Comparison of three methods for Weibull distribution in calculating wind energy potential

被引：1
|
作者：
Ihaddadene, Razika [1 ]
Ihaddadene, Nabila [1 ]
Mostefaoui, Merouane [2 ]
机构：
[1] Msila Univ, Dept Mech Engn, Msila, Algeria
[2] Msila Weather stat, Msila, Algeria
来源：
POWER AND ENERGY SYSTEMS III | 2014年 / 492卷
关键词：
Wind energy; Weibull distribution; Graphic method; Power density method; Moments method;
D O I：
10.4028/www.scientific.net/AMM.492.574
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Three kinds of methods commonly used for estimating Weibull parameters were fitted to a collection of wind speed data at 10 m above ground level for the year of 2009 to determine the best distribution function which describes the wind speed variation at M'sila, Algeria site for wind energy. Three methods used the coefficient of determination R-2, root mean square error RMSE and Chi-Square chi(2) were compared with failure analysis. According to the results of failure analysis the moment method has better results than graphic method and power density method. The wind power density calculated from moment method shows a good approximation to estimate the power density. So the Weibull distribution using the moment method adequately fit the data and it is suitable for modeling the wind speed distribution in M'sila province of Algeria.
引用
收藏
页码：574 / +
页数：2
相关论文
共 50 条
  • [31] Wind energy resource assessment for Kiribati with a comparison of different methods of determining Weibull parameters
    Aukitino, Tiaon
    Khan, M. G. M.
    Ahmed, M. Rafiuddin
    ENERGY CONVERSION AND MANAGEMENT, 2017, 151 : 641 - 660
  • [32] Comparison of Wind Energy Generation Using the Maximum Entropy Principle and the Weibull Distribution Function
    Shoaib, Muhammad
    Siddiqui, Imran
    Rehman, Shafiqur
    Rehman, Saif Ur
    Khan, Shamim
    Lashin, Aref
    ENERGIES, 2016, 9 (10)
  • [33] Estimation of wind power potential using Weibull distribution
    Genc, A
    Erisoglu, M
    Pekgor, A
    Oturanc, G
    Hepbasli, A
    Ulgen, K
    ENERGY SOURCES, 2005, 27 (09): : 809 - 822
  • [34] Wind energy potential and economic analysis with a comparison of different methods for determining the optimal distribution parameters
    Saeed, Muhammad Abid
    Ahmed, Zahoor
    Zhang, Weidong
    RENEWABLE ENERGY, 2020, 161 : 1092 - 1109
  • [35] Wind energy potential assessment using the Weibull distribution method for future energy self-sufficiency
    El Kihel, Badr
    Elyamani, Nacer Eddine El Kadri
    Chillali, Abdelhakim
    SCIENTIFIC AFRICAN, 2024, 26
  • [36] COMPARISON OF ESTIMATION METHODS FOR THE KUMARASWAMY WEIBULL DISTRIBUTION
    Ergenc, Cansu
    Senoglu, Birdal
    COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS, 2023, 72 (01): : 1 - 21
  • [37] COMPARISON OF PARAMETER ESTIMATION METHODS IN WEIBULL DISTRIBUTION
    Koksal Babacan, Esin
    Kaya, Samet
    SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, 2020, 38 (03): : 1609 - 1621
  • [38] COMPARISON OF METHODS OF ESTIMATION OF PARAMETERS OF THE WEIBULL DISTRIBUTION
    ALBAIDHANI, FA
    SINCLAIR, CD
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 1987, 16 (02) : 373 - 384
  • [39] Weibull distribution for determination of wind analysis and energy production
    Oral, Faruk
    Ekmekci, Ismail
    Onat, Nevzat
    WORLD JOURNAL OF ENGINEERING, 2015, 12 (03) : 215 - 220
  • [40] Analysis of wind speed data and wind energy potential in Faya-Largeau, Chad, using Weibull distribution
    Soulouknga, M. H.
    Doka, S. Y.
    Revanna, N.
    Djongyang, N.
    Kofane, T. C.
    RENEWABLE ENERGY, 2018, 121 : 1 - 8
12345