Resilient type-2 self adaptive fuzzy-TFOPI strategy for frequency mitigation in energy storage based power system

The urgency of demand and variations in generation due to increased reliance on renewable energy have raised concerns about power system stability (PSS). In light of the challenges posed by the complexity of the power system, this research aims to develop an intelligent controller architecture that can enhance the PSS and efficiency of multi-area power systems (MAPSs) through self-adaptive properties. Keeping electric power balance is indispensable for efficient and reliable function for MAPSs. This paper introduces the T2-SAF-TFOPI controller approach, which is a combination of type-2 self-adaptive fuzzy and tilt fractional order PI. The TFOPID controller is tuned using a bio-inspired tunicate search algorithm (TSA) and to make the power system self-adapt, the fuzzy rules are continuously fine-tuned in response to changes occurring in real time. The proposed control system is put into action for MAPSs, which includes thermal, redox flow batteries (RFBs), PV, and wind generation. The TSA-tuned T2-SAF-TFOPI controller provides overall stability by 159.7 % and 118.7 % percent in ∆F₁, and by 181.6 % and 310.3 % in ∆F₂ correspondingly as compared to other state-of-the-art techniques.