XGBoost-based electric power secondary equipment defect degree evaluation method

A secondary equipment and defect technology, applied in the field of evaluation of the defect degree of power secondary equipment based on XGBoost, can solve problems such as low efficiency and error-prone

Inactive Publication Date: 2020-02-25
ELECTRIC POWER SCI RES INST OF STATE GRID XINJIANG ELECTRIC POWER +5
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  • Abstract
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  • Application Information

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Problems solved by technology

[0005] Purpose of the invention: Aiming at the problem that secondary equipment operation and maintenance personnel in the power system are prone to make mistakes and have low effic

Method used

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  • XGBoost-based electric power secondary equipment defect degree evaluation method
  • XGBoost-based electric power secondary equipment defect degree evaluation method
  • XGBoost-based electric power secondary equipment defect degree evaluation method

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Embodiment Construction

[0031] In order to describe the technical solution disclosed in the present invention in detail, further elaboration will be made below in conjunction with the accompanying drawings and specific embodiments.

[0032] Specifically, take the secondary equipment defect record data of a power plant from 2016 to 2018 as an example, with a total of 556 typical defect information. Among them: 147 cases of general defects, 256 cases of serious defects, and 153 cases of crisis defects. The data is randomly divided into training set and test set according to the ratio of 4:1.

[0033] Table 1 Specific distribution of sample data

[0034]

[0035] like figure 1 As shown, the method for evaluating the defect degree of power system secondary equipment based on the Apriori-XGBoost algorithm of the present invention, the specific implementation steps are as follows:

[0036] Step 1. Data collection

[0037] Collect historical defect data of secondary equipment through the power grid p...

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Abstract

The invention discloses an XGBoost-based electric power secondary equipment defect degree evaluation method, which comprises the following steps of: firstly, acquiring and arranging related defect data of electric power system secondary equipment, and performing a series of preprocessing work such as duplicate removal, abnormal value filtration, missing value removal and the like on the acquired historical defect data of the electric power system secondary equipment; then carrying out association rule mining on the processed data based on an Apriori algorithm; screening out features having strong association rules with the defect degree of the secondary equipment of the power system to establish a feature index set, performing feature and label coding on index data, and after data grouping, performing training and parameter optimization on an XGBoost model by utilizing data of a training set and a test set respectively; and finally, achieving accurate classification of the defects of the secondary equipment of the power system by using the trained classification model. Maintenance personnel can be well assisted in maintenance and management of the equipment.

Description

technical field [0001] The invention belongs to the state evaluation and defect classification technology of electric equipment, and in particular relates to an XGBoost-based evaluation method for the defect degree of electric secondary equipment. Background technique [0002] The secondary equipment of the power system is one of the key equipment for the safe and stable operation of the smart substation, and its operating status is related to the reliable power supply of the power system. In recent years, with the rapid development of science and technology, the scale of the power system has continued to expand, and the number of secondary equipment in the power system has also grown by leaps and bounds. Personnel have brought a considerable workload, and at the same time brought risks to the operation of the power system. The operation, maintenance and control level of secondary equipment needs to be improved urgently. [0003] The defect rate of secondary equipment is in...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06Q10/06G06Q50/06
CPCG06Q10/0639G06Q50/06G06F18/2148G06F18/24G06F18/10
Inventor 南东亮王开科王维庆孙永辉于永军魏伟吴杰杨飞王晓飞冯小萍赵启周杰张路武家辉田景辅周勇彭寅章陈凯
Owner ELECTRIC POWER SCI RES INST OF STATE GRID XINJIANG ELECTRIC POWER
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