An Innovative Islanding Detection Algorithm for Grid-Tied Inverter Utilizing In-Circuit Magnetic Characteristics of Inductors in LCL Filters

Abstract

Unintentional islanding in grid-connected photovoltaic inverters (GCPVI) poses a significant challenge to power system reliability and safety. This article introduces a novel islanding detection method that leverages the magnetic characteristics of the GCPVI system. The $BH$ curve, which defines the relationship between the magnetic flux density ($B$) and the magnetic field strength ($H$), is derived from the voltage across the inverter-side and grid-side inductors, and the current flowing through them. These $BH$ curves are obtained for each cycle of the measured signals and analysed over successive cycles to calculate the alienation coefficient and cumulative index. The computed coefficients and indices form a time series vector, referred to as the islanding index. This index is compared against a threshold to detect unintentional islanding, even in the non-detection zone (NDZ). The proposed algorithm is experimentally validated on a single-phase hardware-based grid-connected inverter driven by bipolar pulse-width modulation. The measured voltage and current samples of the both side inductors are transmitted to a micro controller for real-time analysis. Using these samples, the method effectively distinguishes islanding from non-islanding events, such as load switching and distributed generation (DG) tripping, within a shorter time frame, adhering to international standards.