Advertisement

Dealing with Uncertainty for Dissolved Gas Analysis

  • W. H. Tang
  • Q. H. Wu
Chapter
Part of the Power Systems book series (POWSYS)

Abstract

This chapter presents three approaches to tackling uncertainties occurring in transformer condition assessment, including the ER approach, the hybrid FL and ER approach and the BN approach. Firstly, the methodology of transferring a transformer condition assessment problem into an MADM solution under an ER framework is presented. Three examples for performing transformer condition assessment, using the ER approach, are then illustrated highlighting the potential of the ER approach. The second part of this chapter employs a hybrid approach to the analysis of DGA data based upon several traditional DGA methods. Ideas adapted from the FL theory are applied to soften fault decision boundaries used by the traditional DGA methods. These diagnoses are then considered as pieces of evidence ascertaining to conditions of transformers, which are aggregated using an ER algorithm. The third part is concerned with a BN approach to processing dissolved gases. The methodology of mapping the knowledge in the DGA domain into a BN is described. Finally, an applicable solution to tackle the cases which are not identifiable by the IEEE and IEC code scheme is discussed using the BN approach.

Keywords

Fault Diagnosis Fault Type Preference Degree Basic Probability Assignment Transformer Fault 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Mollmann A, Pahlavanpour B (1999) New guidelines for interpretation of dissolved gas analysis in oil-filled transformers. Electra, CIGRE France 186:30–51Google Scholar
  2. 2.
    International Electrotechnical Commission (1993) IEC600762-power transformers—part 2: temperature rise. International Electrotechnical Commission Standard, GenevaGoogle Scholar
  3. 3.
    International Electrotechnical Commission (1978) IEC60559: interpretation of the analysis of gases in transformers and other oil-filled electrical equipment in service. International Electrotechnical Commission Standard, GenevaGoogle Scholar
  4. 4.
    The Institute of Electrical and Electronics Engineers (1994) Transformers Committee of the IEEE Power Engineering Society, IEEE guide for the interpretation of gases generated in oil immersed transformers, IEEE Std. C57.104-1991. The Institute of Electrical and Electronics Engineers, Inc., New YorkGoogle Scholar
  5. 5.
    Saaty TL, Vargas LG (1988) The analytic hierarchy process, RWS Publications, Pittsburgh, pp 1–24Google Scholar
  6. 6.
    Rogers RR (1978) IEEE and IEC codes to interpret incipient faults in transformers using gas in oil analysis. IEEE Trans Electr Insul 13(5):348–354CrossRefGoogle Scholar
  7. 7.
    Yang JB, Singh MG (1994) An evidential reasoning approach for multiple attribute decision making with uncertainty. IEEE Trans Syst Man Cybern 24(1):1–18CrossRefGoogle Scholar
  8. 8.
    Yang JB, Xu DL (2002) On the evidential reasoning algorithm for multiple attribute decision making under uncertainty. IEEE Trans Syst Man Cybern A Syst Hum 32(3):289–304CrossRefGoogle Scholar
  9. 9.
    Lin CE, Ling JM, Huang CL (1993) An expert system for transformer fault diagnosis and maintenance using dissolved gas analysis. IEEE Trans Power Deliv 8(1):231–238CrossRefGoogle Scholar
  10. 10.
    Zaman MR (1998) Experimental testing of the artificial neural network based protection of power transformers. IEEE Trans Power Deliv 13(2):510–517CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited  2011

Authors and Affiliations

  1. 1.Department of Electrical Engineering and ElectronicsThe University of LiverpoolLiverpoolUK

Personalised recommendations