Statistical study of the influence of the data sampling interval on the estimation of wind turbine energy

Dhaker Abbes, André Martinez, Gérard Champenois, Jean-Paul Gaubert, International Conference on Renewable Energies and Power Quality, Granada, Spain, 2010.

RÉSUMÉ / ABSTRACT :

Main deficiency for wind power is variability. It is really difficult to predetermine the wind’s potential since wind velocity cannot be controlled or predicted with pinpoint accuracy.
In this paper, two different methods are applied in order to estimate the monthly wind energy for different sites; those estimations are done using Weibull distribution and calculating energy with direct integration methodology. In additional, the influence of the data sampling interval is studied. Results show that the computational method based on the integration of the power is more accurate. Also, it is shown that the hourly time resolution provides satisfactory accuracy in wind resource estimation, in comparison with one minute’s resolution. Results allow better design of wind or hybrid systems. Moreover, wind speed acquisitions are minimized. A shorter time of treatment and less expensive measurement equipments are required.

 

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