Complex-valued prediction of wind profile using augmented complex statistics

This paper presents a novel approach for the simultaneous modelling and forecasting of wind whereby the wind field is considered as a vector of its speed and direction components in the field of complex numbers C. To account for the intermittency and coupling of wind speed and direction, we propose to use the recently introduced framework of augmented complex statistics. The augmented complex least mean square (ACLMS) algorithm is introduced and its usefulness in wind forecasting is analysed. Simulations over different wind regimes support the approach.

[1]  Liang Li,et al.  Nonlinear adaptive prediction of nonstationary signals , 1995, IEEE Trans. Signal Process..

[2]  Shuhui Li,et al.  Using neural networks to estimate wind turbine power generation , 2001 .

[3]  Bernard C. Picinbono,et al.  On circularity , 1994, IEEE Trans. Signal Process..

[4]  P. Dokopoulos,et al.  Short-term forecasting of wind speed and related electrical power , 1998 .

[5]  Louis L. Scharf,et al.  Second-order analysis of improper complex random vectors and processes , 2003, IEEE Trans. Signal Process..

[6]  Danilo P. Mandic,et al.  An augmented CRTRL for complex-valued recurrent neural networks , 2007, Neural Networks.

[7]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[8]  D.P. Mandic,et al.  Why a Complex Valued Solution for a Real Domain Problem , 2007, 2007 IEEE Workshop on Machine Learning for Signal Processing.

[9]  S. L. Goh,et al.  Complex-valued estimation of wind profile and wind power , 2004, Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (IEEE Cat. No.04CH37521).

[10]  Bernard C. Picinbono,et al.  Second-order complex random vectors and normal distributions , 1996, IEEE Trans. Signal Process..

[11]  Danilo P. Mandic,et al.  A non-parametric test for detecting the complex-valued nature of time series , 2004 .

[12]  S. L. Goh,et al.  An Augmented Extended Kalman Filter Algorithm for Complex-Valued Recurrent Neural Networks , 2007, Neural Computation.

[13]  Zoran Obradovic,et al.  Rapid design of neural networks for time series prediction , 1996 .

[14]  Amir F. Atiya,et al.  A comparison between neural-network forecasting techniques-case study: river flow forecasting , 1999, IEEE Trans. Neural Networks.

[15]  Kazuyuki Aihara,et al.  Complex-valued forecasting of wind profile , 2006 .

[16]  B. Widrow,et al.  The complex LMS algorithm , 1975, Proceedings of the IEEE.

[17]  James L. Massey,et al.  Proper complex random processes with applications to information theory , 1993, IEEE Trans. Inf. Theory.