1. Prediction of Wind Speed Using Hybrid Techniques.
- Author
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Lopez, Luis, Oliveros, Ingrid, Torres, Luis, Ripoll, Lacides, Soto, Jose, Salazar, Giovanny, and Cantillo, Santiago
- Subjects
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WIND speed , *FORECASTING , *HILBERT-Huang transform , *STANDARD deviations , *SUPPORT vector machines , *WAVELETS (Mathematics) , *WIND forecasting - Abstract
This paper presents a methodology to calculate day-ahead wind speed predictions based on historical measurements done by weather stations. The methodology was tested for three locations: Colombia, Ecuador, and Spain. The data is input into the process in two ways: (1) As a single time series containing all measurements, and (2) as twenty-four separate parallel sequences, corresponding to the values of wind speed at each of the 24 h in the day over several months. The methodology relies on the use of three non-parametric techniques: Least-squares support vector machines, empirical mode decomposition, and the wavelet transform. Moreover, the traditional and simple auto-regressive model is applied. The combination of the aforementioned techniques results in nine methods for performing wind prediction. Experiments using a matlab implementation showed that the least-squares support vector machine using data as a single time series outperformed the other combinations, obtaining the least root mean square error (RMSE). [ABSTRACT FROM AUTHOR]
- Published
- 2020
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