SoC Based Application of Smart Automatic Online Realtime Partial Discharge Condition Monitoring System for the Power Grid

This paper presents a hardware-software co-designed system for real-time online monitoring of Partial Discharge (PD) in the Power Grid without human interaction. PD is a critical indicator of insulation degradation, which can lead to premature failure of components and disrupt reliable electric supply. The proposed system utilizes an SoC-based Edge Computing Unit for long-term monitoring activities. It incorporates a wavelet denoising module, an auto management program, and an AI-based detection model to enable automatic PD alarm generation. The system is tested and iterated in a controlled lab environment, capturing standard PD signals. The AI classification model is trained using manually labeled PRPD pattern datasets. Subsequently, the system is deployed in a real power grid for long-term, real-time PD monitoring. The effectiveness of the proposed system is demonstrated through experimental setups and result analysis. The SoC-based real-time online PD monitoring system offers a proactive approach to safeguarding power equipment by detecting and addressing insulation degradation in the Power Grid.