Soft Measures to Improve the Wind Speed Prediction Capability in Wind Farm

Ya Lan Yang; Yao Liang Xu; Shao Shan Zhong

doi:10.4028/www.scientific.net/AMR.718-720.439

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 718-720Soft Measures to Improve the Wind Speed Prediction...

Soft Measures to Improve the Wind Speed Prediction Capability in Wind Farm

Abstract:

For decreasing the error of wind speed prediction in wind farm, improvements from the aspects of arithmetic, space and time has been proposed based on the soft sensor. Support Vector Machine as the basic prediction method is used to analyze. MRA-SVM testify the improvement of algorithm can increase the performance targets.The modified model about meteorological information achieves the space continuity and the cascading of turbines profits the time continuity. Based the actual measured data, the calculated result shows that it is feasible to improve the wind speed prediction from the aspects of algorithm, space and time.

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Periodical:

Advanced Materials Research (Volumes 718-720)

Pages:

439-444

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.718-720.439

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Online since:

July 2013

Authors:

Ya Lan Yang, Yao Liang Xu, Shao Shan Zhong

Keywords:

Algorithm (GA), Space Continuity, Support Vector Machine (SVM), Time Continuity, Wind Speed Prediction

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