Five different distributions and metaheuristics to model wind speed distribution

被引:5
|
作者
Wadi, Mohammed [1 ]
机构
[1] Istanbul S Zaim Univ, Elect & Elect Engn Dept, Istanbul, Turkey
来源
JOURNAL OF THERMAL ENGINEERING | 2021年 / 7卷 / 08期
关键词
Wind Energy; Wind Speed; Statistical distributions; Probability distribution function (PDF); Cumulative distribution function (CDF); Inverse CDF (ICDF); Grey Wolf Optimization (GWO); Whale Optimization Algorithm (WOA); PROBABILITY-DISTRIBUTIONS; RAYLEIGH DISTRIBUTION; BURR; WEIBULL; NETWORKS;
D O I
10.18186/thermal.1051262
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents a comprehensive empirical study of five distribution functions to analyze wind energy potential: Rayleigh, Weibull, Gamma, Burr Type XII, and Generalized Extreme Value. In addition, two metaheuristics optimization methods, Grey Wolf optimization and Whale optimization algorithm, are utilized to determine the optimal parameter values of each distribution. Five error measures are investigated and compared to test the accuracy of the introduced distributions and optimization methods, such as mean absolute error, root mean square error, regression coefficient, correlation coefficient, and net fitness. The Catalca site in Istanbul, Turkey, was selected to be the case study to conduct this analysis. The obtained results confirm that all introduced distributions based on optimization methods efficiently model wind speed distribution in the selected site. Although Gamma distribution based on GWO and WOA outperformed other distributions for all datasets at all heights, it was the worst in terms of computation complexity. Rayleigh distribution occupied the latest rank, but it was the best in terms of computation complexity. MATLAB 2020b and Excel 365 were used to perform this study.
引用
收藏
页码:1898 / 1920
页数:23
相关论文
共 50 条
  • [1] Comparison of Five Different Distributions based on Three Metaheuristics to Model Wind Speed Distribution
    Wadi, Mohammed
    Elmasry, Wisam
    JOURNAL OF ELECTRICAL SYSTEMS, 2022, 18 (03) : 369 - 390
  • [2] A Comparative Assessment of Five Different Distributions Based on Five Different Optimization Methods for Modeling Wind Speed Distribution
    Wadi, Mohammed
    Elmasry, Wisam
    GAZI UNIVERSITY JOURNAL OF SCIENCE, 2023, 36 (03): : 1096 - 1120
  • [3] Mixture probability distribution functions to model wind speed distributions
    Kollu R.
    Rayapudi S.R.
    Narasimham S.V.L.
    Pakkurthi K.M.
    International Journal of Energy and Environmental Engineering, 2012, 3 (1) : 1 - 10
  • [4] Distributions of Wind Speed at Different Heights
    Mert Kantar, Yeliz
    Usta, Ilhan
    Arik, Ibrahim
    Yenilmez, Ismail
    2016 INTERNATIONAL CONFERENCE ON ENGINEERING & MIS (ICEMIS), 2016,
  • [5] A Statistical Analysis of Wind Speed Probabilistic Distributions for the Wind Power Assessment in Different Regions
    Bay, Yuly
    Ruban, Nikolay
    Andreev, Mikhail
    Gusev, Alexandr
    PRZEGLAD ELEKTROTECHNICZNY, 2021, 97 (12): : 82 - 85
  • [6] Comparison of the Weibull model with measured wind speed distributions for stochastic wind generation
    van Donk, SJ
    Wagner, LE
    Skidmore, EL
    Tatarko, J
    TRANSACTIONS OF THE ASAE, 2005, 48 (02): : 503 - 510
  • [7] Application of five continuous distributions and evaluation of wind potential at five stations using normal distribution
    Sumair, Muhammad
    Aized, Tauseef
    Gardezi, Syed Asad Raza
    Bhutta, Muhammad Mahmood Aslam
    Rehman, Syed Muhammad Sohail
    Rehman, Syed Ubaid Ur
    ENERGY EXPLORATION & EXPLOITATION, 2021, 39 (06) : 2214 - 2239
  • [8] Comparative Analysis of Wind Speed Models Using Different Weibull Distributions
    Dokur, Emrah
    Ceyhan, Salim
    Kurban, Mehmet
    ELECTRICA, 2019, 19 (01): : 22 - 28
  • [9] Design wind speed prediction suitable for different parent sample distributions
    Zhao, Lin
    Hu, Xiaonong
    Ge, Yaojun
    WIND AND STRUCTURES, 2021, 33 (06) : 423 - 435
  • [10] WEIBULL PARAMETERS FOR ANNUAL AND MONTHLY WIND SPEED DISTRIBUTIONS FOR FIVE LOCATIONS IN INDIA.
    Gupta, B.K.
    1600, (37):