Comparisons of the accuracy of different wake models in wind farm layout optimization
Accurate wake model in wind farm layout optimization can help extracting maximum power generation, minimizing cost of energy and prolonging wind turbines’ lifetime as well. With the development of different wake models, the wind farm layout optimization results based on the models should be updated....
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2020-09-01
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Series: | Energy Exploration & Exploitation |
Online Access: | https://doi.org/10.1177/0144598720942852 |
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doaj-ec5b4037742d45e8b11452595e31df7b2020-11-25T04:05:31ZengSAGE PublishingEnergy Exploration & Exploitation0144-59872048-40542020-09-013810.1177/0144598720942852Comparisons of the accuracy of different wake models in wind farm layout optimizationXiaoxia GaoYue LiFei ZhaoHaiying SunAccurate wake model in wind farm layout optimization can help extracting maximum power generation, minimizing cost of energy and prolonging wind turbines’ lifetime as well. With the development of different wake models, the wind farm layout optimization results based on the models should be updated. This paper investigates the performances of four wake models in wind farm layout optimization using multi-population genetic algorithm (MPGA) with the wind farm power generation, COST/AEP and wind farm efficiency been reported. Comparison of results between typical wake models’ performance shows that Jensen’s wake model reported a higher wind farm power generation and efficiency because it underestimates the velocity deficit in the wake, and to the contrary, in the Frandsen wake model, the velocity in the wake is underestimated, resulting in a deceased power generation. The expression of 2D_k model shall be out of work in complicated wind condition. The 2D Jensen–Gaussian wake model performed better in the wind farm layout optimization using the MPGA program which can be promoted in real-world wind farm micrositing.https://doi.org/10.1177/0144598720942852 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaoxia Gao Yue Li Fei Zhao Haiying Sun |
spellingShingle |
Xiaoxia Gao Yue Li Fei Zhao Haiying Sun Comparisons of the accuracy of different wake models in wind farm layout optimization Energy Exploration & Exploitation |
author_facet |
Xiaoxia Gao Yue Li Fei Zhao Haiying Sun |
author_sort |
Xiaoxia Gao |
title |
Comparisons of the accuracy of different wake models in wind farm layout optimization |
title_short |
Comparisons of the accuracy of different wake models in wind farm layout optimization |
title_full |
Comparisons of the accuracy of different wake models in wind farm layout optimization |
title_fullStr |
Comparisons of the accuracy of different wake models in wind farm layout optimization |
title_full_unstemmed |
Comparisons of the accuracy of different wake models in wind farm layout optimization |
title_sort |
comparisons of the accuracy of different wake models in wind farm layout optimization |
publisher |
SAGE Publishing |
series |
Energy Exploration & Exploitation |
issn |
0144-5987 2048-4054 |
publishDate |
2020-09-01 |
description |
Accurate wake model in wind farm layout optimization can help extracting maximum power generation, minimizing cost of energy and prolonging wind turbines’ lifetime as well. With the development of different wake models, the wind farm layout optimization results based on the models should be updated. This paper investigates the performances of four wake models in wind farm layout optimization using multi-population genetic algorithm (MPGA) with the wind farm power generation, COST/AEP and wind farm efficiency been reported. Comparison of results between typical wake models’ performance shows that Jensen’s wake model reported a higher wind farm power generation and efficiency because it underestimates the velocity deficit in the wake, and to the contrary, in the Frandsen wake model, the velocity in the wake is underestimated, resulting in a deceased power generation. The expression of 2D_k model shall be out of work in complicated wind condition. The 2D Jensen–Gaussian wake model performed better in the wind farm layout optimization using the MPGA program which can be promoted in real-world wind farm micrositing. |
url |
https://doi.org/10.1177/0144598720942852 |
work_keys_str_mv |
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