Wind Speed Forecasting Based on Least Squares Support Vector Machine and Particle Swarm Optimization

Jun Zhang

doi:10.4028/www.scientific.net/AMM.602-605.3251

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Wind Speed Forecasting Based on Least Squares...

Wind Speed Forecasting Based on Least Squares Support Vector Machine and Particle Swarm Optimization

Abstract:

This paper is based on Least Squares Support Vector Machine theory to build the wind speed forecasting model. Meanwhile, as there is still no effective choice method of Least Squares Support Vector Ma-chine parameter, this paper tried to use Particle Swarm Optimization theory to optimization choice for parameter. And last, use wind farm observed wind speed (sampling interval is 1 minute) of three days to forecast the next minute wind speed through this paper's wind forecasting model, and prediction result is that the MAPE is only 4.63%, the prediction effect is relative ideal, confirm the feasibility of applying the Particle Swarm Optimization Algorithm and Least Squares Support Vector Machine theory to forecast the wind speed, it will provide theoretical support to wind farm layout and wind power forecasting and so on.

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Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

3251-3255

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.3251

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Online since:

August 2014

Authors:

Jun Zhang*

Keywords:

Least Squares Support Vector Machine, Particle Swarm Optimization Algorithm, Wind Power, Wind Speed Forecasting

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* - Corresponding Author

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