Intelligent system design for loss detection and real-time monitoring in electrical distribution networks

In today's energy systems, the increasing demand and the need for sustainability make it imperative to improve the efficiency of power transmission and distribution infrastructures. In this context, non-technical losses — primarily caused by electricity theft — constitute a critical issue, particularly in low-voltage distribution networks. In hybrid grid configurations involving both underground and overhead lines, the detection of such losses typically requires costly excavation, field inspections, and manual labor, all of which disrupt operational continuity and increase overall system costs. This thesis proposes a cost-effective, remotely monitorable, and real-time alerting system for detecting electricity theft without requiring physical intervention. The system is designed to be integrated into distribution panels and relies on SCT-013 current sensors installed at the entry and exit points of the circuit. The analog signals captured by the sensors are digitized using a high-resolution ADS1115 analog-to-digital converter and processed by a NodeMCU ESP8266 microcontroller. Through this architecture, real-time current flow is continuously monitored, and abnormal discrepancies exceeding defined thresholds are interpreted as potential theft conditions, prompting an immediate alert. The proposed system has been tested in a simulated environment under various load conditions and theft scenarios, yielding consistent and reliable results. The findings suggest that the model can offer a viable alternative for theft detection in densely populated urban areas with predominantly underground distribution lines, eliminating the need for intrusive excavation. Additionally, the system's wireless data transmission capability enables seamless integration with centralized management platforms such as SCADA, aligning with the broader trend of digital grid transformation. This study presents an innovative approach to non-technical loss detection using low-cost hardware components. It introduces a scalable, easy-to-install monitoring system that holds significant promise for improving energy efficiency, reducing economic losses, and enhancing grid transparency and control.