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Prediction of charging demand of electric city buses of Helsinki, Finland by random forest
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Deb, Sanchari and Gao, Xiao-Zhi (2022) Prediction of charging demand of electric city buses of Helsinki, Finland by random forest. Energies, 15 (10). 3679. doi:10.3390/en15103679 ISSN 1996-1073.
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Official URL: http://dx.doi.org/10.3390/en15103679
Abstract
Climate change, global warming, pollution, and energy crisis are the major growing concerns of this era, which have initiated the electrification of transport. The electrification of roadway transport has the potential to drastically reduce pollution and the growing demand for energy and to increase the load demand of the power grid, thereby giving a rise to technological and commercial challenges. Thus, charging load prediction is a crucial and demanding issue for maintaining the security and stability of power systems. During recent years, random forest has gained a lot of popularity as a powerful machine learning technique for classification as well as regression analysis. This work develops a random forest (RF)-based approach for predicting charging demand. The proposed method is validated for the prediction of public e-bus charging demand in the city of Helsinki, Finland. The simulation results demonstrate the effectiveness of our scheme.
Item Type: | Journal Article | ||||||||
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Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
Library of Congress Subject Headings (LCSH): | Buses, Electric -- Finland, Urban transportation -- Finland, Battery charging stations (Electric vehicles), Electric vehicles -- Power supply -- Finland, Electric automobiles -- Power supply -- Finland, Electric discharges, Smart power grids | ||||||||
Journal or Publication Title: | Energies | ||||||||
Publisher: | M.D.P.I.A.G. | ||||||||
ISSN: | 1996-1073 | ||||||||
Official Date: | 17 May 2022 | ||||||||
Dates: |
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Volume: | 15 | ||||||||
Number: | 10 | ||||||||
Number of Pages: | 18 | ||||||||
Article Number: | 3679 | ||||||||
DOI: | 10.3390/en15103679 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 28 June 2022 | ||||||||
Date of first compliant Open Access: | 28 June 2022 |
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