کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
303033 512571 2007 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions
چکیده انگلیسی

The typical two-parameter Weibull is a flexible distribution that is useful for describing unimodal frequency distributions of wind speeds at many sites. A two-component mixture Weibull distribution (WW-probability distribution function (pdf)) is even more useful because it is additionally able to represent heterogenous wind regimes in which there is evidence of bimodality or bitangentiality or, simply, unimodality.An analysis is made in this paper of three of the most frequently used methods in the estimation of the five parameters of the WW-pdf and the numerical methods employed are described. Hourly mean wind speed data recorded at four weather stations located in the island of Gran Canaria (Spain) are used to analyse the estimation methods. Prior identification of the sample components of the mixture is not required.The suitability of the distributions is judged from the various tests-of-fit commonly used in the specialised literature on wind energy. A comparison is also made of the ability to describe the experimental wind power density distribution. The general conclusion is that if the sample data are independent then maximum likelihood (ML) estimators should be used due to their large sampling efficiency. However, they require elaborate calculation techniques. The least-square (LS) method provides a robust and computationally efficient alternative to the techniques currently in use. The method of moments has the disadvantage that it does not always supply a feasible result and lacks the desirable optimality properties of ML and LS estimators.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable Energy - Volume 32, Issue 3, March 2007, Pages 518–531
نویسندگان
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