Practices and Considerations in Wind Data Processing for Accurate and Efficient Wind Farm Energy Calculation

Angel Gaspar Gonzalez-Rodriguez (), Jose Manuel Riega-Medina, Ildefonso Ruano-Ruano and Jose Vicente Muñoz-Diez
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Angel Gaspar Gonzalez-Rodriguez: Department of Electronic Engineering and Automation, University of Jaen, 23071 Jaen, Spain
Jose Manuel Riega-Medina: Facultad de Ciencias, Universidad Nacional de Ingeniería, Rimac 15333, Peru
Ildefonso Ruano-Ruano: Department of Telecommunications Engineering, University of Jaen, 23071 Jaen, Spain
Jose Vicente Muñoz-Diez: Department of Electronic Engineering and Automation, University of Jaen, 23071 Jaen, Spain

Energies, 2025, vol. 18, issue 13, 1-20

Abstract: An accurate estimation of future wind conditions is essential for calculating the annual energy produced by a wind farm. This estimation should be based on historical wind data collected over several years at the site location. However, research articles often rely on data grouped into 12 sectors. This article examines five methods to improve the speed and accuracy in the use of wind data. First, it studies the effect of inadequate Weibull parameter calculation based on historical data showing that purely mathematical fitting methods (the traditional ones) are not valid. Then, the error introduced by wind speed discretization is evaluated showing that the traditional binning of 1 m/s is not always the best choice. Next, the effect of using symmetric wind roses is examined, demonstrating that it is possible to reduce computation time by half for layouts exhibiting point symmetry, with negligible error for other layouts. After that, the effect of abrupt wind condition distributions caused by sectorization, which can alter results when searching for optimal configurations, is analyzed proposing continuous interpolation of wind data to improve result consistency. Finally, an alternative to the wind rose is proposed to provide a quick assessment of the highest-quality wind directions.

Keywords: wind rose; sector-wise Weibull distribution; Weibull fitting; wind speed binning; wind direction binning; point symmetry; energy rose (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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