T/IQA 21-2023 Active

Scope: This document proposes technical requirements for the remote diagnosis of operational errors in electricity meters using big data analysis technology, including requirements for data sets, the construction of big data analysis models, model evaluation and monitoring, and operational error diagnosis. This document is applicable to the online diagnosis of operational errors in single-phase and three-phase electronic AC electricity meters with voltages of 10 kV and below that are in operation in power grids. Main technical content: The remote diagnosis of operational errors in electricity meters is primarily based on the law of conservation of energy and the topological relationships of substation lines, using big data analysis technology to construct a model for analyzing the operational errors of electricity meters. By timely collecting and storing real-time data from electricity meters, taking the substation total meter as a standard device, and using the timed frozen electricity quantities of the substation total meter and the calibrated electricity meters, an equation system is established and solved on the online electricity meter calibration platform to perform "point-to-point" real-time operational error calculations for electricity meters, thereby achieving remote diagnosis of operational errors in electricity meters in real time. This document provides the technical process for applying big data analysis models in the remote diagnosis of operational errors in electricity meters, specifies the necessary technical content and performance requirements, and aims to improve the diagnostic efficiency and accuracy of operational errors in electricity meters. The document mainly includes requirements for data sets, the construction of big data analysis models, model evaluation and monitoring, and operational error diagnosis. The document aims to provide technical guidance for the remote diagnosis of operational errors in electricity meters and promote the