A Comparison of long-term wind speed forecasting models / Petros P. Kritharas in Transactions of the ASME. Journal of solar energy engineering, Vol. 132 N° 4 (Novembre 2010)  

Public ISBD [article]  inTransactions of the ASME. Journal of solar energy engineering > Vol. 132 N° 4 (Novembre 2010) . - pp. [041008/1-8] Titre : A Comparison of long-term wind speed forecasting models Type de document : texte imprimé Auteurs : Petros P. Kritharas, Auteur ; Simon J. Watson, Auteur Année de publication : 2011 Article en page(s) : pp. [041008/1-8] Note générale : Energie Solaire Langues : Anglais (eng) Mots-clés : Forecasting theory Maintenance engineering Purchasing Scheduling Time series Wind power Index. décimale : 621.47 Résumé : This paper presents a time series analysis of historical observations of wind speed in order to project future wind speed trends. For this study, 52 years of data have been used from seven suitable stations across the UK. Four parsimonious models have been employed, and the data were split into two different segments: the training and the validation data sets. During the fitting process, the optimum parameters for each model were determined in order to minimize the mean square error in the predictions. The results suggest that the seasonal pattern in wind speeds is the most important factor but that there is some monthly autocorrelation in the data, which can improve forecasts. This is confirmed by testing the four models with the model having considered both autocorrelation and seasonality achieving the smallest errors. The approach proposed for forecasting wind speeds a month ahead may be deemed useful to suppliers for purchasing base load in advance and to system operators for power system maintenance scheduling up to a month ahead. DEWEY : 621.47 ISSN : 0199-6231 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JSEEDO00013200 [...] [article] A Comparison of long-term wind speed forecasting models [texte imprimé] / Petros P. Kritharas, Auteur ; Simon J. Watson, Auteur . - 2011 . - pp. [041008/1-8]. Energie Solaire Langues : Anglais (eng) in Transactions of the ASME. Journal of solar energy engineering > Vol. 132 N° 4 (Novembre 2010) . - pp. [041008/1-8] Mots-clés : Forecasting theory Maintenance engineering Purchasing Scheduling Time series Wind power Index. décimale : 621.47 Résumé : This paper presents a time series analysis of historical observations of wind speed in order to project future wind speed trends. For this study, 52 years of data have been used from seven suitable stations across the UK. Four parsimonious models have been employed, and the data were split into two different segments: the training and the validation data sets. During the fitting process, the optimum parameters for each model were determined in order to minimize the mean square error in the predictions. The results suggest that the seasonal pattern in wind speeds is the most important factor but that there is some monthly autocorrelation in the data, which can improve forecasts. This is confirmed by testing the four models with the model having considered both autocorrelation and seasonality achieving the smallest errors. The approach proposed for forecasting wind speeds a month ahead may be deemed useful to suppliers for purchasing base load in advance and to system operators for power system maintenance scheduling up to a month ahead. DEWEY : 621.47 ISSN : 0199-6231 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JSEEDO00013200 [...]

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