An extensive review of islanding detection approaches in microgrids for distribution generations

Abstract

Microgrids integrated with distributed systems provide several benefits to the power grid, including faster detection times, superior power quality, and energy savings. Microgrids are managed using various methodologies in both grid-connected and island states. Microgrids must detect inadvertent islanding to protect individuals and prevent device damage. Monitoring and identifying magnitude anomalies are the foundation of the majority of islanding detection approaches (IDAs). This study summarizes the IDAs used in microgrids. An islanding fault is a microgrid that inadvertently disconnects from itself owing to a problem in the utility grid. A through categorization of IDAs is provided, with a focus on both local and remote approaches. Local IDAs can be further classified using passive, active, and hybrid methods. Furthermore, the power-quality effect, nondetection zone (NDZ), detection time (DT), and error detection rate (EDR) statistical comparison of the IDAs is examined. The benefits, drawbacks, and research gaps in the current work are evaluated. Lastly, challenges and recommendations for future research are highlighted.