String-Level Ground Fault Localization for TN-Earthed Three-Phase Photovoltaic Systems

• URL: http://arxiv.org/abs/2602.12289v2
• Date: Mon, 16 Feb 2026 02:12:30 GMT
• Title: String-Level Ground Fault Localization for TN-Earthed Three-Phase Photovoltaic Systems
• Authors: Yuanliang Li, Xun Gong, Reza Iravani, Bo Cao, Heng Liu, Ziming Chen,
• Abstract summary: The DC-side ground fault (GF) poses significant risks to three-phase TN-earthed photovoltaic (PV) systems.<n>This work presents a comprehensive analysis of GF characteristics through fault-current analysis and a simulation-based case study covering multiple fault locations.<n>Building on these insights, we propose an edge-AI-based GF localization approach tailored for three-phase TN-earthed PV systems.
• Score: 7.573722142546887
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The DC-side ground fault (GF) poses significant risks to three-phase TN-earthed photovoltaic (PV) systems, as the resulting high fault current can directly damage both PV inverters and PV modules. Once a fault occurs, locating the faulty string through manual string-by-string inspection is highly time-consuming and inefficient. This work presents a comprehensive analysis of GF characteristics through fault-current analysis and a simulation-based case study covering multiple fault locations. Building on these insights, we propose an edge-AI-based GF localization approach tailored for three-phase TN-earthed PV systems. A PLECS-based simulation model that incorporates PV hysteresis effects is developed to generate diverse GF scenarios, from which correlation-based features are extracted throughout the inverter's four-stage shutdown sequence. Using the simulated dataset, a lightweight Variational Information Bottleneck (VIB)-based localization model is designed and trained, achieving over 93% localization accuracy at typical sampling rates with low computational cost, demonstrating strong potential for deployment on resource-constrained PV inverters.

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