Design of optimal intelligent frequency control approach for autonomous microgrid: a step towards sustainable future

Nowadays, numerous renewable energy sources (RESs) have been integrated into autonomous microgrids (AμGs) to reduce carbon emissions and promote sustainable energy. This study presents an approximate model of an AμG comprising solar photovoltaic, wind turbine generator, biodiesel, and biogas turbine generators as primary sources, along with aqua electrolyser, reformer, and fuel cell (FC) as energy storage elements. The proposed AμG operates fully on RESs, aiming for a transition to an emission-free future. Surplus renewable energy is converted to hydrogen via an electrolyser, while excess biogas is reformed into hydrogen and stored for later use. During peak demand, hydrogen is utilised through the FC to generate electricity. For efficient load frequency control, an intelligent fuzzy-driven tilt integral derivative with filter (F-TIDF) controller, optimised using a novel electric eel foraging optimisation algorithm, is proposed. Its performance is validated against five advanced controllers and tested on the IEEE 39-bus system.