State Grid Zhenjiang Power Supply Company has successfully enhanced the efficiency and accuracy of fault diagnosis in its distribution network through the deployment of the self-developed “Autonomous Fault Diagnosis System for Distribution Network Disconnection and Phase Loss.” A recent example of its effectiveness occurred when a phase loss fault was detected between Poles 17 and 18 on the 10 kV Antou 292 line of the 110 kV Baitu Substation. Thanks to the rapid response enabled by the system, the entire process—from fault detection to resolution—took only 40 minutes, restoring normal power supply to 26 transformer areas that were affected by the incident.
Challenges of Traditional Fault Diagnosis Methods
Previously, diagnosing and resolving distribution network faults was a cumbersome and time-intensive process. When a fault occurred, dispatch operators had to manually notify line operation and maintenance personnel, who then needed to access multiple systems and go through complex queries to preliminarily determine the fault’s general scope. This initial step alone consumed significant time and resources before repair personnel could even be mobilized to physically inspect the site and locate the exact fault.
The difficulties were compounded during nighttime incidents when identifying concealed faults became particularly challenging. Traditional methods often relied on manual inspections, which not only delayed power restoration but also introduced additional risks, such as grounding faults and potential electrical hazards for passersby. The inefficiencies in fault detection and resolution not only affected power reliability but also increased operational costs for the utility company.
Revolutionizing Fault Diagnosis with Automation
Recognizing the limitations of traditional fault diagnosis methods, State Grid Zhenjiang Power Supply Company developed the “Autonomous Fault Diagnosis System for Distribution Network Disconnection and Phase Loss” to optimize fault detection, localization, and resolution. The system incorporates advanced data analytics and automation technologies to significantly reduce the time required to pinpoint the exact location of faults within the distribution network.
One of the system’s most significant advantages is its ability to detect and locate faults within just 5 minutes. This represents a substantial improvement compared to previous methods, which could take over 30 minutes or even hours in complex scenarios. The system achieves this through a multi-layered approach that includes:
- Real-Time Data Monitoring: The system continuously monitors the distribution network for any abnormalities, detecting irregularities in voltage, current, and other key parameters.
- Automated Data Screening: By setting predefined thresholds for abnormal data fluctuations, the system can automatically screen transformer areas experiencing irregularities, significantly reducing the need for manual intervention.
- Fault Correlation with Pole Numbers: The system automatically correlates the identified anomalies with the corresponding pole numbers, allowing for precise localization of the fault without requiring extensive on-site investigations.
- Instant Fault Notifications: As soon as a fault is detected, the system instantly sends notifications to operation and maintenance personnel. This real-time alert system enables teams to prepare necessary repair materials and deploy resources effectively, minimizing downtime.
Case Study: Successful Deployment and Impact
The recent resolution of the phase loss fault on the 10 kV Antou 292 line serves as a testament to the effectiveness of the new system. Upon detection of the fault, the system swiftly analyzed abnormal fluctuations and pinpointed the affected location between Poles 17 and 18. Within moments, maintenance personnel received automated alerts and were able to mobilize immediately, arriving at the site fully prepared with the necessary repair materials.
By leveraging the autonomous fault diagnosis capabilities, the entire process—from initial detection to full restoration of power—was completed in just 40 minutes. This marked a significant improvement over traditional fault-handling methods, which would have taken considerably longer, potentially leaving the affected areas without power for an extended duration.
Beyond just speed, the accuracy of fault detection also played a crucial role in enhancing overall operational efficiency. By eliminating the need for extensive manual inspections and guesswork, maintenance teams could directly focus on resolving the fault, reducing both the operational burden and the risk of prolonged outages.
Large-Scale Implementation Across Zhenjiang
Following the success of the initial deployment, the “Autonomous Fault Diagnosis System for Distribution Network Disconnection and Phase Loss” has now been widely implemented across Zhenjiang City. The system currently covers 29 substations and 374 distribution network lines, providing a city-wide infrastructure for intelligent fault management.
The widespread adoption of this system has led to notable improvements, including:
- Reduction in Fault Localization Time: The time required to locate disconnection faults has decreased from over 30 minutes to under 5 minutes, significantly accelerating power restoration efforts.
- Enhanced Reliability and Safety: By swiftly addressing faults and minimizing outage durations, the system has contributed to a safer and more stable power supply for residents and businesses.
- Optimized Resource Utilization: Maintenance personnel can now respond more efficiently, reducing the time spent on manual fault detection and focusing on effective repair strategies.
Future Prospects and Technological Advancements
As part of its ongoing commitment to innovation, State Grid Zhenjiang Power Supply Company plans to further enhance the capabilities of the autonomous fault diagnosis system. Future developments may include:
- Integration with AI and Machine Learning: By incorporating AI-driven predictive analytics, the system could anticipate potential faults before they occur, enabling preventive maintenance strategies.
- Expansion of Coverage: Efforts are underway to extend the system’s reach to additional substations and distribution networks, ensuring comprehensive fault diagnosis across an even larger service area.
- Enhanced User Interfaces and Mobile Applications: Providing maintenance teams with mobile-friendly platforms could further streamline fault resolution workflows, allowing for real-time monitoring and decision-making on the go.
The implementation of the “Autonomous Fault Diagnosis System for Distribution Network Disconnection and Phase Loss” marks a transformative step forward in power distribution management for State Grid Zhenjiang Power Supply Company. By leveraging advanced automation and real-time data analytics, the company has significantly improved the speed, accuracy, and efficiency of fault diagnosis and resolution.
With its ability to detect and locate faults within just minutes, the system not only enhances the reliability of the power supply but also reduces operational costs and improves overall safety. As further advancements are integrated into the system, the future of intelligent power distribution in Zhenjiang looks increasingly promising, setting a benchmark for other regions seeking to modernize their energy infrastructure.
Through continued innovation and technological upgrades, State Grid Zhenjiang Power Supply Company is demonstrating its commitment to delivering a smarter, more resilient, and customer-centric power distribution network.
