Study of different parameters estimation methods of Weibull distribution to determine wind power density using ground based Doppler SODAR instrument

被引:85
作者
Chaurasiya, Prem Kumar [1 ]
Ahmed, Siraj [1 ]
Warudkar, Vilas [1 ]
机构
[1] MANIT, Dept Mech Engn, Bhopal, MP, India
关键词
Weibull parameters; Wind frequency distribution; Wind speed; Probability distribution function; Statistical analysis; SPEED;
D O I
10.1016/j.aej.2017.08.008
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The effectiveness of nine different numerical methods is examined for calculating the parameters of Weibull distribution at three different heights 80 m, 100 m and 120 m to estimate wind power density. The measurement campaign was conducted at Kayathar, Tamil Nadu, India. The time series wind data were recorded using SecondWind Triton SODAR (Sound Detection and Ranging) instrument. Firstly, the fidelity assessment of SODAR measurement was examined. The aim of this study is to identify the more accurate method for computing wind power density of a selected region. The performance of the selected methods is judged based on goodness of fit test i.e. Root Mean Square Error Test (RMSE), Coefficient of Determination (R-2), Mean Absolute Percentage Error (MAPE), and Chi-square Test (X-2). Wind power densities are estimated with the help of estimated parameter values. This study proposes an approach to utilize SODAR and also aims to examine the accuracy of SODAR measurement by comparing the results with cup anemometer, in an attempt to establish adequate criteria for an effective utilization of SODAR for wind resource assessment. The results suggest that SODAR may be used as an alternative to meteorological mast. (C) 2017 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:2299 / 2311
页数:13
相关论文
共 23 条
[1]  
Ahmed S.A., 2013, INT J PHYS SCI, V8, P186, DOI DOI 10.5897/IJPS12.697
[2]   Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean [J].
Akdag, S. A. ;
Bagiorgas, H. S. ;
Mihalakakou, G. .
APPLIED ENERGY, 2010, 87 (08) :2566-2573
[3]   A new method to estimate Weibull parameters for wind energy applications [J].
Akdag, Seyit A. ;
Dinler, Ali .
ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (07) :1761-1766
[4]   An alternative distribution to Weibull for modeling the wind speed data: Inverse Weibull distribution [J].
Akgul, Fatma Gul ;
Senoglu, Birdal ;
Arslan, Talha .
ENERGY CONVERSION AND MANAGEMENT, 2016, 114 :234-240
[5]  
[Anonymous], 2015, GLOBAL WIND ENERGY C
[6]  
[Anonymous], 2015, WIND ENERGY THEORY P
[7]   Comparative study of numerical methods for determining Weibull parameters for wind energy potential [J].
Arslan, Talha ;
Bulut, Y. Murat ;
Yavuz, Arzu Altin .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 40 :820-825
[8]   WEIBULL PARAMETERS ESTIMATION USING FOUR DIFFERENT METHODS AND MOST ENERGY-CARRYING WIND SPEED ANALYSIS [J].
Bagiorgas, Haralambos S. ;
Giouli, Mihalakakou ;
Rehman, Shafiqur ;
Al-Hadhrami, Luai M. .
INTERNATIONAL JOURNAL OF GREEN ENERGY, 2011, 8 (05) :529-554
[9]   Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application [J].
Chang, Tian Pau .
APPLIED ENERGY, 2011, 88 (01) :272-282
[10]   Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil [J].
Costa Rocha, Paulo Alexandre ;
de Sousa, Ricardo Coelho ;
de Andrade, Carla Freitas ;
Vieira da Silva, Maria Eugenia .
APPLIED ENERGY, 2012, 89 (01) :395-400