Proceedings of the 2016 International Conference on Education, Management and Computer Science

Electric Vehicle Charging Load Forecasting Based on ACO and Monte Carlo Algorithms

Authors
Tianyi Qu, Xiaofang Cao
Corresponding Author
Tianyi Qu
Available Online May 2016.
DOI
https://doi.org/10.2991/icemc-16.2016.26How to use a DOI?
Keywords
Electric vehicle; Charging load; Ant colony algorithm; Monte carlo simulation algorithm; Fault line selection; Ground fault
Abstract
The Electric Vehicle Charging Infrastructure Development Guide (2015-2020) and The Action Plan of Distribution Network Construction Reforming (2015-2020) have been analyzed and comprehended . Based on meeting a lot of rapid development of electric vehicle charging load, the optimal operation method of introducing the scale electric vehicle charging infrastructure is studied from the distribution network of safe, reliability and economic operation, which improve safety and efficiency in planning scale electric vehicle charging load to distribution network and charging facilities .
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Proceedings
2016 International Conference on Education, Management and Computer Science
Part of series
Advances in Intelligent Systems Research
Publication Date
May 2016
ISBN
978-94-6252-202-2
ISSN
1951-6851
DOI
https://doi.org/10.2991/icemc-16.2016.26How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Tianyi Qu
AU  - Xiaofang Cao
PY  - 2016/05
DA  - 2016/05
TI  - Electric Vehicle Charging Load Forecasting Based on ACO and Monte Carlo Algorithms
BT  - 2016 International Conference on Education, Management and Computer Science
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icemc-16.2016.26
DO  - https://doi.org/10.2991/icemc-16.2016.26
ID  - Qu2016/05
ER  -