Weibull parameters evaluation by different methods for windmills farms
| Autor: | Ali K. Resen, Auday H. Shaban, Nathalie Bassil |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Wind power
Coefficient of determination Correlation coefficient business.industry 020209 energy Modified maximum likelihood method 02 engineering and technology Weibull parameters Shape parameter General Energy 020401 chemical engineering Goodness of fit Statistics ddc:330 Maximum likelihood method 0202 electrical engineering electronic engineering information engineering Curve fitting lcsh:Electrical engineering. Electronics. Nuclear engineering 0204 chemical engineering business lcsh:TK1-9971 Scale parameter Mathematics Weibull distribution |
| Zdroj: | Energy Reports, Vol 6, Iss, Pp 188-199 (2020) |
| ISSN: | 2352-4847 |
| DOI: | 10.1016/j.egyr.2019.10.037 |
| Popis: | Electrical power generated from the wind’s motion is one of the most common clean and renewable energy produced. The wind turbines used to convert wind mechanical power to electricity have to be placed at a site presenting favorable conditions. This work focuses on finding an accurate method for modeling the power generated by a wind farm using Weibull distribution. Experimental data collected at AL-Najaf site – Iraq – is used to determine the best theoretical method to hold in order to determine the Weibull parameters. The data was collected on different levels above the ground 10, 30, and 50 m. Four criteria were displayed to assess the wind data fitting procedures; these are Root Mean Square Error, Chi-Square, correlation coefficient, and coefficient of determination. The valid distribution model was determined according to specific conditions that gives the best results. The findings indicate that the Equivalent Energy Method is the best to calculate the value of the Weibull shape parameter and the Weibull scale parameter for the Weibull distribution curves at this site based on the goodness of fit tests. Keywords: Weibull parameters, Maximum likelihood method, Modified maximum likelihood method |
| Databáze: | OpenAIRE |
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