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Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

Billel Meghni1, Afaf Benamor2, Oussama Hachana3, Ahmad Taher Azar4,5,*, Amira Boulmaiz6, Salah Saad1, El-Sayed M. El-kenawy7,8, Nashwa Ahmad Kamal9, Suliman Mohamed Fati5, Naglaa K. Bahgaat10

1 Department of Electrical Engineering, Badji Mokhtar University, LSEM Laboratory, Annaba, 23000, Algeria
2 Department of Electrical Engineering, Biskra University, LGEB Laboratory, Biskra, 07000, Algeria
3 Department of Drilling and Rig Mechanics, Ksadi Merbah University, Ouargla, 30000, Algeria
4 College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia
5 Faculty of Computers and Artificial Intelligence, Benha University, Benha, 13518, Egypt
6 Department of Electronics, University of Badji Mokhtar, LERICA Laboratory, Annaba, 23000, Algeria
7 Delta Higher Institute for Engineering &Technology (DHIET), Mansoura, 35511, Egypt
8 Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura, 35712, Egypt
9 Faculty of Engineering, Cairo University, Giza, 12613, Egypt
10 Department of Communications and Electronics Engineering, Faculty of Engineering, Canadian International College (CIC), ElShiekh Zayed, Egypt

* Corresponding Author: Ahmad Taher Azar. Email: email

Computers, Materials & Continua 2023, 74(2), 3977-3996. https://doi.org/10.32604/cmc.2023.029838

Abstract

The integration of wind turbines (WTs) in variable speed drive systems belongs to the main factors causing low stability in electrical networks. Therefore, in order to avoid this issue, WTs hybridization with a storage system is a mandatory. This paper investigates WT system operating at variable speed. The system contains of a permanent magnet synchronous generator (PMSG) supported by a battery storage system (BSS). To enhance the quality of active and reactive power injected into the network, direct power control (DPC) scheme utilizing space-vector modulation (SVM) technique based on proportional-integral (PI) control is proposed. Meanwhile, to improve the rendition of this method (DPC-SVM-PI), the rooted tree optimization technique (RTO) algorithm-based controller parameter identification is used to achieve PI optimal gains. To compare the performance of RTO-based controllers, they were implemented and tested along with some other popular controllers under different working conditions. The obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion (THD), overshoot percentage, settling time, rise time, average active power value, overall efficiency, and active power steady-state error.

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Cite This Article

APA Style
Meghni, B., Benamor, A., Hachana, O., Azar, A.T., Boulmaiz, A. et al. (2023). Rooted tree optimization for wind turbine optimum control based on energy storage system. Computers, Materials & Continua, 74(2), 3977-3996. https://doi.org/10.32604/cmc.2023.029838
Vancouver Style
Meghni B, Benamor A, Hachana O, Azar AT, Boulmaiz A, Saad S, et al. Rooted tree optimization for wind turbine optimum control based on energy storage system. Comput Mater Contin. 2023;74(2):3977-3996 https://doi.org/10.32604/cmc.2023.029838
IEEE Style
B. Meghni et al., “Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System,” Comput. Mater. Contin., vol. 74, no. 2, pp. 3977-3996, 2023. https://doi.org/10.32604/cmc.2023.029838



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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