Combining Sliding Mode and Fractional-Order Theory for Maximum Power Point Tracking Enhancement of Variable-Speed Wind Energy Conversion-Reference-Cited by-同舟云学术

Combining Sliding Mode and Fractional-Order Theory for Maximum Power Point Tracking Enhancement of Variable-Speed Wind Energy Conversion

Published:2024-07-30 Issue:8 Volume:8 Page:447
ISSN:2504-3110
Container-title:Fractal and Fractional
language:en
Short-container-title:Fractal Fract

Author:

Al-Dhaifallah Mujahed¹²^ORCID,Saif Abdul-Wahid A.¹³^ORCID,Elferik Sami¹³^ORCID,Elkhider Siddig M.¹³^ORCID,Aldean Abdalrazak Seaf¹

Affiliation:

1. Control and Instrumentation Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia

2. Interdisciplinary Research Center for Sustainable Energy Systems (IRC-SES), King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia

3. Interdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML), King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia

Abstract

The present study used the wind turbine as a model to focus on combining sliding mode and fractional-order theory for maximum power point tracking (MPPT) enhancement. The combination of sliding mode and fractional-order theory was implemented considering the nonlinearity of the studied model for studying the system’s response. The response of the wind turbine was evaluated after introducing disturbance to the output of the regulator. The results showed the excellent ability of the system to track the reference, regardless of any disturbances. There was no impact of any disturbance on the system or the system’s good follow-up. Moreover, the control scheme showed robustness as regards rejecting the disturbances.

Funder

King Fahd University of Petroleum and Minerals

Publisher

MDPI AG

Link

https://www.mdpi.com/2504-3110/8/8/447/pdf

Reference45 articles.

1. Benbouhenni, H., Boudjema, Z., Bizon, N., Thounthong, P., and Takorabet, N. (2022). Direct power control based on modified sliding mode controller for a variable-speed multi-rotor wind turbine system using PWM strategy. Energies, 15.

2. Shchur, I., Klymko, V., Xie, S., and Schmidt, D. (2023). Design features and numerical investigation of counter-rotating VAWT with co-axial rotors displaced from each other along the axis of rotation. Energies, 16.

3. A new direct power control method of the DFIG-DRWT system using neural PI controllers and a four-level neural modified SVM technique;Benbouhenni;J. Appl. Res. Technol.,2023

4. REN21 (2024, March 23). Renewable Global Status Report. Available online: https://www.ren21.net/reports/global-status-report/.

5. Chauhan, S., Sameeullah, M., and Dahiya, R. (2014, January 8–10). Maximum Power Point Tracking scheme for variable speed wind generator. Proceedings of the IEEE 6th India International Conference on Power Electronics (IICPE), Kurukshetra, India.