Proceedings of the 2018 International Conference on Energy Development and Environmental Protection (EDEP 2018)

Analysis of Problems in Wind Power Generation Based on Artificial Intelligence

Authors
Jia-Jun ZHANG, Xin-Yan ZHANG, Liang GAO, Tao TONG
Corresponding Author
Jia-Jun ZHANG
Available Online October 2018.
DOI
10.2991/edep-18.2018.5How to use a DOI?
Keywords
New energy utilization, Artificial intelligence, Wind power generation, Fault diagnosis.
Abstract

Wind energy is widely used as clean, renewable and mature new energy. However, the inhomogeneity and non-steady state of the operating environment of the wind turbine lead to the randomness of the load, which will cause the fluctuation of the voltage and frequency of the power grid, and affect the power quality of the power grid; the wind turbine will also have various faults, which will cause the unit to stop and reduce the utilization rate of the unit. Artificial intelligence technology can diagnose and predict wind power for wind turbines, so that new energy can be better complemented with traditional hydro thermal power. Finally, an example of fault diagnosis of daily monitoring data of doubly fed induction generator in Dabancheng, Xinjiang is given to demonstrate the application of artificial intelligence technology in wind power generation.

Copyright
© 2018, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2018 International Conference on Energy Development and Environmental Protection (EDEP 2018)
Series
Advances in Engineering Research
Publication Date
October 2018
ISBN
10.2991/edep-18.2018.5
ISSN
2352-5401
DOI
10.2991/edep-18.2018.5How to use a DOI?
Copyright
© 2018, 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  - Jia-Jun ZHANG
AU  - Xin-Yan ZHANG
AU  - Liang GAO
AU  - Tao TONG
PY  - 2018/10
DA  - 2018/10
TI  - Analysis of Problems in Wind Power Generation Based on Artificial Intelligence
BT  - Proceedings of the 2018 International Conference on Energy Development and Environmental Protection (EDEP 2018)
PB  - Atlantis Press
SP  - 26
EP  - 30
SN  - 2352-5401
UR  - https://doi.org/10.2991/edep-18.2018.5
DO  - 10.2991/edep-18.2018.5
ID  - ZHANG2018/10
ER  -