Research on the Location of Influencing Factors and Quality Early Warning of Energy Meter Faults Based on Block Chain Technology

The fault warning is critical in power fault detection in smart grid, however it has an issue with erroneous performance positioning. The typical Side-by-side comparison method is unable to address the fault location and quality early warning in smart grid power fault detection issue in power fault detection in smart grid, and the result is insufficient. As a result, a Block chain technology-based research on the location of influencing factors and quality early warning of energy meter faults is provided, and the research on the location of influencing factors and quality early warning of energy meter faults is assessed. To begin, the current overload theory is used to discover the influencing elements, and the indicators are split based on the fault warning's needs to decrease interference factors in the fault warning. The current overload theory is then used to create a Block chain technology fault warning scheme, and the outcomes of the fault warning are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Block chain technology outperforms the standard Side-by-side comparison method in terms of fault warning accuracy and time of influencing variables.