Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)

Predicting Charging Load of Pure Electric Buses Based on Multi-distribution Statistics

Authors
TianYi Qu
Corresponding Author
TianYi Qu
Available Online October 2018.
DOI
10.2991/icmcs-18.2018.71How to use a DOI?
Keywords
Pure electric buses; Combination of fast and slow speed; Charging mode; Monte Carlo load forecasting
Abstract

Compared with family cars and taxis, buses have more regular features such as driving time, space, and distance. In a large number of statistics on the running and charging rules of pure electric buses, and on the basis of fully considering the power consumption and opening time of the hot and cold air-conditioning of pure electric buses, hybrid charging mode ,the combination of the normal nighttime charging for a pure electric bus and the fast charging during work, is obtained. Monte Carlo method is used to predict the charging load of pure electric vehicles, which provides a reference for the grid to formulate relevant countermeasures to reduce the impact of electric vehicle access on the grid.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)
Series
Advances in Computer Science Research
Publication Date
October 2018
ISBN
978-94-6252-590-0
ISSN
2352-538X
DOI
10.2991/icmcs-18.2018.71How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - TianYi Qu
PY  - 2018/10
DA  - 2018/10
TI  - Predicting Charging Load of Pure Electric Buses Based on Multi-distribution Statistics
BT  - Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)
PB  - Atlantis Press
SP  - 353
EP  - 355
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmcs-18.2018.71
DO  - 10.2991/icmcs-18.2018.71
ID  - Qu2018/10
ER  -