Author
Listed:
- Yongxiao Li
(School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)
- Zaheer Ul Hassan
(School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)
- Haresh Kumar Sootahar
(School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)
- Touseef Hussain
(School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)
- Kamlesh Kumar Soothar
(School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)
- Zulfiqar Ali Bhutto
(School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)
Abstract
Efficient decentralized power management is crucial for enhancing the reliability, resilience, responsiveness, and sustainability of secondary power distribution systems, thereby preventing major power outages and providing rapid responses. However, existing secondary power distribution networks are prone to failures, thus compromising their operational trustworthiness and efficiency. This work proposes an intelligent, decentralized control system with distributed processing capabilities. The proposed system is designed to automate fault detection and rectification along with optimized power management at secondary distribution nodes. The system enables rapid fault detection (line-to-line, line-to-ground, and overload) and initiates a fault-based response to isolate the load through controlled relays. Additionally, an intelligent power management system automatically rectifies surge faults (short-lived faults) and reports non-surge faults (persistent faults) to the control center. It continuously updates the status of real-time power parameters to the database using a Global System for Mobile Communications (GSM)-based communication system with a frequency of 60 s per sample for power management. The Proteus-based simulation and a scaled-down model validate the efficiency and supremacy of the proposed system over the existing control system for power distribution nodes. The results demonstrate that our model detects critical faults and initiates the response within 100 and 200 milliseconds, respectively. Surge faults are automatically rectified within 90 s, while non-surge faults are reported to the database after 90 s. This approach significantly reduces downtime, enables energy accountability, and supports sustainable energy management through a decentralized and distributed control system.
Suggested Citation
Yongxiao Li & Zaheer Ul Hassan & Haresh Kumar Sootahar & Touseef Hussain & Kamlesh Kumar Soothar & Zulfiqar Ali Bhutto, 2025.
"Intelligent Power Management and Autonomous Fault Diagnosis for Enhanced Reliability in Secondary Power Distribution Systems,"
Sustainability, MDPI, vol. 17(13), pages 1-18, June.
Handle:
RePEc:gam:jsusta:v:17:y:2025:i:13:p:6009-:d:1691077
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