Study on Identification of Wind Turbine Power Characteristic Curve by Genetic Algorithm

Jia An Zhang; Xin Yi Meng; Lin Lin Wu; Hai Xiang Xu; Ning Liu; Hai Feng Liu; Xuan Li; Yan Hong Gao; Zi Mei Sun; Sheng Nan Zhang

doi:10.4028/www.scientific.net/AMR.1070-1072.270

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1070-1072Study on Identification of Wind Turbine Power...

Study on Identification of Wind Turbine Power Characteristic Curve by Genetic Algorithm

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 1070-1072)

Pages:

270-274

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1070-1072.270

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Online since:

December 2014

Authors:

Jia An Zhang, Xin Yi Meng, Lin Lin Wu, Hai Xiang Xu, Ning Liu, Hai Feng Liu, Xuan Li, Yan Hong Gao, Zi Mei Sun, Sheng Nan Zhang

Keywords:

Genetic Algorithm (GA), Linearization, Parameter Identification, Wind Power, Wind Turbine Characteristic Curve

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