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An innovative LFC system using a Fuzzy FOPID-enhanced via PI controller tuned by the catch fish optimization algorithm under nonlinear conditions

Almutairi, Saleh, Anayi, Fatih ORCID: https://orcid.org/0000-0001-8408-7673, Packianather, Michael ORCID: https://orcid.org/0000-0002-9436-8206 and Shouran, Mokhtar ORCID: https://orcid.org/0000-0002-9904-434X 2025. An innovative LFC system using a Fuzzy FOPID-enhanced via PI controller tuned by the catch fish optimization algorithm under nonlinear conditions. Sustainability 17 (13) , 5966. 10.3390/su17135966

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Abstract

Load frequency control (LFC) remains a critical challenge in ensuring the stability of modern power grids. The integration of nonlinear dynamics into LFC design is paramount to achieving robust performance, which directly underpins grid reliability. This study introduces a novel hybrid control strategy—a fuzzy fractional-order proportional–integral–derivative (Fuzzy FOPID) controller augmented with a proportional–integral (PI) compensator—for LFC applications in two distinct dual-area interconnected power systems. To optimize the controller’s parameters, the recently developed Catch Fish Optimization Algorithm (CFOA) is employed, leveraging the Integral Time Absolute Error (ITAE) as the primary cost function for precision tuning. A comprehensive comparative analysis is conducted to benchmark the proposed controller against the existing methodologies documented in the literature. Nonlinear elements’ impact on the system stability is also investigated. The investigation evaluates the impact of critical nonlinearities, including governor dead band (GDB) and generation rate constraints (GRCs), on system performance. The simulation results demonstrate that the CFOA-tuned Fuzzy FOPID + PI controller exhibits superior robustness and dynamic response compared to conventional approaches, effectively mitigating frequency deviations and maintaining grid stability under nonlinear operating conditions. Furthermore, the CFOA demonstrates marginally superior convergence and tuning accuracy relative to the widely adopted Particle Swarm Optimization (PSO) algorithm. These findings underscore the proposed controller’s potential as a high-performance solution for real-world LFC systems, particularly in scenarios characterized by nonlinearities and interconnected grid complexities. This study advances the field by bridging the gap between fractional-order fuzzy control theory and practical power system applications, offering a validated strategy for enhancing grid resilience in dynamic environments.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Schools > Engineering
Publisher: MDPI
ISSN: 2071-1050
Date of First Compliant Deposit: 2 July 2025
Date of Acceptance: 27 June 2025
Last Modified: 03 Jul 2025 12:30
URI: https://orca.cardiff.ac.uk/id/eprint/179475

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