LAPSE:2023.6234v1
Published Article
LAPSE:2023.6234v1
Adaptive Mixed-Integer Linear Programming-Based Energy Management System of Fast Charging Station with Nuclear−Renewable Hybrid Energy System
Abu Bakar Siddique, Hossam A. Gabbar
February 23, 2023
Abstract
The concept of transportation electrification is proliferating due to its high impact on emission reduction. However, the increased usage of electric vehicles strains the power grid’s charging infrastructure. As a result, to reduce demand on the power grid, lower the emissions, and solve the intermittency problem of Renewable Energy Sources (RESs), a Nuclear−renewable Hybrid Energy System (N-R HES) is proposed in this research to support the load demand of a Fast Charging Station (FCS). Fulfilling the power demand of the FCS while reducing the generation cost and waste of energy is a vital issue, and hence, energy management with optimization is a must for the hybrid energy system. To address this issue, a model reference adaptive control with a mixed-integer linear programming-based energy management method was modelled to accomplish the charging station’s extensive performance. MATLAB/Simulink software has been used to model and simulate the proposed system, and the results are analyzed. The assessment shows that the proposed energy management system offers an optimized performance of the fast charging station integrating with nuclear and renewable energy.
Keywords
adaptive control, energy management system, fast charging station, mixed-integer linear programming, nuclear–renewable hybrid energy system, Optimization
Suggested Citation
Siddique AB, Gabbar HA. Adaptive Mixed-Integer Linear Programming-Based Energy Management System of Fast Charging Station with Nuclear−Renewable Hybrid Energy System. (2023). LAPSE:2023.6234v1
Author Affiliations
Siddique AB: Faculty of Energy Systems and Nuclear Science, Ontario Tech University (UOIT), Oshawa, ON L1H 7K4, Canada
Gabbar HA: Faculty of Energy Systems and Nuclear Science, Ontario Tech University (UOIT), Oshawa, ON L1H 7K4, Canada; Faculty of Engineering and Applied Science, Ontario Tech University (UOIT), Oshawa, ON L1H 7K4, Canada [ORCID]
Journal Name
Energies
Volume
16
Issue
2
First Page
685
Year
2023
Publication Date
2023-01-06
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en16020685, Publication Type: Journal Article
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LAPSE:2023.6234v1
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https://doi.org/10.3390/en16020685
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