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A quasi-oppositional FBI algorithm driven fuzzy cascaded fractional-order controller for enhancing transient stability in hybrid power systems
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A quasi-oppositional FBI algorithm driven fuzzy cascaded fractional-order controller for enhancing transient stability in hybrid power systems
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Journal Article
A quasi-oppositional FBI algorithm driven fuzzy cascaded fractional-order controller for enhancing transient stability in hybrid power systems
2025
Overview
The basic contemplate of this work is to enhance the power and frequency variances of power system. The integration of wind and solar energy along with pumped hydrogen energy storage (PHES) may enhance the challenge to maintain the stability of the system. The design of smart and knowledgeable controller is immensely obligatory for stability of hybrid power system. In this work, intelligent fuzzy fractional order proportional integral derivative cascaded with 1 + fractional order proportional integral (FFOPID (1 + FOPI)) is designed for frequency regulation of power system. The immensely influential parameters of proposed FFOPID (1 + FOPI) controller are decided by forensic-based investigation (FBI) and quasi oppositional-based FBI (QOFBI) algorithms. The integration of QOFBI and FFOPID (1 + FOPI) is tested in four different power system environments over other controllers. The supremacy of proposed QOFBI based FFOPID (1 + FOPI) controller is confirmed through simulation result analysis by considering some statistical errors such as undershoot, overshoot, settling time and integral of time-weighted absolute error. The improvement of proposed controller over other controllers is quietly detectable in terms of frequency and tie-line power deviations. These results demonstrate that intelligent optimization in conjunction with fuzzy logic based fractional-order control can effectively increase system robustness in transient scenarios. The results of this research demonstrate that PHES is an appropriate choice for preserving frequency stability throughout the development of smart and renewable-dominated power grids when combined with RESs.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
