Power transformer defect online diagnosis method based on operation information

Abstract

The invention discloses a power transformer defect on-line diagnosis method using operation information, which comprises the following steps of: acquiring voltage and current data of each phase of a high-voltage side and a low-voltage side of a transformer within a period of time, and performing parameter identification on equivalent circuit parameters of the transformer by adopting a parameter identification algorithm; the method comprises the following steps: acquiring voltage and current data and temperature data of each phase of the high-voltage side and the low-voltage side of a transformer, automatically modeling, automatically learning, automatically training, generating a proper heat accumulation model, inputting voltage and current effective values of the high-voltage side and the low-voltage side of each phase and starting moment temperature in a period of time to the heat accumulation model, and outputting ending moment temperature by the heat accumulation model; according to the deviation between the actually measured temperature of the transformer and the temperature output by the heat accumulation model and the equivalent circuit parameter identification result of the transformer, the defect and fault type and degree of the transformer can be effectively judged, transformer defect online diagnosis based on comprehensive electric and non-electric operation parameters is realized, and the accuracy of defect and fault diagnosis is improved.

Description

technical field [0001] The invention relates to the field of electrical equipment, in particular to an online diagnosis method for power transformer defects using operating information. Background technique [0002] Power transformers are important equipment in substations. Realizing transformer defect diagnosis and health deterioration assessment is the key to preventing unexpected outages and realizing predictive maintenance. Solve the following problems in transformer defect diagnosis for a long time: [0003] 1) When the transformer is partially overheated due to partial discharge or other local insulation defects, the method of "measuring temperature and setting a fixed alarm temperature threshold" cannot issue an alarm in time; [0004] 2) When the load rate of the transformer is relatively low, the method of "measuring temperature and setting a fixed alarm temperature threshold" cannot detect abnormal problems in the cooling system in time, nor can it detect defects ...

AI Technical Summary

Problems solved by technology

[0003] 1) When the transformer is partially overheated due to partial discharge or other local insulation defects, the method of "measuring temperature and setting a fixed alarm temperature threshold" cannot issue an alarm in time;

[0004] 2) When the load rate of the transformer is relatively low, the method of "measuring temperature and setting a fixed alarm temperature threshold" cannot detect abnormal problems in the cooling system in time, nor can it detect defects such as short circuits between iron chips in time;

[0005] 3) Defects such as poor contact of the tap changer or inter-turn short circuit cannot be alarmed in time by the method of "measuring temperature and setting a fixed alarm temperature threshold";

[0006] 4) Partial discharge on-line monitoring and other methods can only solve the problem of partial discharge monitoring alone, and the accuracy of its diagnosis is related to many factors such as the installation position of the sensor;

[0007] 5) On-line analysis of oil chromatography can only explain the deterioration of oil in a single way

[0008] Existing transformer fault diagnosis methods often use a single method to judge the defect or fault degree of the transformer, which cannot fully reflect the defect or fault of the transformer, and may easily cause misjudgment

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