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An intelligent hybrid PIDF enhanced by a fuzzy fractional-order controller for robust load frequency regulation in a two-area interconnected power system

Almutairi, Saleh, Anayi, Fatih ORCID: https://orcid.org/0000-0001-8408-7673, Packianather, Michael ORCID: https://orcid.org/0000-0002-9436-8206, Almutairi, Mohammad and Shouran, Mokhtar 2026. An intelligent hybrid PIDF enhanced by a fuzzy fractional-order controller for robust load frequency regulation in a two-area interconnected power system. Energies 19 (6) , 1442. 10.3390/en19061442

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Abstract

Maintaining frequency regulation in interconnected power systems becomes increasingly difficult in the presence of nonlinear operating conditions. To address this issue, this study develops a hybrid load frequency control scheme in which a fuzzy fractional-order FOPI–FOPD controller is incorporated within a PIDF framework for a two-area LFC system. The controller parameters are optimized using the Dwarf Mongoose Optimization Algorithm (DMOA) and the Catch Fish Optimization Algorithm (CFOA), while the Integral of Time-Weighted Absolute Error (ITAE) is adopted as the performance criterion. The proposed strategy is examined under both linear and nonlinear scenarios, including the effects of Governor Dead Band (GDB) and Generation Rate Constraints (GRC). In the linear case, the DMOA-based design achieves an ITAE of 0.02939 with a tie-line settling time of 13.5478 s, whereas the CFOA-based design produces a bounded and convergent response with an ITAE of 0.03937 and a settling time of 14.4947 s. When GDB nonlinearity is introduced, the DMOA-tuned controller exhibits performance deterioration, yielding an ITAE of 0.1098 and a settling time of 19.0416 s, while the CFOA-tuned design shows more favorable time-domain performance with a lower ITAE of 0.05845 and a bounded settling time of 16.3595 s. These findings indicate that the CFOA-optimized PIDF–Fuzzy FOPI–FOPD controller provides an effective LFC solution under the examined nonlinear operating conditions.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Schools > Engineering
Publisher: MDPI
ISSN: 1996-1073
Date of First Compliant Deposit: 24 March 2026
Date of Acceptance: 9 March 2026
Last Modified: 24 Mar 2026 16:58
URI: https://orca.cardiff.ac.uk/id/eprint/185991

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