a sequence component-based feature for passive and artificial-intelligence-based islanding detection

Feature selection is a critical aspect of designing islanding detection schemes, as it affects the method’s accuracy, speed, complexity, and overall performance. various features are suggested in the literature and integrated into different (ai)-based methods to achieve high performance in islanding detection. in this paper, a feature based on electrical zero sequence components is proposed, which can be used as the sole feature for islanding detection. the proposed feature demonstrates favorable results of 97.84% when using a simple threshold model. additionally, the proposed feature can be employed in ai-based methods to achieve high balanced accuracy.based on the obtained results, using the proposed feature as the only feature in a 1d cnn model yields a competitive result of (99.78 ± 0.012). this feature is a key aspect when comparing the results of ai-based methods, such as sophisticated long short-term memory (lstm) neural networks, that utilize a higher number of different features.