Wind Speed Forecasting Using Hybrid Wavelet Transform—ARMA Techniques

Wind Speed Forecasting Using Hybrid Wavelet Transform—ARMA Techniques

The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT) along with the Auto Regressive Moving Average (ARMA) is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Predicti...

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Bibliographic Details
Main Authors: Diksha Kaur, Tek Tjing Lie, Nirmal K. C. Nair, Brice Vallès
Format: Article
Language:English
Published: AIMS Press 2015-01-01
Series:AIMS Energy
Subjects:
Wind Speed Forecasting
Wavelet Transform
ARMA
MATLAB
Online Access:http://www.aimspress.com/energy/article/30/fulltext.html
Description
Summary:The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT) along with the Auto Regressive Moving Average (ARMA) is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Prediction Error (MAPE). A simulation study has been conducted by comparing the forecasting results using the Wavelet-ARMA with the ARMA and Artificial Neural Network (ANN)-Ensemble Kalman Filter (EnKF) hybrid technique to verify the effectiveness of the proposed hybrid method. Results of the proposed hybrid show significant improvements in the forecasting error.
ISSN:2333-8334

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