A Widely Linear Multichannel Wiener Filter for Wind Prediction

Dowell, J. , Weiss, S., Infield, D. and Chandna, S. (2014) A Widely Linear Multichannel Wiener Filter for Wind Prediction. In: 2014 IEEE Workshop on Statistical Signal Processing (SSP), Gold Coast, QLD, Australia, 29 Jun - 02 Jul 2014, pp. 29-32. ISBN 9781479949755 (doi: 10.1109/SSP.2014.6884567)

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The desire to improve short-term predictions of wind speed and direction has motivated the development of a spatial covariance-based predictor in a complex valued multichannel structure. Wind speed and direction are modelled as the magnitude and phase of complex time series and measurements from multiple geographic locations are embedded in a complex vector which is then used as input to a multichannel Wiener prediction filter. Building on a C-linear cyclo-stationary predictor, a new widely linear filter is developed and tested on hourly mean wind speed and direction measurements made at 13 locations in the UK over 6 years. The new predictor shows a reduction in mean squared error at all locations. Furthermore it is found that the scale of that reduction strongly depends on conditions local to the measurement site.

Item Type:Conference Proceedings
Additional Information:This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Grant number EP/K014307/1 and the MOD University Defence Research Collaboration in Signal Processing. The authors gratefully acknowledge the UK Met. Office and the British Atmospheric Data Centre for their supply of meteorological data and the support of EPSRC via the University of Strathclyde’s Wind Energy Systems Centre for Doctoral Training, grant number EP/G037728/1.
Glasgow Author(s) Enlighten ID:Browell, Dr Jethro
Authors: Dowell, J., Weiss, S., Infield, D., and Chandna, S.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Published Online:28 August 2014

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