High penetrated renewable energy sourcesbased AOMPC for microgrid's frequency regulation during weather changes, timevarying parameters and generation unit collapse

Abstract

Using inverter-based topologies and lack of rotational masses can lead to a noticeable reduction in the inertia ofmodern systems and have detrimental effects on the resiliency, stability and strengths of microgrids. Effective frequency controlancillary services and modern adaptive control mechanisms can be proposed to resolve the mentioned challenges practically.From this perspective, several flexible and intelligent control approaches have been recently introduced to create a balancebetween generation and load demand during various operational conditions in low-inertia power systems. This study suggests asupportive collaboration between two distributed generations including virtual inertia of wind turbine generator and fast speedmicro-turbine based on an adaptive optimal model predictive control (AOMPC). To demonstrate the effectiveness of theproposed framework, the results are compared with the previous controllers like optimal proportional-integral, optimal fractionalorder proportional-integral-derivative (PID), optimal fuzzy PID, the optimised membership function of fuzzy and adaptive MPCcontroller during multiple load variations, changes in the weather patterns, unwanted time-varying uncertainties and collapse ofpower generation units.