Applying Wavelet Filters in Wind Forecasting Methods
Wind is a physical phenomenon with uncertainties in several temporal scales, in addition, measured wind time series have noise superimposed on them. These time series are the basis for forecasting methods. This paper studied the application of the wavelet transform to three forecasting methods, name...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/11/3181 |
| _version_ | 1797532114221006848 |
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| author | José A. Domínguez-Navarro Tania B. Lopez-Garcia Sandra Minerva Valdivia-Bautista |
| author_facet | José A. Domínguez-Navarro Tania B. Lopez-Garcia Sandra Minerva Valdivia-Bautista |
| author_sort | José A. Domínguez-Navarro |
| collection | DOAJ |
| description | Wind is a physical phenomenon with uncertainties in several temporal scales, in addition, measured wind time series have noise superimposed on them. These time series are the basis for forecasting methods. This paper studied the application of the wavelet transform to three forecasting methods, namely, stochastic, neural network, and fuzzy, and six wavelet families. Wind speed time series were first filtered to eliminate the high-frequency component using wavelet filters and then the different forecasting methods were applied to the filtered time series. All methods showed important improvements when the wavelet filter was applied. It is important to note that the application of the wavelet technique requires a deep study of the time series in order to select the appropriate family and filter level. The best results were obtained with an optimal filtering level and improper selection may significantly affect the accuracy of the results. |
| first_indexed | 2024-03-10T10:54:30Z |
| format | Article |
| id | doaj.art-467b22211ac44115bd504f51c648eac7 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T10:54:30Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-467b22211ac44115bd504f51c648eac72023-11-21T21:57:03ZengMDPI AGEnergies1996-10732021-05-011411318110.3390/en14113181Applying Wavelet Filters in Wind Forecasting MethodsJosé A. Domínguez-Navarro0Tania B. Lopez-Garcia1Sandra Minerva Valdivia-Bautista2Department of Electrical Engineering, EINA, University of Zaragoza, 50018 Zaragoza, SpainDepartment of Electrical Engineering, EINA, University of Zaragoza, 50018 Zaragoza, SpainCentro Universitario de Ciencias e Ingenierías (CUCEI), Universidad de Guadalajara (UDG), Guadalajara 44160, MexicoWind is a physical phenomenon with uncertainties in several temporal scales, in addition, measured wind time series have noise superimposed on them. These time series are the basis for forecasting methods. This paper studied the application of the wavelet transform to three forecasting methods, namely, stochastic, neural network, and fuzzy, and six wavelet families. Wind speed time series were first filtered to eliminate the high-frequency component using wavelet filters and then the different forecasting methods were applied to the filtered time series. All methods showed important improvements when the wavelet filter was applied. It is important to note that the application of the wavelet technique requires a deep study of the time series in order to select the appropriate family and filter level. The best results were obtained with an optimal filtering level and improper selection may significantly affect the accuracy of the results.https://www.mdpi.com/1996-1073/14/11/3181wavelet transformsforecasting methodswind energy |
| spellingShingle | José A. Domínguez-Navarro Tania B. Lopez-Garcia Sandra Minerva Valdivia-Bautista Applying Wavelet Filters in Wind Forecasting Methods Energies wavelet transforms forecasting methods wind energy |
| title | Applying Wavelet Filters in Wind Forecasting Methods |
| title_full | Applying Wavelet Filters in Wind Forecasting Methods |
| title_fullStr | Applying Wavelet Filters in Wind Forecasting Methods |
| title_full_unstemmed | Applying Wavelet Filters in Wind Forecasting Methods |
| title_short | Applying Wavelet Filters in Wind Forecasting Methods |
| title_sort | applying wavelet filters in wind forecasting methods |
| topic | wavelet transforms forecasting methods wind energy |
| url | https://www.mdpi.com/1996-1073/14/11/3181 |
| work_keys_str_mv | AT joseadomingueznavarro applyingwaveletfiltersinwindforecastingmethods AT taniablopezgarcia applyingwaveletfiltersinwindforecastingmethods AT sandraminervavaldiviabautista applyingwaveletfiltersinwindforecastingmethods |