R.J., Wang K., Liu L., Investigation on Chaotic Characteristic of PD Magnitude Series during Propagation of Electrical tree in XLPE Power Cables, Przegląd Elektrotechniczny, 88(2012), No.5B, 213-217
  • [13] Liao R.J., Zheng, H.B., Grzybowski, S. et al., An Integrated Decision-Making Model for Condition Assessment of Power Transformers Using Fuzzy Approach and Evidential Reasoning, IEEE Trans. Power Del., 26(2011), No. 2, 1111-1118
  • [14] Tang W.H., Spurgeon K., Wu Q. H., Richardson, Z.J., An evidential reasoning approach to transformer condition assessments, IEEE Trans. Power Del., 19(2004), No. 4, 1696–1703
  • [15] IEEE Guide for Acceptance and Maintenance of Insulating Oil in Equipment, IEEE Std.C57.106–2006, IEEE: New York, NY, USA, 2007
  • [16] Regulations of Condition-Based Maintenance & Test for Electric Equipment; China State Grid Corporation standard, Q/GDW 168–2008, China Electric Power Press: Beijing, China, 2008.
  • [17] IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers, IEEE Std.C57.104–2008, IEEE: New York, NY, USA, 2009
  • [18] Li D., Liu C., Gan W., A New Cognitive Model: Cloud Model, Int. J. Intell. Syst., 24(2009), No. 3, 357–375
  • [19] Hu S., Li D., Liu Y., Li D., Land Evaluation Model Integrated Fuzziness and Randomness, ITESS: 2008 Proceedings Of Information Technology and Environmental System Sciences, 2(2008), 793-798
  • [20] Meng X.Y., Z G.W., K J.C., A New Subjective Trust Model Based on Cloud Model, Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control,ICNSC, 2008,1125–1130
  • [21] Saaty T.L., The Analytic Hierarchy Process, New York: McGraw-Hill, 1980
  • [22] Cai W., The extension set and incompatibility problem, Scientific Exploration, 1(1983), 81– 93
  • [23] Cai W., Extension set, fuzzy set and classical set, Proc. First Congress Int, Fuzzy Syst, Assoc, 1985
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8113745b-d178-46f7-92d3-0a9b8796b9f5
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