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RICCARDO BURLON

Wind Speed Forecasting

  • Authors: Bonanno, G; Burlon, R; Gurrera, D
  • Publication year: 2009
  • Type: Articolo in rivista (Articolo in rivista)
  • Key words: arima, forecasting, weather
  • OA Link: http://hdl.handle.net/10447/51185

Abstract

This paper aims at providing a general class of stochastic models for hourly average wind speed time series taking into account all the main features of wind speed data, namely autocorrelation, non-Gaussian distribution, seasonal and diurnal nonstationarity. It will be shown that the methodology developed in this study, tested using the data recorded in two sites of Italy, attains valuable results in terms both of modelling and forecasting.