Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

Study on the Performance of Light Sources under Voltage Sag and the Compensation Method

Authors
Binbin Li, Taiyun Zhu, Dengfeng Cheng, Wei Yang, Yanguo Ke, Sha Luo, Shenglong Zhu, Yu Tian, Changwei Zhao
Corresponding Author
Binbin Li
Available Online June 2017.
DOI
10.2991/caai-17.2017.53How to use a DOI?
Keywords
gas discharge lamp; voltage sag; compensation device; drop amplitude; phase angle
Abstract

All kinds of light sources are sensitive to the power supply, which may be shut down when the grid voltage sag or cut off. It will take more than ten minutes for gas discharge lamps to restart due to their cold start features. In this paper, several typical light sources are selected to do voltage drop tests under different amplitude and phase angle, in which the performance of lamps are carried out. Then a compensation method is presented for HID lamps.

Copyright
© 2017, 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 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
10.2991/caai-17.2017.53
ISSN
1951-6851
DOI
10.2991/caai-17.2017.53How to use a DOI?
Copyright
© 2017, 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  - Binbin Li
AU  - Taiyun Zhu
AU  - Dengfeng Cheng
AU  - Wei Yang
AU  - Yanguo Ke
AU  - Sha Luo
AU  - Shenglong Zhu
AU  - Yu Tian
AU  - Changwei Zhao
PY  - 2017/06
DA  - 2017/06
TI  - Study on the Performance of Light Sources under Voltage Sag and the Compensation Method
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 238
EP  - 241
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.53
DO  - 10.2991/caai-17.2017.53
ID  - Li2017/06
ER  -