Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea

The Weibull probability distribution indicates the probability of a specific wind speed and must be calculated before wind turbine installation. The Weibull distribution is affected by shape and scale parameters, which are driven in various ways. Many studies have conducted research to determine a m...

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Autores principales: Sangkyun Kang, Ali Khanjari, Sungho You, Jang-Ho Lee
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Publicado: Elsevier 2021
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spelling oai:doaj.org-article:f054633a512042e5a71a61bac03ade342021-11-12T04:41:13ZComparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea2352-484710.1016/j.egyr.2021.10.078https://doaj.org/article/f054633a512042e5a71a61bac03ade342021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352484721010969https://doaj.org/toc/2352-4847The Weibull probability distribution indicates the probability of a specific wind speed and must be calculated before wind turbine installation. The Weibull distribution is affected by shape and scale parameters, which are driven in various ways. Many studies have conducted research to determine a more reliable method among various Weibull parameter estimation methods. However, since these studies showed different results, studies on determining the higher reliable Weibull parameter estimation methods continues. In this study, we analyzed 10 years of data collected at the same location and height level in Maldo island(from 2010 to 2019) and Saemangeum seawall (from 2011 to 2012), the Republic of Korea. While former studies tried to rank the Weibull distribution methods based on the statistical analyses, in this study, we compared the Weibull parameters using twelve methods and identified the highest reliable and efficient methods for deriving the Weibull probability distribution by using the new approach comparing the variance of RMSE, R2, and χ2, which give a comprehensive insight about the level and fluctuations errors. These twelve methods are Alternative maximum likelihood method, Equivalent energy method, Empirical method of Justus, Empirical method of Lysen, Energy pattern factor method, Graphical method, Modified energy pattern factor method, Maximum likelihood method, Moment method, Modified maximum likelihood method, Power density method, Standard deviation method. The results showed while Empirical method of Justus, Empirical method of Lysen, Moment method, and Standard deviation method had the best accuracies in prediction of wind speed distribution, some methods such as Graphical method, Alternative maximum likelihood method, Equivalent energy method, and Energy pattern factor method had the worst prediction of wind speed distribution based on all variance of statistical methods for both regions.Sangkyun KangAli KhanjariSungho YouJang-Ho LeeElsevierarticleWind speedWeibull distributionWeibull parameterEstimation methodsStatistical analysisElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENEnergy Reports, Vol 7, Iss , Pp 7358-7373 (2021)
institution DOAJ
collection DOAJ
language EN
topic Wind speed
Weibull distribution
Weibull parameter
Estimation methods
Statistical analysis
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
spellingShingle Wind speed
Weibull distribution
Weibull parameter
Estimation methods
Statistical analysis
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Sangkyun Kang
Ali Khanjari
Sungho You
Jang-Ho Lee
Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea
description The Weibull probability distribution indicates the probability of a specific wind speed and must be calculated before wind turbine installation. The Weibull distribution is affected by shape and scale parameters, which are driven in various ways. Many studies have conducted research to determine a more reliable method among various Weibull parameter estimation methods. However, since these studies showed different results, studies on determining the higher reliable Weibull parameter estimation methods continues. In this study, we analyzed 10 years of data collected at the same location and height level in Maldo island(from 2010 to 2019) and Saemangeum seawall (from 2011 to 2012), the Republic of Korea. While former studies tried to rank the Weibull distribution methods based on the statistical analyses, in this study, we compared the Weibull parameters using twelve methods and identified the highest reliable and efficient methods for deriving the Weibull probability distribution by using the new approach comparing the variance of RMSE, R2, and χ2, which give a comprehensive insight about the level and fluctuations errors. These twelve methods are Alternative maximum likelihood method, Equivalent energy method, Empirical method of Justus, Empirical method of Lysen, Energy pattern factor method, Graphical method, Modified energy pattern factor method, Maximum likelihood method, Moment method, Modified maximum likelihood method, Power density method, Standard deviation method. The results showed while Empirical method of Justus, Empirical method of Lysen, Moment method, and Standard deviation method had the best accuracies in prediction of wind speed distribution, some methods such as Graphical method, Alternative maximum likelihood method, Equivalent energy method, and Energy pattern factor method had the worst prediction of wind speed distribution based on all variance of statistical methods for both regions.
format article
author Sangkyun Kang
Ali Khanjari
Sungho You
Jang-Ho Lee
author_facet Sangkyun Kang
Ali Khanjari
Sungho You
Jang-Ho Lee
author_sort Sangkyun Kang
title Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea
title_short Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea
title_full Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea
title_fullStr Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea
title_full_unstemmed Comparison of different statistical methods used to estimate Weibull parameters for wind speed contribution in nearby an offshore site, Republic of Korea
title_sort comparison of different statistical methods used to estimate weibull parameters for wind speed contribution in nearby an offshore site, republic of korea
publisher Elsevier
publishDate 2021
url https://doaj.org/article/f054633a512042e5a71a61bac03ade34
work_keys_str_mv AT sangkyunkang comparisonofdifferentstatisticalmethodsusedtoestimateweibullparametersforwindspeedcontributioninnearbyanoffshoresiterepublicofkorea
AT alikhanjari comparisonofdifferentstatisticalmethodsusedtoestimateweibullparametersforwindspeedcontributioninnearbyanoffshoresiterepublicofkorea
AT sunghoyou comparisonofdifferentstatisticalmethodsusedtoestimateweibullparametersforwindspeedcontributioninnearbyanoffshoresiterepublicofkorea
AT jangholee comparisonofdifferentstatisticalmethodsusedtoestimateweibullparametersforwindspeedcontributioninnearbyanoffshoresiterepublicofkorea
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