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Statistical analysis of wind energy potential using different estimation methods for Weibull parameters: a case study

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Abstract

Accurate estimation of wind speed distributions is a challenging task in wind power planning and operation. The selection of convenient functions for describing wind speed distribution is a crucial requisite. In this paper, remarkable bi-parameter Weibull function is presented to estimate the wind energy potential. Weibull parameters based on different six estimation methods, namely graphical, method of moment, energy pattern factor, mean standard deviation, power density methods, and genetic algorithm are evaluated. Besides, the goodness of fit of the estimation methods is investigated via mean absolute error, root mean square error, normalized mean absolute error, Chi-square error, and regression coefficient. To plainly identify the best matching estimation method, Net Fitness test is also presented. Catalca in the Marmara region in Istanbul, Republic of Turkey, is selected to be the underlying site. The experimental results show the effectiveness of the estimation methods in modeling wind distribution but with relatively small differences in terms of performance. However, the genetic algorithm and energy pattern factor accomplish the best and worst matching estimation methods, respectively.

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Acknowledgements

The authors would like to thank the Turkish general directorate of meteorology in Istanbul for their gentleness in providing the raw data for this study.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Electrical and Electronics Engineering Department, Istanbul Sabahattin Zaim University, Istanbul, Turkey

    Mohammed Wadi & Wisam Elmasry

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  1. Mohammed Wadi
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Wadi, M., Elmasry, W. Statistical analysis of wind energy potential using different estimation methods for Weibull parameters: a case study. Electr Eng 103, 2573–2594 (2021). https://doi.org/10.1007/s00202-021-01254-0

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