共 14 条
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A new estimation approach based on moments for estimating Weibull parameters in wind power applications.[J].Ilhan Usta;Ibrahim Arik;Ismail Yenilmez;Yeliz Mert Kantar.Energy Conversion and Management.2018,
[2]
Estimation of wind speed probability distribution and wind energy potential using adaptive neuro-fuzzy methodology.[J].Aamer Bilal Asghar;Xiaodong Liu.Neurocomputing.2018,
[3]
Statistical analysis of wind characteristics based on Weibull methods for estimation of power generation in Lithuania.[J].Vladislovas Katinas;Mantas Marčiukaitis;Giedrius Gecevičius;Antanas Markevičius.Renewable Energy.2017,
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A novel method based on Weibull distribution for short-term wind speed prediction
[J].
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY,
2017, 42 (28)
:17793-17800
Kaplan, Orhan
;
Temiz, Murat
.
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Assessing different parameters estimation methods of Weibull distribution to compute wind power density.[J].Kasra Mohammadi;Omid Alavi;Ali Mostafaeipour;Navid Goudarzi;Mahdi Jalilvand.Energy Conversion and Management.2016,
[6]
An alternative distribution to Weibull for modeling the wind speed data: Inverse Weibull distribution.[J].Fatma Gül Akgül;Birdal ?eno?lu;Talha Arslan.Energy Conversion and Management.2016,
[7]
Wind speed and power density analysis based on Weibull and Rayleigh distributions (a case study: Firouzkooh county of Iran).[J].S.H. Pishgar-Komleh;A. Keyhani;P. Sefeedpari.Renewable and Sustainable Energy Reviews.2015,
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The parent wind speed distribution: Why Weibull?.[J].R. Ian Harris;Nicholas J. Cook.Journal of Wind Engineering & Industrial Aerodynamics.2014,
[9]
Analysis of Wind Energy Conversion System Using Weibull Distribution.[J].A.K. Azad;M.G. Rasul;M.M. Alam;S.M. Ameer Uddin;Sukanta Kumar Mondal.Procedia Engineering.2014, C
[10]