Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

Optimization Model of Wind Farm

Authors
Xueying Ding
Corresponding Author
Xueying Ding
Available Online May 2017.
DOI
10.2991/msmee-17.2017.202How to use a DOI?
Keywords
wind farm optimization farm wake model cost-benefit model wind farm incremental capacity evaluation model Niche Genetic Algorithm
Abstract

For the optimization of wind farm layout, the model of fan wake model, fan cost - benefit model and wind farm incremental capacity evaluation model are established in this paper. The simulation of the wake effect of the wind turbine is the basis for the prediction of the generation efficiency of the wind farm. The cost-benefit model of the wind farm is used to calculate the cost of the wind turbine with the installed cost of the fan. The wind farm incremental capacity evaluation model is used to analyze the comparative evaluation of the selected different fan arrangement. And finally determine the optimal arrangement of the fan for a given area wind farm.

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 Materials Science, Machinery and Energy Engineering (MSMEE 2017)
Series
Advances in Engineering Research
Publication Date
May 2017
ISBN
978-94-6252-346-3
ISSN
2352-5401
DOI
10.2991/msmee-17.2017.202How 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  - Xueying Ding
PY  - 2017/05
DA  - 2017/05
TI  - Optimization Model of Wind Farm
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 1039
EP  - 1042
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.202
DO  - 10.2991/msmee-17.2017.202
ID  - Ding2017/05
ER  -