Particle swarm optimization algorithm-tuned fuzzy cascade fractional order PI-Fractional order PD for frequency regulation of dual-area power system

Shouran, Mokhtar ORCID: https://orcid.org/0000-0002-9904-434X and Alsseid, Aleisawee 2022. Particle swarm optimization algorithm-tuned fuzzy cascade fractional order PI-Fractional order PD for frequency regulation of dual-area power system. Processes 10 (3) , 477. 10.3390/pr10030477

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Abstract

This study proposes a virgin structure of Fuzzy Logic Control (FLC) for Load Frequency Control (LFC) in a dual-area interconnected electrical power system. This configuration benefits from the advantages of fuzzy control and the merits of Fractional Order theory in traditional PID control. The proposed design is based on Fuzzy Cascade Fractional Order Proportional-Integral and Fractional Order Proportional-Derivative (FC FOPI-FOPD). It includes two controllers, namely FOPI and FOPD connected in cascade in addition to the fuzzy controller and its input scaling factor gains. To boost the performance of this controller, a simple and powerful optimization method called the Particle Swarm Optimization (PSO) algorithm is employed to attain the best possible values of the suggested controller’s parameters. This task is accomplished by reducing the Integral Time Absolute Error (ITAE) of the deviation in frequency and tie line power. Furthermore, to authenticate the excellence of the proposed FC FOPI-FOPD, a comparative study is carried out based on the obtained results and those from previously published works based on classical PID tuned by the Losi Map-Based Chaotic Optimization Algorithm (LCOA), Fuzzy PID Optimized by Teaching Learning-Based Optimization (TLBO) algorithm and Fuzzy PID with a filtered derivative mode tuned by PSO, which is employed in the same interconnected power system. The robustness of the suggested fuzzy structure is investigated against the parametric uncertainties of the testbed system. The simulation results revealed that the proposed FC FOPI-FOPD is robust, and it outperformed the other investigated controllers. For example, the drops in the frequency in area one and area two were improved by 89.785% and 97.590%, respectively, based on employing the proposed fuzzy configuration compared with the results obtained from the traditional PID.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Additional Information:	This is an open access article distributed under the Creative Commons Attribution License
Publisher:	MDPI
ISSN:	2227-9717
Date of First Compliant Deposit:	25 April 2022
Date of Acceptance:	24 February 2022
Last Modified:	10 Feb 2024 02:09
URI:	https://orca.cardiff.ac.uk/id/eprint/149200

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