Research on remote adjustment tech for industrial & commercial TOU meters via multi-mechanism synergy
Rundan Zhang, Shang Ying, Muxin Zhang · IET conference proceedings. · 2025
In the context of the “dual carbon” strategy and the construction of a new power system, precise implementation of time of use electricity prices is crucial for the allocation of power resources. The current average success rate of remote calibration of energy meters for industrial and commercial users is only 63.7%, which is difficult to meet the needs of dynamic electricity pricing policies. This study aims to address the low success rate of remote calibration of electric energy meters and the problem of system congestion. It innovatively proposes three core mechanisms: adaptive version calibration, Flink real-time stream processing, and intelligent negotiation of front-end machine clusters, and constructs a closed-loop optimization system of “data perception intelligent decision-making precise execution”. Through the three-level verification of “virtual simulation+sandbox testing+on-site verification” and the pilot practice of the Yangtze River Delta Industrial Park, the results show that the success rate of remote calibration has been increased to 93.1%, and the amount of manual on-site operations has been reduced by 81%; The daily processing task volume of the collection system has increased from 120000 to 350000, and the average processing delay of tasks has been reduced to 280ms. Four invention patents and three software copyrights have been developed and promoted in five provincial power grids, providing key technical support for the construction of new power systems. Later, it will expand to new load scenarios and deepen the research on edge computing cloud collaboration and federated learning fault prediction models.