Adaptive PI Control Strategy for Optimal Microgrid Autonomous Operation

The present research produces a new technique for the optimum operation of an isolated microgrid (MGD) based on enhanced block-sparse adaptive Bayesian algorithm (EBSABA). To update proportional-integral (PI) controller gains online, suggested approach considers impact actuating error signal as well its magnitude. reach compromise result between various purposes, Response Surface Methodology (RSMT) is combined with sunflower optimization (SFO) and particle swarm (PSO) algorithms. demonstrate success novel approach, benchmark MGD evaluated in three different Incidents: (1) removing from utility (islanding mode); (2) load variations under islanding mode; (3) three-phase fault mode. Extensive simulations are run to test using PSCAD/EMTDC program. validity proposed optimizer demonstrated by comparing results those obtained least mean square root exponential method (LMSRE) control, SFO, PSO methodologies. study demonstrates superiority EBSABA over LMSRE, approaches system’s transient reactions.