A Review on Real-time Substation Feeder Power Line Monitoring and Auditing Systems

Abstract

The increasing demand for reliable and efficient power distribution has underscored the critical need for real-time substation feeder power line monitoring and auditing systems. These systems are essential for enhancing grid reliability, minimizing outages, and improving power quality in modern smart grids. Traditional monitoring methods, reliant on manual inspections and delayed responses, often fail to meet the dynamic requirements of today’s power networks. This review comprehensively examines the state-of-the-art technologies driving real-time feeder monitoring and auditing, focusing on internet of things (IoT), supervisory control and data acquisition (SCADA) systems, artificial intelligence (AI), wireless sensor networks (WSN), and advanced sensors. By synthesizing recent advancements, the study highlights their applications in monitoring key parameters like voltage, current, and power factor, as well as auditing for energy losses and theft. The review categorizes approaches into sensor-based, communication-based, and AI/ML-driven methodologies, evaluating their strengths, limitations, and scalability. It also addresses challenges such as cybersecurity, interoperability, and cost-effectiveness, particularly in rural deployments. Contributions include a comparative analysis of technologies, identification of research gaps, and a roadmap for future innovations, including the integration of 5G and edge-AI. This review serves as a valuable resource for researchers, engineers, and policymakers aiming to advance smart grid technologies and ensure sustainable power distribution.