Literature DB >> 17698475

Wind direction modelling using multiple observation points.

Yoshito Hirata1, Danilo P Mandic, Hideyuki Suzuki, Kazuyuki Aihara.   

Abstract

The prediction of wind direction is a prerequisite for the intelligent and efficient operation of wind turbines. This is a complex task, due to the intermittent behaviour of wind, its non-Gaussian and nonlinear nature, and the coupling between the wind speed and direction. To provide improved wind direction forecasting, we propose a nonlinear model with augmented information from an additional measurement point. This is further enhanced by making use of both the speed and direction components of the wind field vector. The analysis and a comprehensive set of simulations demonstrate that the proposed approach achieves improved prediction performance over the standard and persistent model. The potential of the proposed approach is justified by the fact that even relatively small improvements in the forecasts result in large gains in the produced output power.

Year:  2008        PMID: 17698475     DOI: 10.1098/rsta.2007.2112

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  1 in total

1.  Novel strategy for wide-range wind vector measurement using the hybrid CP/CTD heating mode and sequential measuring and correcting.

Authors:  Tian Wang; Yunbo Shi; Xiaoyu Yu; Guangdong Lan; Congning Liu
Journal:  PLoS One       Date:  2021-07-08       Impact factor: 3.240

  1 in total

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