Method for calculating failure rate of insulation oil degradation of transformer

Abstract

The invention relates to the field of power systems and automation thereof, in particular to a method for calculating the failure rate of insulation oil degradation of a transformer. Aiming at the problem of how to deal with the big data of insulation oil deterioration failure state evaluation of the transformer, which involves many kinds, large quantity and complex interrelation, the method adopts the data clustering principle to process and analyze the big data on the basis of establishing a big database. For parameters of the random and fuzzy uncertainties involved in the evaluation of theinsulation oil deterioration failure state of the transformer, the theory of probabilistic fuzzy sets is used to process and analyze the parameters. The method for calculating the failure rate of insulation oil deterioration of the transformer may evaluate the insulation oil degradation failure state of the transformer, reflects the uncertainty of eigenvalues of the insulation oil degradation failure state of the transformer, provides theoretical guidance for insulation oil degradation failure state evaluation, and provides a necessary technical support for distribution network operation and maintenance.

Description

technical field [0001] The invention relates to the field of electric power system and automation thereof, in particular to a method for calculating the failure rate of transformer insulation oil degradation. Background technique [0002] There are a large number of transformers, and there will be different degrees of deterioration, deterioration, and defects, which are familial and concealed, and it is difficult to detect and evaluate them in time. Due to the great differences in the operating years, environment, maintenance, etc. and the influence of many factors, the difficulty and complexity of the evaluation of the deterioration state of the insulating oil in transformer operation are increased, and it cannot meet the higher requirements of precise and intelligent evaluation. [0003] Oil dielectric loss, water content in oil, gas content in oil, oil breakdown voltage, oil volume resistivity, oil conductivity, acid value in oil, breakdown voltage of oil, total acid valu...

AI Technical Summary

Problems solved by technology

Aiming at how to deal with the big data problems involving many types, large quantities, and complex interrelationships involved in the assessment of transformer insulation oil degradation fault status, the data clustering principle is used to process and analyze big data on the basis of establishing a large database; for transformer insulation oil degradation The random and fuzzy uncertain parameters involved in fault state assessment are processed and analyzed using the theory of probabilistic fuzzy sets

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