Bayesian method for estimating Weibull parameters for wind resource assessment in a tropical region: a comparison between two-parameter and three-parameter Weibull distributions

IF 3.6 Q3 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY
Mohammad G.M. Khan, M. R. Ahmed
{"title":"Bayesian method for estimating Weibull parameters for wind resource assessment in a tropical region: a comparison between two-parameter and three-parameter Weibull distributions","authors":"Mohammad G.M. Khan, M. R. Ahmed","doi":"10.5194/wes-8-1277-2023","DOIUrl":null,"url":null,"abstract":"Abstract. The two-parameter Weibull distribution has garnered much attention\nin the assessment of wind energy potential. The estimation of the shape and\nscale parameters of the distribution has brought forth a successful tool for\nthe wind energy industry. However, it may be inappropriate to use the\ntwo-parameter Weibull distribution to assess energy at every location,\nespecially at sites where low wind speeds are frequent, such as in tropical\nregions. In this work, a robust technique for wind resource assessment using\na Bayesian approach for estimating Weibull parameters is first proposed.\nSecondly, the wind resource assessment techniques using a two-parameter\nWeibull distribution and a three-parameter Weibull distribution, which is a\ngeneralized form of two-parameter Weibull distribution, are compared.\nSimulation studies confirm that the Bayesian approach seems a more robust\ntechnique for accurate estimation of Weibull parameters. The research is\nconducted using data from seven sites in the tropical region from 1∘ N of\nthe Equator to 21∘ S of the Equator. Results reveal that a three-parameter\nWeibull distribution with a non-zero shift parameter is a better fit for the\nwind data with a higher percentage of low wind speeds (0–1 m s−1) and\nlow skewness. However, wind data with a smaller percentage of low wind\nspeeds and high skewness showed better results with a two-parameter\ndistribution that is a special case of the three-parameter Weibull distribution\nwith a zero shift parameter. The proposed distribution can be incorporated into\ncommercial software like WAsP to improve the accuracy of wind resource\nassessments. The results also demonstrate that the proposed Bayesian\napproach and application of a three-parameter Weibull distribution are\nextremely useful for accurate estimation of wind power density.\n","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wind Energy Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/wes-8-1277-2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract. The two-parameter Weibull distribution has garnered much attention in the assessment of wind energy potential. The estimation of the shape and scale parameters of the distribution has brought forth a successful tool for the wind energy industry. However, it may be inappropriate to use the two-parameter Weibull distribution to assess energy at every location, especially at sites where low wind speeds are frequent, such as in tropical regions. In this work, a robust technique for wind resource assessment using a Bayesian approach for estimating Weibull parameters is first proposed. Secondly, the wind resource assessment techniques using a two-parameter Weibull distribution and a three-parameter Weibull distribution, which is a generalized form of two-parameter Weibull distribution, are compared. Simulation studies confirm that the Bayesian approach seems a more robust technique for accurate estimation of Weibull parameters. The research is conducted using data from seven sites in the tropical region from 1∘ N of the Equator to 21∘ S of the Equator. Results reveal that a three-parameter Weibull distribution with a non-zero shift parameter is a better fit for the wind data with a higher percentage of low wind speeds (0–1 m s−1) and low skewness. However, wind data with a smaller percentage of low wind speeds and high skewness showed better results with a two-parameter distribution that is a special case of the three-parameter Weibull distribution with a zero shift parameter. The proposed distribution can be incorporated into commercial software like WAsP to improve the accuracy of wind resource assessments. The results also demonstrate that the proposed Bayesian approach and application of a three-parameter Weibull distribution are extremely useful for accurate estimation of wind power density.
热带地区风资源评价中威布尔参数估计的贝叶斯方法:两参数与三参数威布尔分布的比较
摘要双参数威布尔分布在风能潜力评价中受到广泛关注。对分布的形状和尺度参数的估计为风能工业提供了一个成功的工具。然而,使用双参数威布尔分布来评估每个地点的能量可能是不合适的,特别是在低风速频繁的地点,如热带地区。在这项工作中,首次提出了一种使用贝叶斯方法估计威布尔参数的风力资源评估技术。其次,比较了双参数威布尔分布和广义的三参数威布尔分布的风力资源评价技术。仿真研究证实,贝叶斯方法对于精确估计威布尔参数似乎是一种更可靠的技术。这项研究使用了从赤道1°N到赤道21°S的热带地区7个地点的数据。结果表明,对于低风速(0-1 m s−1)和低偏度的风数据,具有非零偏移参数的三参数威布尔分布更适合。然而,低风速和高偏度比例较小的风数据在双参数分布中显示出更好的结果,这是具有零移位参数的三参数威布尔分布的特殊情况。提议的分布可以被整合到像WAsP这样的商业软件中,以提高风能资源评估的准确性。结果还表明,所提出的贝叶斯方法和三参数威布尔分布的应用对于准确估计风力密度非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Wind Energy Science
Wind Energy Science GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
6.90
自引率
27.50%
发文量
115
审稿时长
28 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信