Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
Document Type
Article
Publication Date
4-1-2021
Abstract
Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Integrated Moving Average (ARIMA), Simple Exponential Smoothing (SES) and a hybrid model combination of ARIMA and SES will be used in this study to predict the wind speed. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) are used as measurement of efficiency. The hybrid model provides a positive outcome for predicting wind speed compare to the single model of ARIMA and SES. © 2021. All Rights Reserved.
Keywords
ARIMA model, Hybrid time series model, Wind energy, Wind speed forecasting
Divisions
foundation
Funders
Universiti Teknologi Malaysia [Grant No.: QJ130000.2654.17J90]
Publication Title
Mathematical Modelling of Engineering Problems (MMEP)
Volume
8
Issue
2
Publisher
International Information and Engineering Technology Association (IIETA)