Wind prediction enhancement by exploiting data non-stationarity
Wind prediction enhancement by exploiting data non-stationarity
- Author(s): A. Malvaldi ; J. Dowell ; S. Weiss ; D. Infield
- DOI: 10.1049/cp.2015.1795
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- Author(s): A. Malvaldi ; J. Dowell ; S. Weiss ; D. Infield Source: 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP), 2015 page ()
- Conference: 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP)
- DOI: 10.1049/cp.2015.1795
- ISBN: 978-1-78561-136-0
- Location: London, UK
- Conference date: 1-2 Dec. 2015
- Format: PDF
The short term forecasting of wind speed and direction has previously been improved by adopting a cyclo-stationary multichannel linear prediction approach which incorporated seasonal cycles into the estimation of statistics. This paper expands previous analysis by also incorporating diurnal variation and time-dependent window lengths. Based on a large data set from the UK's Met Ofjice, we demonstrate the impact of this proposed approach.
Inspec keywords: atmospheric techniques; estimation theory; wind
Subjects: Probability theory, stochastic processes, and statistics; Winds and their effects in the lower atmosphere; Atmospheric, ionospheric and magnetospheric techniques and equipment; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research; Other topics in statistics
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