Vigil AI Assemble Leveraging Ensemble Technique for Enhanced Detection of Multi-Converter Synchronous Active Islanding Mode in Hybrid Power Distribution Systems

Abstract

The increasing complexity of contemporary power distribution networks and the necessity to incorporate renewable energy sources have led to the rise in popularity of hybrid power distribution systems. A significant challenge for such systems is the reliable identification of multi-converter synchronous islanding mode, wherein numerous converters operate in synchronous islanded situations. Using state-of-the-art artificial intelligence ensemble techniques, we introduce "Vigil AI Assemble," a novel approach to detecting multi-converter synchronous islanding modes in hybrid power distribution systems. The proposed method enhances the precision and robustness of islanding situation recognition by combining various AI algorithms, each with its own distinct properties. By combining several AI-based techniques, the ensemble method can analyze system properties, waveform data, and communication in real-time.