Short-term prediction method and prediction system for top oil temperature of distribution transformer

A distribution transformer and top oil temperature technology, applied in the field of substations, can solve the problems of unguaranteed prediction effect, time-consuming and labor-consuming, and inability to guarantee prediction accuracy, etc., to overcome time-consuming and labor-intensive, improve accuracy, and avoid unsatisfactory prediction results Effect

Pending Publication Date: 2022-02-18
STATE GRID HUNAN ELECTRIC POWER +2
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the existing distribution transformer top layer oil temperature prediction model, the prediction model based on the finite volume method and the finite element method needs the data of various static and physical indicators of the transformer as support and the calculation is time-consuming; the differential t

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Short-term prediction method and prediction system for top oil temperature of distribution transformer
  • Short-term prediction method and prediction system for top oil temperature of distribution transformer
  • Short-term prediction method and prediction system for top oil temperature of distribution transformer

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0096] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0097] Such as figure 1 As shown, the short-term prediction method for the top layer oil temperature of the distribution transformer according to the embodiment of the present invention, the specific implementation steps are as follows:

[0098] S1: First select a specific model and type of distribution transformer in a certain area, install a top layer oil temperature sensor for it, collect historical data of distribution transformer top layer oil temperature, process it into time series data, and select a certain proportion as training data;

[0099] S2: Initialize various parameters in the ISSA algorithm, including sparrow population m, sparrow position dimension n, discoverer ratio PD, scout ratio SD, maximum number of iterations N, warning threshold ST;

[0100] S3: Input the sparrow population m and the sparrow position dimension n into ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a short-term prediction method for the top oil temperature of a distribution transformer, and the method comprises the steps: S1, obtaining the historical data of the top oil temperature of the distribution transformer, and processing the historical data into time series data; S2, initializing various parameters in an ISSA algorithm; S3, inputting the number m of the sparrow populations and the dimension n of the position of the sparrow into a one-dimensional composite chaotic mapping model (SPM) to generate an initial sparrow population of an ISSA algorithm; S4, substituting the hyper-parameter value represented by the position of each sparrow into the double-layer LSTM model, and training the double-layer LSTM model after normalization processing in combination with the training data divided in the step S1; S5, determining a discoverer, a follower and a reconnaissitor; S6, updating the position of the optimal sparrow; S7, judging whether an iteration ending requirement is met or not; and S8, inputting the top oil temperature time sequence data into the model to obtain a prediction result of the top oil temperature. The method has the advantages of high prediction precision and the like.

Description

technical field [0001] The invention mainly relates to the technical field of substations, in particular to a short-term prediction method and a prediction system for the top layer oil temperature of a distribution transformer. Background technique [0002] With the development of power technology, the safe and stable operation of power transformers is a necessary condition to ensure the reliability and economy of modern power systems. The insulation damage and service life reduction caused by the temperature limit of the transformer is one of the important factors affecting the load capacity of the power transformer. Therefore, monitoring the internal temperature of the power transformer is an effective method to judge the real-time operation status of the transformer. The hot spot temperature of the transformer winding and the top layer oil temperature are important indicators to measure the internal thermal state of the transformer. Due to the immature development of meas...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F30/27G06N3/00G06N3/04G06N3/08G06N7/08G06F111/08G06F119/08
CPCG06F30/27G06N3/006G06N3/084G06N7/08G06F2111/08G06F2119/08G06N3/044
Inventor 邓威吴潮刘奕罗威成罗冠儒任磊游金梁康童刘绚
Owner STATE GRID HUNAN ELECTRIC POWER
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products