MustafaKamoona/NDSA-Grid-Connected-AC-DC-Microgrid: Model-Less Neural Dual-Sequence Adaptive Control for Grid-Connected Hybrid AC/DC Microgrid

This repository provides the simulation models, control algorithms, and data associated with the paper "Model-Less Neural Dual-Sequence Adaptive Control for Grid-Connected Hybrid AC/DC Microgrids." The work proposes a fully model-less neural dual-sequence adaptive (NDSA) control framework for grid-interfacing voltage source converters (VSCs), enabling robust DC-bus voltage regulation, bidirectional AC–DC power exchange, and coordinated power sharing under unbalanced and uncertain operating conditions. The proposed approach relies only on locally measured electrical quantities and does not require detailed system parameters or offline training. Validation is carried out on a five-bus hybrid AC/DC microgrid using realistic 24-hour load and renewable generation profiles, with comparative evaluation against a well-tuned PI-based controller. This repository supports reproducible research and is intended for researchers and practitioners working on hybrid AC/DC microgrids, power electronics, and intelligent control.