Electric energy metering device fault analysis method based on big data mining and scene pre-judgment

Abstract

The invention discloses an electric energy metering device fault analysis method based on big data mining and scene pre-judgment, belonging to the monitoring field. The electric energy metering device fault analysis method comprises steps of calculating out a fault type of a secondary circuit of a watt hour meter, inferring relation coefficients between display electric quantities of the watt hour meter after various types of faults and the display electric quantity of the watt hour meter under a normal condition by targeting watt hour meters of two connection modes which include a three-phase four-wire mode and a three-phase three-wire mode, respectively calculating electric quantity imbalance rates corresponding to buses of a transformer station and performing determination according to electric quantity data of a bus balance daily statement, finding out a bus j corresponding to a failed watt hour meter, performing fault pre-judgment before going to side for checking, finding out potential faults and sorting the faults according to priorities, performing on site checking according to a pre-judgment result and finding out a final fault. The electric energy metering device fault analysis method of the invention carries out fault analysis of an electric energy metering device under a big data background, effectively solves a problem of influence on line loss statistics which is caused by electric energy metering device and improves efficiency and accuracy of fault analysis and checking of the electric energy metering device.

Description

technical field [0001] The invention belongs to the field of monitoring, in particular to an analysis and identification method for faults of electric energy metering devices. Background technique [0002] With the advancement of power system reform, effectively reducing the line loss rate has become the focus of work for power companies to improve their economic benefits. [0003] In order to do a good job in line loss management, relevant personnel need to collect a large amount of data from the field, and the main source of these data is the electric energy metering device. [0004] All the leakage and stealing electricity caused by the failure of the electric energy metering device will be counted in the line loss rate of the distribution network, resulting in abnormal line loss statistics. It can be seen that the accuracy of the measurement results of the electric energy metering device directly affects Statistical index of line loss rate. [0005] Therefore, timely a...

AI Technical Summary

Problems solved by technology

By carrying out analysis and research on the failure of electric energy metering devices under the background of big data, it can effectively solve the problem of the influence of electric energy metering devices on line loss statistics, reduce unnecessary electric energy losses, and promote the green development of the electric power industry to low energy consumption and high efficiency Mode change is also an effective way to deepen the construction of smart grid and promote the development of electric power big data management technology

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