Power grid automation system and equipment running state risk assessment algorithm

A technology for automatic system and equipment operation, applied in computing, instruments, data processing applications, etc., can solve problems such as manual judgment, a large number of manpower, complex relationships, etc., to achieve the effect of avoiding threshold errors

CN105654229AInactive Publication Date: 2016-06-08STATE GRID CORP OF CHINA +2
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2016-06-08
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention relates to a power grid automation system and equipment running state risk assessment algorithm. The algorithm comprises the following steps of 1.1 feature extraction based on a Relief algorithm: equipment is abnormal because of interaction of one factor or a plurality of factors of the equipment during an equipment operation process; and the feature extraction means that from a lot of information collected from the equipment, the factor influencing a type of abnormity is extracted and irrelevant factors are rejected so that latter data analysis is performed; 1.2 similar sample gathering based on kmeans algorithm: through the Relief algorithm in the step1.1, a feature index sequence influencing an equipment operation risk is acquired; and through the k-means algorithm, a threshold scope of each feature index under each risk grade is calculated. By using the algorithm, there are the following advantages that aiming at each equipment, a specific state analysis threshold knowledge database is set so that a threshold error caused by an extraneous environment and an equipment self condition is avoided; and accuracy of alarm and early warning is ensured.
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Description

technical field

[0001] The invention belongs to the technical field of power system dispatching automation, uses data mining algorithms to analyze the relationship between automation equipment operation data and defects, generates an expert database of safety thresholds for equipment operation status, and then monitors and analyzes the real-time and staged operation status of equipment, Early warning of potential dangers in equipment operation to reduce system failures. Background technique

[0002] With the increasing scale of the power grid, the safe and stable operation of the power grid is increasingly inseparable from the support of the automation system. The gradual expansion of the scale and coverage of the automation system also brings challenges to the daily operation and maintenance of automation professionals. How to efficiently and reasonably Controlling the systems under its jurisdiction is the key to automated operation and maintenance.

[0003] Automation equ...

Examples

Embodiment Construction

[0016] This program combines two data mining algorithms, Relief and kmeans, to analyze system information for the final warning threshold extraction.

[0017] 1. Relief algorithm

[0018] Function: The abnormality of the equipment is often caused by the interaction of one factor or multiple factors of the equipment during the operation of the equipment. From the numerous information collected by the equipment, the factors that affect this type of abnormality are extracted, and irrelevant factors are eliminated for subsequent data analysis. This is feature extraction. Relief is such an algorithm. The Relief algorithm was first proposed by Kira, and was initially limited to the classification of two types of data. The Relief algorithm is a feature weighting algorithm (Featureweighting algorithms), which assigns different weights to features according to the relevance of each feature and category, and features with weights less than a certain threshold will be removed. The cor...