Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Elevator Regenerative Energy Feedback Technology

Authors
Peng Gao, Weifei Niu, Zhuojun Quanji, Yang Yang, Yinghui Lv
Corresponding Author
Peng Gao
Available Online November 2016.
DOI
10.2991/aiea-16.2016.33How to use a DOI?
Keywords
Elevator, Regenerative energy feedback, Regenerative energy storage.
Abstract

Elevator regenerative energy feedback technology is an important method of reducing energy consumption. Elevator regenerative energy feedback technology includes energy feedback system structures and feedback energy storage methods. This article introduces the feedback system structures and energy storage methods. The dual PWM regenerative energy feedback circuitry and plug-in regenerative energy feedback system are analyzed, and their different characteristics are concluded; the battery and the supercapacitor energy storage methods are discussed and the novel technology on the energy storage is described. This paper aims to introduce different structures and storage methods to help deepen the further understanding on the elevator energy feedback technology.

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 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
10.2991/aiea-16.2016.33
ISSN
2352-538X
DOI
10.2991/aiea-16.2016.33How 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  - Peng Gao
AU  - Weifei Niu
AU  - Zhuojun Quanji
AU  - Yang Yang
AU  - Yinghui Lv
PY  - 2016/11
DA  - 2016/11
TI  - Elevator Regenerative Energy Feedback Technology
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 176
EP  - 183
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.33
DO  - 10.2991/aiea-16.2016.33
ID  - Gao2016/11
ER  -