Extensive research conducted over the past decade (2015–2025) has consistently demonstrated that ML methods effectively detect and diagnose inverter faults in grid-connected solar systems, frequently achieving accuracies exceeding 95%. Summary: Inverter power meters play a critical role in monitoring solar energy systems. Discover how advanced tools like EK SOLAR's monitoring solutions simplify diagnostics while. This paper proposes a novel AMI-only method that remotely detects Volt-Watt settings via Hough transform-based inference and estimates long-term energy curtailment using historical voltage and active power measurements. Year-long quasi-static time-series (QSTS) simulations on a benchmark feeder. Hybrid inverters add battery, PV, and grid dynamics, so arc-fault detection needs smarter logic. This review breaks down AFCI algorithms, how hybrid control loops affect detection, and what mitigation strategies prove reliable in the field. Validated across more than 1,000 systems, the approach offers a low-cost, low-intervention solution for improving reliability, fault. The continuous, effective operation of grid-connected photovoltaic (GCPV) systems depends on dependable inverter failure detection. Early, precise fault diagnosis improves general system dependability, lowers maintenance costs, and saves downtime. Although computing efficiency remains a difficulty.