A. Genç, Murat Erisoglu, A. Pekgor, G. Oturanç, A. Hepbasli, K. Ulgen
{"title":"Estimation of Wind Power Potential Using Weibull Distribution","authors":"A. Genç, Murat Erisoglu, A. Pekgor, G. Oturanç, A. Hepbasli, K. Ulgen","doi":"10.1080/00908310490450647","DOIUrl":null,"url":null,"abstract":"The main objective of the present study is to estimate wind power potential using the two Weibull parameters of the wind speed distribution function, the shape parameter k (dimensionless) and the scale parameter c (m/s). In this regard, a methodology that uses three various techniques (maximum likelihood, least squares, and method of moments) for estimating the Weibull parameters was given first. The methodology was then applied to a region in Turkey. Finally, the parameter techniques were compared to Monte-Carlo simulation in different sample sizes, and the best parameter estimation techniques belonging to the sample sizes were also determined.","PeriodicalId":11841,"journal":{"name":"Energy Sources","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2005-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"102","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Sources","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00908310490450647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 102
Abstract
The main objective of the present study is to estimate wind power potential using the two Weibull parameters of the wind speed distribution function, the shape parameter k (dimensionless) and the scale parameter c (m/s). In this regard, a methodology that uses three various techniques (maximum likelihood, least squares, and method of moments) for estimating the Weibull parameters was given first. The methodology was then applied to a region in Turkey. Finally, the parameter techniques were compared to Monte-Carlo simulation in different sample sizes, and the best parameter estimation techniques belonging to the sample sizes were also determined.