Optimal Fractional-Order Controller for the Voltage Stability of a DC Microgrid Feeding an Electric Vehicle Charging Station

Sherif A. Zaid; Abualkasim Bakeer; Hani Albalawi; Aadel M. Alatwi; Hossam AbdelMeguid; Ahmed M. Kassem

doi:10.3390/fractalfract7090677

Fractal and Fractional (Sep 2023)

Optimal Fractional-Order Controller for the Voltage Stability of a DC Microgrid Feeding an Electric Vehicle Charging Station

Sherif A. Zaid,
Abualkasim Bakeer,
Hani Albalawi,
Aadel M. Alatwi,
Hossam AbdelMeguid,
Ahmed M. Kassem

Affiliations

Sherif A. Zaid: Electrical Engineering Department, Faculty of Engineering, University of Tabuk, Tabuk 47913, Saudi Arabia
Abualkasim Bakeer: Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt
Hani Albalawi: Electrical Engineering Department, Faculty of Engineering, University of Tabuk, Tabuk 47913, Saudi Arabia
Aadel M. Alatwi: Electrical Engineering Department, Faculty of Engineering, University of Tabuk, Tabuk 47913, Saudi Arabia
Hossam AbdelMeguid: Department of Mechanical Engineering, Faculty of Engineering, University of Tabuk, Tabuk 47913, Saudi Arabia
Ahmed M. Kassem: Electrical Engineering Department, Faculty of Engineering, Sohag University, Sohag 82524, Egypt

DOI: https://doi.org/10.3390/fractalfract7090677
Journal volume & issue: Vol. 7, no. 9
p. 677

Abstract

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Charging stations are regarded as the cornerstone of electric vehicle (EV) development and utilization. Electric vehicle charging stations (EVCSs) are now energized via standalone microgrids that utilize renewable energy sources and reduce the stress on the utility grid. However, the control and energy management of EVCSs are challenging tasks because they are nonlinear and time-varying. This study suggests a fractional-order proportional integral (FOPI) controller to improve the performance and energy management of a standalone EVCS microgrid. The microgrid is supplied mainly by photovoltaic (PV) energy and utilizes a battery as an energy storage system (ESS). The FOPI’s settings are best created utilizing the grey wolf optimization (GWO) method to attain the highest performance possible. The grey wolf is run for 100 iterations using 20 wolves. In addition, after 80 iterations for the specified goal function, the GWO algorithm almost discovers the ideal values. For changes in solar insolation, the performance of the proposed FOPI controller is compared with that of a traditional PI controller. The Matlab/Simulink platform models and simulates the EVCS’s microgrid. The results demonstrate that the suggested FOPI controller significantly improves the transient responsiveness of the EVCS performance compared to the standard PI controller. Despite all PV insolation disruptions, the EV battery continues to charge while the ESS battery precisely stores and balances PV energy changes. The results support the suggested FOPI control’s robustness to parameter mismatches. The microgrid’s efficiency fluctuations with the insolation level and state of charge of the EV battery are discussed.

Published in Fractal and Fractional

ISSN: 2504-3110 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science: Physics: Heat: Thermodynamics; Science: Mathematics: Analysis
Website: http://www.mdpi.com/journal/fractalfract

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