Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution

[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 decre...

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Main Author: Hua LI
Format: Article
Language:English
Published: Energy Observer Magazine Co., Ltd. 2024-01-01
Series:南方能源建设
Subjects:
Online Access:https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024.1.04
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author Hua LI
author_facet Hua LI
author_sort Hua LI
collection DOAJ
description [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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spelling doaj.art-cbea8b13c02f47968fcbd90d086a0d5b2024-03-03T03:02:53ZengEnergy Observer Magazine Co., Ltd.南方能源建设2095-86762024-01-01111334110.16516/j.ceec.2024.1.042023-060Comparison of Wind Power Density Calculation Methods Based on Weibull DistributionHua LI0Runyang Energy Technology Co., Ltd., Tianjin 300300, China[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.https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024.1.04weibull distributionwind power densityenergy pattern factor (epf) methodmaximum likelihood estimation (mle) methodcoefficient of determination
spellingShingle Hua LI
Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution
南方能源建设
weibull distribution
wind power density
energy pattern factor (epf) method
maximum likelihood estimation (mle) method
coefficient of determination
title Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution
title_full Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution
title_fullStr Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution
title_full_unstemmed Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution
title_short Comparison of Wind Power Density Calculation Methods Based on Weibull Distribution
title_sort comparison of wind power density calculation methods based on weibull distribution
topic weibull distribution
wind power density
energy pattern factor (epf) method
maximum likelihood estimation (mle) method
coefficient of determination
url https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024.1.04
work_keys_str_mv AT huali comparisonofwindpowerdensitycalculationmethodsbasedonweibulldistribution