A method for predicting the temperature rise of transformer hot spots by comparing optical fiber temperature measurement

Abstract

The invention discloses a transformer hot spot temperature rise prediction method for comparing optical fiber temperature measurement, which comprises the following steps: obtaining the measured hot spot temperature, top layer oil temperature, ambient temperature and load current data of an oil-immersed transformer equipped with optical fiber temperature measurement equipment; obtaining the measured hot spot temperature, ambient temperature and load current data of an oil-immersed transformer installed with optical fiber temperature measurement equipment; Setting up the basic frame of the hotspot temperature rise prediction model; dividing The measured data into training set and prediction set after being processed. Adopting Genetic Programming (GA) to model the data of training set, andsetting up an explicit model for predicting the temperature rise of hot spots. Inputting the data of prediction set into the prediction model to predict the temperature rise of transformer hot spots.The invention has the beneficial effects that an explicit hot spot temperature rise prediction model is finally established, and the mechanism of the hot spot temperature rise dynamic change with theload can be intuitively disclosed; With strong generalization performance, it can realize batch prediction and on-line monitoring of hot spot temperature rise of oil-immersed transformers with the same capacity in power system.

Description

technical field [0001] The invention relates to the field of electrical insulation on-line monitoring and fault diagnosis, in particular to a method for predicting temperature rise of transformer hot spots by comparing optical fiber temperature measurement. Background technique [0002] Oil-immersed transformer is the core equipment of the power system, and its efficient and safe operation plays a vital role in the operation and development of the power industry. The working life of a transformer depends on the internal insulation performance, and thermal aging is the main factor affecting the deterioration of its insulation performance. Through the prediction of hot spot temperature rise of oil-immersed transformer, the maximum temperature of winding can be directly determined, and the internal thermal state of transformer can be known to judge whether it is overheated; therefore, accurate prediction of hot spot temperature rise of oil-immersed transformer is the basis of l...

AI Technical Summary

Problems solved by technology

However, the fiber optic sensor is very fragile, and it is easy to be damaged by bending or mechanical stress during installation; the insulation layer at the installation place is relatively weak, and the overall insulation of the winding will suffer a certain degree of damage, and the operation and maintenance are difficult and costly; To sum up, it is difficult to widely apply the method of monitoring the temperature rise of hot spots by using the optical fiber temperature measurement system

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