| Autor: |
Xuan Li, Ning Liu, Hai Xiang Xu, Xin Yi Meng, Jia An Zhang, Yan Hong Gao, Sheng Nan Zhang, Lin Lin Wu, Hai Feng Liu, Zi Mei Sun |
| Rok vydání: |
2014 |
| Předmět: |
|
| Zdroj: |
Advanced Materials Research. :270-274 |
| ISSN: |
1662-8985 |
| DOI: |
10.4028/www.scientific.net/amr.1070-1072.270 |
| Popis: |
Wind turbine power characteristic curve is not only an important indicator to assess the performance of wind turbine and evaluate the power generation performance, but also an important factor of impacting the wind power prediction accuracy. In this article, an identification method of the wind turbine power characteristic curve based on the genetic algorithm is proposed. With the piecewise linearization method, the wind turbine power characteristic curve is divided into several sections that can be described by linear or quadratic functions. Data preprocessing is used to filter the abnormal points in the original data. The distance from the wind turbine operating points to the power characteristic curve is selected as the fitness function. The identification process is to look for the parameters of the linear or quadratic curves that have the shortest distance to the massive operating points. The effectiveness of the algorithm is verified through the computation of a wind farm data. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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