LAPSE:2023.20542
Published Article
LAPSE:2023.20542
Optimal Operation of Park and Ride EV Stations in Island Operation with Model Predictive Control
March 20, 2023
The urgent need to reduce greenhouse gas emissions to achieve a decarbonized society has led to the active introduction of electric vehicles worldwide. Renewable energy sources that do not emit greenhouse gases during charging must also be used. However, the uncertainty in the supply of renewable energy is an issue that needs to be considered in practical applications. Therefore, in this study, we predicted the amount of electricity generated by renewable energy using model predictive control, and we considered the operation of a complete island-operated park and ride EV parking station that does not depend on commercial electricity. To perform appropriate model predictive control, we performed comparative simulations for several different forecast interval cases. Based on the obtained results, we determined the forecast horizon and we simulated the economic impact of implementing EV demand response on the electricity demand side. We found that without demand response, large amounts of electricity are recharged and a very high return on investment can be achieved, but with demand response, the return on investment is faster. The results provide a rationale for encouraging infrastructure development in areas that have not yet adopted electric vehicles.
Keywords
electric vehicle, microgrid, Model Predictive Control, park and ride, Renewable and Sustainable Energy
Suggested Citation
Ueda S, Yona A, Rangarajan SS, Collins ER, Takahashi H, Hemeida AM, Senjyu T. Optimal Operation of Park and Ride EV Stations in Island Operation with Model Predictive Control. (2023). LAPSE:2023.20542
Author Affiliations
Ueda S: Faculty of Engineering, University of the Ryukyus, Senbaru Nishihara-cho, Nakagami 903-0213, Japan [ORCID]
Yona A: Faculty of Engineering, University of the Ryukyus, Senbaru Nishihara-cho, Nakagami 903-0213, Japan [ORCID]
Rangarajan SS: Department of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru 560078, India; Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29631, USA [ORCID]
Collins ER: Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29631, USA; College of Engineering, Western Carolina University, Cullowhee, NC 28723, USA
Takahashi H: Fuji Electric Co., Ltd., Tokyo 141-0032, Japan
Hemeida AM: Department of Electrical Engineering, Aswan University, Aswan 82825, Egypt [ORCID]
Senjyu T: Faculty of Engineering, University of the Ryukyus, Senbaru Nishihara-cho, Nakagami 903-0213, Japan [ORCID]
Journal Name
Energies
Volume
16
Issue
5
First Page
2468
Year
2023
Publication Date
2023-03-05
Published Version
ISSN
1996-1073
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Original Submission
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PII: en16052468, Publication Type: Journal Article
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LAPSE:2023.20542
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doi:10.3390/en16052468
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