Load frequency control based on the Bees Algorithm for the Great Britain power system

Shouran, Mokhtar ORCID: https://orcid.org/0000-0002-9904-434X, Anayi, Fatih ORCID: https://orcid.org/0000-0001-8408-7673, Packianather, Michael ORCID: https://orcid.org/0000-0002-9436-8206 and Habil, Monier 2021. Load frequency control based on the Bees Algorithm for the Great Britain power system. Designs 5 (3) , 50. 10.3390/designs5030050

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Abstract

This paper focuses on using the Bees Algorithm (BA) to tune the parameters of the proposed Fuzzy Proportional–Integral–Derivative with Filtered derivative (Fuzzy PIDF), Fractional Order PID (FOPID) controller and classical PID controller developed to stabilize and balance the frequency in the Great Britain (GB) power system at rated value. These controllers are proposed to meet the requirements of the GB Security and Quality of Supply Standard (GB-SQSS), which requires frequency to be brought back to its nominal value after a disturbance within a specified time. This work is extended to employ the proposed fuzzy structure controller in a dual-area interconnected power system. In comparison with controllers tuned by Particle Swarm Optimization (PSO) and Teaching Learning-Based Optimization (TLBO) used for the same systems, simulation results show that the Fuzzy PIDF tuned by BA is able to significantly reduce the deviation in the frequency and tie-line power when a sudden disturbance is applied. Furthermore, the applied controllers tuned by BA including the Fuzzy PIDF prove their high robustness against a wide range of system parametric uncertainties and different load disturbances.

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 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher:	MDPI
ISSN:	2411-9660
Date of First Compliant Deposit:	20 August 2021
Date of Acceptance:	26 July 2021
Last Modified:	10 Feb 2024 02:09
URI:	https://orca.cardiff.ac.uk/id/eprint/143490

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