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Transformer top oil temperature prediction method based on elastic network regression model

A technology of top oil temperature and regression model, applied in the field of transformers, can solve problems such as abnormal data and inability to obtain top oil temperature, and achieve the effect of convenient and accurate acquisition

Pending Publication Date: 2020-09-29
HANGZHOU ELECTRIC EQUIP MFG +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, sensors are mainly used to monitor oil temperature, but there are abnormal data due to sensor failure or the location of monitoring points.
In addition, for transformers that are already in operation and have no temperature sensor installed, the top oil temperature cannot be obtained

Method used

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  • Transformer top oil temperature prediction method based on elastic network regression model
  • Transformer top oil temperature prediction method based on elastic network regression model
  • Transformer top oil temperature prediction method based on elastic network regression model

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Embodiment Construction

[0040] The core of the present application is to provide a method for predicting the top layer oil temperature of a transformer based on an elastic network regression model, which can conveniently and accurately obtain the top layer oil temperature of the transformer. Another core of the present application is to provide a transformer top-layer oil temperature prediction device, equipment and computer-readable storage medium based on an elastic network regression model, all of which have the above-mentioned technical effects.

[0041] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments ...

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Abstract

The invention discloses a transformer top oil temperature prediction method based on an elastic network regression model. The method comprises the steps that monitoring data of a transformer is acquired, wherein the monitoring data comprises the top oil temperature of the transformer; a sample array is constructed according to the monitoring data, and the sample array is substituted into a presetelastic network regression model to determine a regression coefficient of the elastic network regression model; real-time monitoring data of the transformer is acquired, wherein the real-time monitoring data does not contain the top oil temperature of the transformer; and the real-time monitoring data is substituted into the elastic network regression model with the determined regression coefficient for data processing to obtain a predicted value of the top oil temperature of the transformer. The method can conveniently and accurately obtain the top oil temperature of the transformer. The invention also discloses a transformer top oil temperature prediction device and equipment based on an elastic network regression model, and a computer readable storage medium, which all have the above technical effects.

Description

technical field [0001] The present application relates to the technical field of transformers, in particular to a method for predicting oil temperature at the top of a transformer based on an elastic network regression model; it also relates to a device, equipment, and computer-readable storage medium for predicting oil temperature at the top of a transformer based on an elastic network regression model. Background technique [0002] The transformer is the core equipment of the substation, and the operation status of the transformer needs to be controlled in time so that the transformer can operate safely. The winding temperature of the transformer is an important indicator that affects the life of the transformer. Since the winding temperature is not easy to measure directly, the temperature of the top layer of the transformer is often monitored to indirectly reflect the internal winding temperature of the transformer. The winding temperature can also be calculated from the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/18G06K9/62
CPCG06F17/18G06F18/214Y04S10/50
Inventor 周广方郑丽娟彭团丰赵莉莉黄思琪
Owner HANGZHOU ELECTRIC EQUIP MFG