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
- 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 .
- Copyright
- © 2016, 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 AU - Xiaofang Cao PY - 2016/05 DA - 2016/05 TI - Electric Vehicle Charging Load Forecasting Based on ACO and Monte Carlo Algorithms BT - Proceedings of the 2016 International Conference on Education, Management and Computer Science PB - Atlantis Press SP - 126 EP - 130 SN - 1951-6851 UR - https://doi.org/10.2991/icemc-16.2016.26 DO - 10.2991/icemc-16.2016.26 ID - Qu2016/05 ER -