Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)

The Research of Power Quality Prediction and Evaluation Method for the Large-scale Charging Load

Authors
Tianyi Qu, Kui Chen
Corresponding Author
Tianyi Qu
Available Online September 2016.
DOI
10.2991/meici-16.2016.106How to use a DOI?
Keywords
Electric vehicle; Charging load; Power quality; Prediction; Evaluation
Abstract

Combined with the project of the development guidelines for charging infrastructure of the electric car (2015-2016) and the plan of Distribution network's construction and renovation action(2015-2020),this article is predicted and evaluated to power quality of the large-scale electric vehicle total charging load with the energy gravity method and classification disturbance method . The results of prediction and evaluation hasÿtheÿgood referenceÿvalueÿtoÿresearch and plan the charging load accessing and related measures of the large-scale electric vehicle.

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/).

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Volume Title
Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
Series
Advances in Intelligent Systems Research
Publication Date
September 2016
ISBN
10.2991/meici-16.2016.106
ISSN
1951-6851
DOI
10.2991/meici-16.2016.106How to use a DOI?
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  - Kui Chen
PY  - 2016/09
DA  - 2016/09
TI  - The Research of Power Quality Prediction and Evaluation Method for the Large-scale Charging Load
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 507
EP  - 511
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.106
DO  - 10.2991/meici-16.2016.106
ID  - Qu2016/09
ER  -