LAPSE:2023.20970
Published Article

LAPSE:2023.20970
Intelligent Control of Converter for Electric Vehicles Charging Station
March 21, 2023
Abstract
Electric vehicles (EVs) are envisaged to be the future transportation medium, and demonstrate energy efficiency levels much higher than conventional gasoline or diesel-based vehicles. However, the sustainability of EVs is only justified if the electricity used to charge these EVs is availed from a sustainable source of energy and not from any fossil fuel or carbon generating source. In this paper, the challenges of the EV charging stations are discussed while highlighting the growing use of distributed generators in the modern electrical grid system. The benefits of the adoption of photovoltaic (PV) sources along with battery storage devices are studied. A multiport converter is proposed for integrating the PV, charging docks, and energy storage device (ESD) with the grid system. In order to control the bidirectional flow between the generating sources and the loads, an intelligent energy management system is proposed by adapting particle swarm optimization for efficient switching between the sources. The proposed system is simulated using MATLAB/Simulink environment, and the results depicted fast switching between the sources and less switching time without obstructing the fast charging to the EVs.
Electric vehicles (EVs) are envisaged to be the future transportation medium, and demonstrate energy efficiency levels much higher than conventional gasoline or diesel-based vehicles. However, the sustainability of EVs is only justified if the electricity used to charge these EVs is availed from a sustainable source of energy and not from any fossil fuel or carbon generating source. In this paper, the challenges of the EV charging stations are discussed while highlighting the growing use of distributed generators in the modern electrical grid system. The benefits of the adoption of photovoltaic (PV) sources along with battery storage devices are studied. A multiport converter is proposed for integrating the PV, charging docks, and energy storage device (ESD) with the grid system. In order to control the bidirectional flow between the generating sources and the loads, an intelligent energy management system is proposed by adapting particle swarm optimization for efficient switching between the sources. The proposed system is simulated using MATLAB/Simulink environment, and the results depicted fast switching between the sources and less switching time without obstructing the fast charging to the EVs.
Record ID
Keywords
Electric Vehicle (EV), Energy Storage Device (ESD), Grid Connected Photovoltaic Systems (GCPVS), Intelligent Energy Management System (iEMS), Multiport Converter (MPC)
Subject
Suggested Citation
Jha M, Blaabjerg F, Khan MA, Bharath Kurukuru VS, Haque A. Intelligent Control of Converter for Electric Vehicles Charging Station. (2023). LAPSE:2023.20970
Author Affiliations
Jha M: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India
Blaabjerg F: Department of Energy Technology, Aalborg University, Aalborg 9220, Denmark [ORCID]
Khan MA: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India [ORCID]
Bharath Kurukuru VS: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India [ORCID]
Haque A: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India [ORCID]
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Blaabjerg F: Department of Energy Technology, Aalborg University, Aalborg 9220, Denmark [ORCID]
Khan MA: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India [ORCID]
Bharath Kurukuru VS: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India [ORCID]
Haque A: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India [ORCID]
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Journal Name
Energies
Volume
12
Issue
12
Article Number
E2334
Year
2019
Publication Date
2019-06-18
ISSN
1996-1073
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Original Submission
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PII: en12122334, Publication Type: Journal Article
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LAPSE:2023.20970
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https://doi.org/10.3390/en12122334
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Mar 21, 2023
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