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Article

Design Optimization of Improved Fractional-Order Cascaded Frequency Controllers for Electric Vehicles and Electrical Power Grids Utilizing Renewable Energy Sources

by
Fayez F. M. El-Sousy
1,*,
Mohammed H. Alqahtani
1,
Ali S. Aljumah
1,
Mokhtar Aly
2,
Sulaiman Z. Almutairi
1 and
Emad A. Mohamed
1,3
1
Department of Electrical Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al Kharj 16278, Saudi Arabia
2
Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Bellavista 7, Santiago 8420000, Chile
3
Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt
*
Author to whom correspondence should be addressed.
Fractal Fract. 2023, 7(8), 603; https://doi.org/10.3390/fractalfract7080603
Submission received: 26 May 2023 / Revised: 17 July 2023 / Accepted: 18 July 2023 / Published: 4 August 2023

Abstract

Recent developments in electrical power grids have witnessed high utilization levels of renewable energy sources (RESs) and increased trends that benefit the batteries of electric vehicles (EVs). However, modern electrical power grids cause increased concerns due to their continuously reduced inertia resulting from RES characteristics. Therefore, this paper proposes an improved fractional-order frequency controller with a design optimization methodology. The proposed controller is represented by two cascaded control loops using the one-plus-proportional derivative (1 + PD) in the outer loop and a fractional-order proportional integral derivative (FOPID) in the inner loop, which form the proposed improved 1 + PD/FOPID. The main superior performance characteristics of the proposed 1 + PD/FOPID fractional-order frequency controller over existing methods include a faster response time with minimized overshoot/undershoot peaks, an ability for mitigating both high- and low-frequency disturbances, and coordination of EV participation in regulating electrical power grid frequency. Moreover, simultaneous determination of the proposed fractional-order frequency controller parameters is proposed using the recent manta ray foraging optimization (MRFO) algorithm. Performance comparisons of the proposed 1 + PD/FOPID fractional-order frequency controller with existing PID, FOPID, and PD/FOPID controllers are presented in the paper. The results show an improved response, and the disturbance mitigation is also obtained using the proposed MRFO-based 1 + PD/FOPID control and design optimization methodology.
Keywords: electric vehicles (EVs); fractional-order control; frequency controller; manta ray foraging optimization; modern power grids electric vehicles (EVs); fractional-order control; frequency controller; manta ray foraging optimization; modern power grids

Share and Cite

MDPI and ACS Style

El-Sousy, F.F.M.; Alqahtani, M.H.; Aljumah, A.S.; Aly, M.; Almutairi, S.Z.; Mohamed, E.A. Design Optimization of Improved Fractional-Order Cascaded Frequency Controllers for Electric Vehicles and Electrical Power Grids Utilizing Renewable Energy Sources. Fractal Fract. 2023, 7, 603. https://doi.org/10.3390/fractalfract7080603

AMA Style

El-Sousy FFM, Alqahtani MH, Aljumah AS, Aly M, Almutairi SZ, Mohamed EA. Design Optimization of Improved Fractional-Order Cascaded Frequency Controllers for Electric Vehicles and Electrical Power Grids Utilizing Renewable Energy Sources. Fractal and Fractional. 2023; 7(8):603. https://doi.org/10.3390/fractalfract7080603

Chicago/Turabian Style

El-Sousy, Fayez F. M., Mohammed H. Alqahtani, Ali S. Aljumah, Mokhtar Aly, Sulaiman Z. Almutairi, and Emad A. Mohamed. 2023. "Design Optimization of Improved Fractional-Order Cascaded Frequency Controllers for Electric Vehicles and Electrical Power Grids Utilizing Renewable Energy Sources" Fractal and Fractional 7, no. 8: 603. https://doi.org/10.3390/fractalfract7080603

APA Style

El-Sousy, F. F. M., Alqahtani, M. H., Aljumah, A. S., Aly, M., Almutairi, S. Z., & Mohamed, E. A. (2023). Design Optimization of Improved Fractional-Order Cascaded Frequency Controllers for Electric Vehicles and Electrical Power Grids Utilizing Renewable Energy Sources. Fractal and Fractional, 7(8), 603. https://doi.org/10.3390/fractalfract7080603

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