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This paper develops a linear predictor for application to wind speed and direction forecasting in time and across different sites. The wind speed and direction are modelled via the magnitude and phase of a complex-valued time-series. A multichannel adaptive filter is set to predict this signal, based on its past values and the spatio-temporal correlation between wind signals measured at numerous geographical locations. The time-varying nature of the underlying system and the annual cycle of seasons motivates the development of a cyclo-stationary Wiener filter, which is tested on hourly mean wind speed and direction data from 13 weather stations across the UK, and shown to provide an improvement over both stationary Wiener filtering and a recent auto-regressive approach.
|Number of pages||5|
|Publication status||Published - Sep 2013|
|Event||21st European Signal Processing Conference - Marrakech, Morocco|
Duration: 9 Sep 2013 → 13 Sep 2013
|Conference||21st European Signal Processing Conference|
|Period||9/09/13 → 13/09/13|
- complex multichannel
- wiener filter
- wind speed
- wind direction
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- 1 Finished
1/10/09 → 31/03/18
Project: Research - Studentship