A Calculation Method of Transformer Insulating Oil Deterioration Failure Rate

Abstract

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 deterioration. 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 evaluation are processed and analyzed by using the theory of probabilistic fuzzy sets. A method for calculating the failure rate of transformer insulation oil degradation proposed by the present invention can evaluate the failure state of transformer insulation oil degradation, which reflects the uncertainty of the characteristic value of the transformer insulation oil degradation fault state, and provides a basis for the evaluation of the transformer insulation oil degradation fault state. Provide theoretical guidance and provide 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 deterioration. 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 va...

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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