Wind prediction enhancement by exploiting data non-stationarity

Malvaldi, Alice and Dowell, Jethro and Weiss, Stephan and Infield, David; (2016) Wind prediction enhancement by exploiting data non-stationarity. In: 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP). IET, GBR. ISBN 978-1-78561-136-0 (https://doi.org/10.1049/cp.2015.1795)

[thumbnail of Malvaldi-etal-IET-ICISP-2015-Wind-prediction-enhancement-by-exploiting-data]
Preview
Text. Filename: Malvaldi_etal_IET_ICISP_2015_Wind_prediction_enhancement_by_exploiting_data.pdf
Accepted Author Manuscript

Download (329kB)| Preview

Abstract

The short term forecasting of wind speed and direction has previously been improved by adopting a cyclo-stationary multichannel linear prediction approach which incorporat ed seasonal cycles into the estimation of statistics. This pap er expands previous analysis by also incorporating diurnal va ri- ation and time-dependent window lengths. Based on a large data set from the UK’s Met Office, we demonstrate the impact of this proposed approach.