Clustering algorithm-based exceptional event analysis method for evaluating whole state of electric meter

Abstract

The invention discloses a clustering algorithm-based exceptional event analysis method for evaluating the whole state of an electric meter. The method comprises the steps of aiming at the abnormal users with overvoltage, overcurrent, wrong clock of the electric meter, undervoltage of the electric meter, overhigh temperature of the electric meter, opened cover of the electric meter, continuous exceeding on the upper limit of a load, voltage reverse phase sequence, current reverse phase sequence, inversed current, imbalanced voltage three phases, imbalanced current three phases and the like, the document information of the users are checked, and the users having documents with problems are filtered; for the users with the abnormity, the whole state of the electric meter is evaluated and analyzed by combining information such as marketing service metering fault, fault meter changing and information lack examining on site through the comprehensive analysis of the clustering algorithm according to multiple dimensions such as the manufacturer, the batch, the region, the type of the metering device, the voltage level, the user class and the line, a technical means and a reference basis are provided for whether an electric power company for on-site inspection needs to be performed and whether a shift plan needs to be made, and the method is accurate and has small errors.

Description

technical field [0001] The invention relates to the technical field of electricity marketing and metering in the electric power industry, in particular to a method for analyzing and evaluating the overall state of an electric energy meter based on a clustering algorithm. Background technique [0002] For the operation monitoring and status evaluation of electric energy meters, preventing measurement risks is an important part of the online measurement monitoring system. The online measurement monitoring system is based on the electricity information collection system, marketing business system, gateway electric energy system and marketing business system. The existing data mining and analysis system for electric energy meters cannot accurately and intuitively detect abnormalities and failures of metering devices and acquisition equipment, and needs to be improved. Contents of the invention [0003] The purpose of the present invention is to make up for the defects of the p...

AI Technical Summary

Problems solved by technology

[0002] For the operation monitoring and status evaluation of electric energy meters, preventing measurement risks is an important part of the online measurement monitoring system. The online measurement monitoring system is based on the electricity information collection system, marketing business system, gateway electric energy system and marketing business system. The existing data mining and analysis system for electric energy meters cannot accurately and intuitively detect abnormalities and failures of metering devices and acquisition equipment, and needs to be improved.

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