Intelligent electric energy meter operation error data statistical processing system and method

Abstract

The invention provides an intelligent electric energy meter operation error data statistical processing system and method. The method comprises steps of designing an error statistical end which is closely related to other parts of a system based on an error statistical demand, and providing a sample-tabulated error statistical result through the connection of a feedback receiving end and a systemdecision-making monitoring end; the online monitoring and data acquisition system and method based on the distributed acquisition system, the transformer area configuration information and the same type of reference information are designed; meanwhile, considering that errors of the intelligent electric energy meter may come from measurement errors, light-load errors influenced by creeping performance, sampling errors of a sampling circuit, attribution errors and the like, error statistics convenient for UI display and system management is realized by performing normalized configuration on ternary verification information; and convenient system monitoring is realized based on multi-dimensional underlying monitoring parameters.

Description

technical field [0001] The invention belongs to the field of information technology of a new generation of intelligent internet of things, and in particular relates to a system and method for statistically processing error data of an intelligent electric energy meter. Background technique [0002] The error is the measured magnitude minus the reference magnitude. The measured value is referred to as the measured value, which represents the value of the measurement result. The error of electric energy measuring instruments under specified working conditions. The allowable basic error limit is referred to as the basic error limit. Working conditions refer to the verification working conditions stipulated in the national verification regulations. The basic error of the electric energy meter is stipulated by the relative percentage error, which is determined as follows: Relative error = ((measured result (indication) - measured true value) / measured true value) * 100% Since th...

AI Technical Summary

Problems solved by technology

The smart energy meter itself has a high technical level and is relatively less likely to be damaged. However, in practical applications, it is found that the smart energy meter still has error problems, which affects the accuracy of the application and brings losses. The performance of the smart energy meter, Statistics and monitoring of status, operating parameters and dynamic errors have become an important part of smart grid management, and put forward higher requirements for the statistics and monitoring of operating error data of smart energy meters

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