Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)

Research on Fusion Model Characteristics of Wind Farm

Authors
Qianli Ma, Xuemin Zhang
Corresponding Author
Qianli Ma
Available Online March 2018.
DOI
10.2991/jiaet-18.2018.34How to use a DOI?
Keywords
wind farm characteristics;simplified model;Short circuit fault;SVR algorithm
Abstract

Wind farm characteristics is the basis of the research on wind power grid operation and control. The main purpose of this paper is to establish a simplified structure, which is a high security, easy maintenance wind farm model. This model can calculate accurate response in the grid disturbance. The idea of modeling is mainly based on the feature fusion method, which is extracted from the detailed model and calculated by SVR algorithm to get parameters.The accuracy of the simplified model analysised by comparing the transient response during grid disturbance. 1

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/).

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Volume Title
Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)
Series
Advances in Engineering Research
Publication Date
March 2018
ISBN
10.2991/jiaet-18.2018.34
ISSN
2352-5401
DOI
10.2991/jiaet-18.2018.34How 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  - Qianli Ma
AU  - Xuemin Zhang
PY  - 2018/03
DA  - 2018/03
TI  - Research on Fusion Model Characteristics of Wind Farm
BT  - Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)
PB  - Atlantis Press
SP  - 195
EP  - 201
SN  - 2352-5401
UR  - https://doi.org/10.2991/jiaet-18.2018.34
DO  - 10.2991/jiaet-18.2018.34
ID  - Ma2018/03
ER  -