Power transformer fault prediction method and system driven by state holographic sensing data

Abstract

The invention discloses a state holographic perception data driven power transformer fault prediction method and system. The method comprises the following steps: establishing a historical fault data set of a transformer; the method comprises the following steps: collecting the concentration of gas dissolved in oil in the operation process of a transformer, environment meteorological data reflecting the state of the transformer and other operation data, forming an optimal data set through a sudden change point detection and phase-space reconstruction mode, and building a recent prediction SARIMA model of the concentration of the gas dissolved in the transformer oil; obtaining a prediction result of the concentration change of the dissolved gas in the recent oil of the transformer; based on the relationship between the concentration of the dissolved gas in the oil and other state quantities of the transformer, the concentration of the dissolved gas in the oil changing in real time is obtained; building a transformer fault diagnosis model based on a DBN network; and taking a prediction result of the change of the concentration of the dissolved gas in the oil recently or the concentration of the dissolved gas in the oil changing in real time as an input characteristic quantity of the transformer fault diagnosis model to realize transformer fault prediction. And comprehensive real-time analysis and auxiliary decision making of the operation risk level of the power grid transformer are realized.

Description

technical field [0001] The invention belongs to the technical field of state prediction and fault diagnosis of electric equipment, and in particular relates to a power transformer fault prediction method and system driven by state holographic perception data. Background technique [0002] In order to meet the needs of clean energy development and low-carbon transformation, a large number of new energy installed capacity will be integrated into the grid. This brings with it a greater challenge to the safety, stability and operation optimization of the power grid, especially the "double high" power system brings unprecedented challenges to the conventional prediction and dispatch control of the power grid operation situation. With the improvement of social construction requirements for the reliability of power systems, the capabilities of multi-dimensional detection, state prediction and system control of power systems need to be improved urgently. [0003] In terms of data p...

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Problems solved by technology

[0004] In terms of cost reduction, although power companies currently invest a lot of manpower, material resources, and financial resources in equipment operation and maintenance every year to ensure the safe operation of equipment, the traditional maintenance mode is not timely and targeted for power transformers with faults or defects , It is mandatory for power transformers without defects, and new faults are likely to occur, resulting in waste of resources. Therefore, the traditional maintenance mode has great limitations, and the cost lean management level needs to be improved

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