Intelligent electric energy meter calibration system multi-line collaborative scheduling method, device, equipment, medium and product

CN122414733APending Publication Date: 2026-07-17STATE GRID TIANJIN ELECTRIC POWER COMPANY +1

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
STATE GRID TIANJIN ELECTRIC POWER COMPANY
Filing Date
2026-06-15
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Traditional smart energy meter calibration systems often employ fixed rule scheduling or manual allocation methods, resulting in low efficiency in multi-production line collaboration. They fail to effectively combine digital twins to achieve real-time perception and simulation of production line status, leading to high energy consumption and low collaboration efficiency in the calibration system.

Method used

A globally schedulable matrix is ​​constructed. Based on atomic task characteristic data and static capability and dynamic status data of heterogeneous testing equipment, a digital twin model is established. Through the hierarchical enhancement of twin perception, the scheduling network generates task allocation and equipment power control decisions, thereby achieving efficient collaborative scheduling of multiple production lines.

Benefits of technology

It improves the accuracy of the matching relationship between verification tasks and heterogeneous verification equipment, ensures real-time synchronization between the virtual model and the physical verification production line, improves the accuracy and timeliness of scheduling decisions, reduces system energy consumption, and achieves efficient collaboration among multiple production lines.

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Abstract

本申请公开了一种智能电能表检定系统多产线协同调度方法、装置、设备、介质及产品,涉及电能表检定技术领域,该方法包括:获取智能电能表检定的原子任务特征数据、异构检定设备的静态能力数据与动态状态数据;基于原子任务特征数据、静态能力数据与动态状态数据,构建全局可调度矩阵;根据全局可调度矩阵、静态能力数据与动态状态数据,建立与物理检定产线实时同步的数字孪生模型,并基于数字孪生模型得到孪生体实时状态数据与仿真预测数据;将孪生体实时状态数据与仿真预测数据输入至预先训练好的孪生感知分层强化调度网络,得到检定任务执行指令与设备能效控制指令。该方法能够实现多产线的高效协同。
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