Transformer risk prediction method based on markov and entropy weight fuzzy comprehensive evaluation

Abstract

The invention relates to a transformer risk prediction method based on markov and entropy weight fuzzy comprehensive evaluation. The method comprises the following steps of: (1) establishing a transformer full-stage model based on a markov process; (2) acquiring a markov state transition diaphragm of a transformer at a running state according to the transformer full-stage model, and the probability of the transformer at full state as well as the fault frequency of each part of the transformer; (3) calculating the fault severity of each part in faults through an entropy weight fuzzy algorithm; and (4) determining the risk of each part of the transformer according to the fault frequency and the fault severity of each part. Compared with the prior art, the transformer risk prediction method based on markov and entropy weight fuzzy comprehensive evaluation provided by the invention has the advantages of high precision, high accuracy and the like.

Description

technical field [0001] The invention relates to a transformer risk assessment and prediction method, in particular to a transformer risk prediction method based on Markov and entropy weight fuzzy comprehensive evaluation. Background technique [0002] The power transformer is one of the important power transmission and transformation equipment in the power system. It is in a pivotal position in the power system. The safety and reliability of its operation is directly related to the safety of the power system. Once a large power transformer fails, the direct and indirect economic losses will be huge. With the rapid development of the power grid, more and more single high-voltage, large-capacity transformers are put into power grid operation. At the same time, transformer failures caused by factors such as manufacturing, transportation, installation and maintenance quality also seriously threaten the entire The safe operation of the power system, so how to improve the reliabi...

AI Technical Summary

Problems solved by technology

[0003] In recent years, condition-based maintenance has gradually entered the maintenance management of electric power enterprises, and the pertinence and scientificity of maintenance have been greatly enhanced. However, the previous maintenance decisions were mainly based on the state of the equipment itself, without considering the different impacts of equipment on the system and economical efficiency. The structure of the transformer is complex, and there are many failure modes. The current condition-based maintenance is not mature enough. It is urgent to introduce new theories to guide the condition-based maintenance of electrical equipment.

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