Hybrid Particle Swarm and Gravitational Search Algorithm-Based Optimal Fractional Order PID Control Scheme for Performance Enhancement of Offshore Wind Farms

Nour A. Mohamed, Hany M. Hasanien (), Abdulaziz Alkuhayli, Tlenshiyeva Akmaral, Francisco Jurado and Ahmed O. Badr
Additional contact information
Nour A. Mohamed: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Hany M. Hasanien: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Abdulaziz Alkuhayli: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Tlenshiyeva Akmaral: Department of Electrical Engineering, University of Jaén, 23700 Linares, Spain
Francisco Jurado: Department of Electrical Engineering, University of Jaén, 23700 Linares, Spain
Ahmed O. Badr: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt

Sustainability, 2023, vol. 15, issue 15, 1-25

Abstract: This article aimed to introduce a novel application of a hybrid particle swarm optimizer and gravitational search algorithm (HPSOGSA) that can be used for optimal control of offshore wind farms’ voltage source converter connected to HVDC transmission lines. Specifically, the algorithm was used to design fractional-order proportional-integral-derivative (FOPID) controller parameters designed to minimize the system’s objective function based on an integral squared error. The proposed FOPID controller was applied to improve offshore wind farm performance under different transient conditions, and its results were compared with a PI controller that was designed using a genetic algorithm and grey wolf optimization algorithm. The fault ride-through capabilities of the proposed control strategy were also evaluated. The findings suggest that the HPSOGSA-based FOPID controller outperformed the other two methods, significantly enhancing offshore wind farm operations. The control strategy was thoroughly tested using MATLAB/Simulink under various operating scenarios.

Keywords: particle swarm optimizer (PSO); gravitational search algorithm (GSA); fractional order proportional-integral derivative (FOPID); high voltage direct current (HVDC) system; voltage source converter (VSC) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/15/11912/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/15/11912/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:15:p:11912-:d:1209354

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().