Distributed Model-Based Predictive Secondary Control for Hybrid AC/DC Microgrids

This article presents a novel scheme based on distributed model-based predictive control for the secondary level of hybrid ac/dc microgrids (MGs). Prediction models droop and power-transfer equations are proposed to characterize generators in both ac dc sub-MGs, whereas power balance constraints used predict behavior interlinking converters. The operational (such as powers action limits) included all formulations. Experimental results validate following cases: 1) load changes, working within operating constraints; 2) managing frequency regulation sub-MG, voltage global consensus whole MG; 3) maintaining MG performance presence communication malfunction while ensuring that plug-and-play capability is preserved.