T/ZSA 182-2023 Active

Scope: This document proposes technical requirements for applying big data analysis technology to conduct remote diagnosis of operational errors in electricity meters, including requirements for data sets, 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 currently in operation in power grids. Main technical content: Remote diagnosis of operational errors in electricity meters is primarily based on the law of conservation of energy and the topological relationship of substation lines, utilizing big data analysis technology to construct a model for analyzing operational errors in electricity meters. By timely collecting and storing real-time data from electricity meters, using the substation total meter as a standard device, and leveraging the synchronized frozen electricity data between the substation total meter and the calibrated electricity meters, an equation system is established and solved on the online electricity meter calibration platform to conduct "point-to-point" real-time calculation of operational errors in electricity meters, thereby achieving remote diagnosis of operational errors in electricity meters in real time. This document outlines the application process of big data analysis models in remote diagnosis of operational errors in electricity meters, specifies necessary technical content and performance requirements, and aims to improve the diagnostic efficiency and accuracy of operational errors in electricity meters. The document primarily includes requirements for data sets, construction of big data analysis models, model evaluation and monitoring, and operational error diagnosis. The document aims to provide technical guidance for remote diagnosis of operational errors in electricity meters and promote the develop