南方能源建设 (Jan 2024)

Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution

  • Hua LI

DOI
https://doi.org/10.16516/j.ceec.2024.1.04
Journal volume & issue
Vol. 11, no. 1
pp. 33 – 41

Abstract

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[Introduction] Wind power density is an important parameter for wind resource assessment, and the accurate calculation of wind power density relies on the accuracy of fitting the wind frequency with the Weibull distribution. It is helpful that reasonable analysis the wind power density in that decreasing the risks and improving the decision-making of wind farm investment. Considering the lack of research on the accuracy of Weibull distribution fitting in wind resource assessment, the paper aims to improve the accuracy of wind resource assessment by comparing and studying which method provides a higher accuracy in Weibull distribution fitting. [Method] Five commonly used methods for simulating wind frequency distribution based on the Weibull model were studied. The coefficient of determination was introduced to determine the accuracy of Weibull simulation. The absolute error and relative error between the wind power density calculated by the Weibull function and the wind power density calculated from measured data were compared. [Result] The results show that the energy pattern factor (EPF) method and the maximum likelihood estimation (MLE) method obtained higher coefficients of determination for Weibull fitting compared to other methods, including empirical methods (EPJ and EPL) and the least squares (LLSA) method. The wind power density calculate using these two methods, based on the obtained parameters, has smaller absolute errors and relative errors compared to the other three methods when compared to the wind power density calculate from measured data. [Conclusion] The research results can provide a reference for selecting the appropriate Weibull method to calculate wind power density in wind resource assessment and the true features of wind farm can be revealed, then, the accuracy of wind resource assessment can be improved.

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