State Grid Zhenjiang Power Supply Company's smart diagnostics speeds up fault resolution times

An intelligent diagnostics system installed in the city of Zhenjiang, Jiangsu province, earlier this year has vastly increased efficiency in the identification and resolution of electrical faults across the city.

Installed by State Grid Zhenjiang Power Supply Company, the Intelligent Pulse Diagnostician system has handled so far some 3,000 collected faults in the Zhenjiang area, preemptively identified 83 percent of potential fault points, reduced the meter replacement error rate by 45 percent, shortened repair time by 65 percent, and cumulatively reduced user power outage duration by approximately 1,200 hours.

At 7:45 am on May 6, the manager of State Grid Zhenjiang Power Supply Company's power distribution station received a text message from the system.

"There are five abnormal electricity meter data in your jurisdiction today. The system determines the fault type as a trip in the agricultural line. It is recommended to troubleshoot from this end, and the recommended repair method is to supply power from the agricultural main switch," the message said.

Upon receiving the message, the station manager immediately rectified the issue with tools and completed the fault repair in just 20 minutes.

In the past, when there were electricity meter problems, it took an average of about 20 minutes for staff members to locate a single faulty electricity meter. Lacking communication signals and user type associations, they could only analyze basic parameters such as voltage and current, which could easily lead to misjudgments and affect power supply reliability.

The Intelligent Pulse Diagnostician system which is now operational, automatically scans 590,000 smart meters in the city at 8 am daily. It can analyze 128 feature values, such as communication signals and current curves, providing a diagnostic service for the meters similar to an experienced doctor. When abnormal electricity meter data is detected, the system can complete fault diagnosis within five minutes and then swiftly pinpoint the fault location and accurately push repair recommendations to the station manager's mobile phone.