Method and device for predicting operation stage and service life of grounding grid of substation

A technology of substation grounding grid and operation stage, which is applied in the field of substation grounding grid operation phase and operation life prediction field, can solve the problems of inability to accurately grasp the substation grounding grid operation phase, waste of manpower and material resources, lack of scientificity, etc., to ensure diversity, The effect of good scalability and high clustering accuracy

Active Publication Date: 2019-03-22
STATE GRID HENAN ELECTRIC POWER ELECTRIC POWER SCI RES INST +3
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Problems solved by technology

[0005] In order to overcome the deficiencies in the prior art, the object of the present invention is to provide a substation grounding grid operation stage and operation life prediction method and device based on the improved random forest algorithm, aiming to solve the lack of scientific knowledge in the prior art when evaluating the operating status of the substation grounding grid. Sexuality, strong blindness, waste of manpower and material resources, unable to accurately grasp the operation stages of substation grounding grids of different ages and the problem of selecting the optimal measurement method in the corresponding stage

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  • Method and device for predicting operation stage and service life of grounding grid of substation

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specific Embodiment 1

[0062] Such as figure 1 and Figure 4 As shown, the embodiment of the present invention provides a substation grounding grid operation phase and operation life prediction method based on the improved random forest algorithm, including the following steps.

[0063] Step S1 is constructed to obtain various types of initial data and construct an original sample set. In this step, the various initial data may include maintenance results of the substation grounding grid, material of the grounding grid, soil condition data, and climate data. Among them, the maintenance results of the substation grounding grid, the material of the grounding grid, and the soil condition are obtained from the records of the substation, and the climate and other data are obtained from the regional meteorological department. data to form the original sample set. The embodiment of the present invention does not limit the total number of samples, which may be 120. The maintenance results of the substat...

specific Embodiment 2

[0089] Such as Figure 5 As shown, the embodiment of the present invention provides a substation grounding grid operation stage and operation life prediction device based on the improved random forest algorithm, including:

[0090] A construction module 201, configured to obtain various initial data and construct an original sample set;

[0091] The extraction module 202 is used to summarize and extract feature variables based on the characteristics of the original sample set;

[0092] The clustering module 203 is used to consider the existing data characteristics, and adopt the K-medoids method to cluster the original sample set;

[0093] The prediction module 204 is used to process various samples by using the random forest algorithm, extract training sets from various sample sets through bootstrap sampling technology, respectively establish classification regression trees and generate decision trees, and summarize and form random forest models; ground the substations to be...

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Abstract

The invention discloses a method and device for predicting the operation stage and service life of a grounding grid of a substation based on the improved random forest algorithm. The method includes the following steps that initial data is obtained, and an original sample set is constructed; based on the characteristics of an original sample set, characteristic variables are extracted; the K-medoids method is used for clustering of the original sample set; the random forest algorithm is used for processing various samples, and a random forest model is formed; the to-be-predicted substation grounding grid characteristic variables are loaded into a random forest model, and the operation time in a feature vector is changed to obtain the relationship of an evaluation result and the operation time, and the predicted result of an operation stage and operation life are deduced. The randomness of the original sample set classification in the random forest algorithm is improved; the forest model is generated on the basis of the random forest algorithm, the generalization error is controllable, and the clustering accuracy is high; various factors affecting the state of the grounding grid ofthe substation are taken into account comprehensively, and different operation stages are divided to identify the corrosion state of the grounding grid in the corresponding stage through combination of the most suitable grounding grid fault detection method.

Description

technical field [0001] The invention relates to the technical field of grounding grid performance evaluation, in particular to a substation grounding grid operation stage and operation life prediction method and device based on an improved random forest algorithm. Background technique [0002] With the rapid improvement of people's living standards in the new century, the demand for power is increasing, and the importance of substations carrying power transmission has become increasingly prominent. Among them, a good substation grounding grid is an important pillar for the safe and reliable operation of the substation. [0003] In order to ensure a good discharge capacity, the substation grounding grid is generally buried deep underground, which makes the grounding grid prone to corrosion and fracture. Affected by factors such as region, climate, and human factors, the time span for corrosion of substation grounding grids in various regions to affect the safe operation of s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/08G01R31/02G01N17/00
CPCG01N17/006G01R31/088G01R31/50
Inventor 陶亚光姚德贵刘尧吕中宾寇晓适李清杨晓辉卢明张博董曼玲谢凯刘阳姚伟张世尧
Owner STATE GRID HENAN ELECTRIC POWER ELECTRIC POWER SCI RES INST
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