Multivariate Weibull Distribution for Wind Speed and Wind Power Behavior Assessment

被引:19
|
作者
Villanueva, Daniel [1 ]
Feijoo, Andres [1 ]
Pazos, Jose L. [1 ]
机构
[1] Univ Vigo, Dept Enxeneria Elect, Maxwell S-N, E-36301 Vigo, Spain
来源
RESOURCES-BASEL | 2013年 / 2卷 / 03期
关键词
wind speed; wind power; bivariate Weibull distribution; multivariate Weibull distribution; correlation; inference;
D O I
10.3390/resources2030370
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The goal of this paper is to show how to derive the multivariate Weibull probability density function from the multivariate Standard Normal one and to show its applications. Having Weibull distribution parameters and a correlation matrix as input data, the proposal is to obtain a precise multivariate Weibull distribution that can be applied in the analysis and simulation of wind speeds and wind powers at different locations. The main advantage of the distribution obtained, over those generally used, is that it is defined by the classical parameters of the univariate Weibull distributions and the correlation coefficients and all of them can be easily estimated. As a special case, attention has been paid to the bivariate Weibull distribution, where the hypothesis test of the correlation coefficient is defined.
引用
收藏
页码:370 / 384
页数:15
相关论文
共 50 条
  • [1] Wind speed estimation based on a novel multivariate Weibull distribution
    Salim, Omar M.
    Dorrah, Hassen Taher
    Hassan, Mahmoud Adel
    IET RENEWABLE POWER GENERATION, 2019, 13 (15) : 2762 - 2773
  • [2] A novel approach to Weibull distribution for the assessment of wind energy speed
    Aljeddani, Sadiah M. A.
    Mohammea, M. A.
    ALEXANDRIA ENGINEERING JOURNAL, 2023, 78 : 56 - 64
  • [3] Seasonal and yearly wind speed distribution and wind power density analysis based on Weibull distribution function
    Bilir, Levent
    Imir, Mehmet
    Devrim, Yilser
    Albostan, Ayhan
    INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2015, 40 (44) : 15301 - 15310
  • [4] Comparative Wind Power Assessment by Weibull Distribution Function in Faridpur
    Ali, Muhammad
    Mridul, Mazbah Kabir
    Al Mahbub, Abdullah
    PROCEEDINGS OF 2020 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (ICECE), 2020, : 13 - 16
  • [5] The parent wind speed distribution: Why Weibull?
    Harris, R. Ian
    Cook, Nicholas J.
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2014, 131 : 72 - 87
  • [6] Fractional Weibull Wind Speed Modeling For Wind Power Production Estimation
    Yu, Zuwei
    Tuzuner, Akiner
    2009 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, VOLS 1-8, 2009, : 2874 - 2880
  • [7] Fractional Weibull Wind Speed Modeling For Wind Power Production Estimation
    Yu, Zuwei
    Tuzuner, Akiner
    2009 INTERNATIONAL CONFERENCE ON SUSTAINABLE POWER GENERATION AND SUPPLY, VOLS 1-4, 2009, : 952 - 957
  • [8] Adequacy Assessment of Wind Energy Conversion System through Simulating Wind Speed using Weibull Distribution
    Novak, Ashwini Kumar
    Mohanty, Kanungo Barada
    2017 NATIONAL POWER ELECTRONICS CONFERENCE (NPEC), 2017, : 102 - 105
  • [9] An alternative distribution to Weibull for modeling the wind speed data: Inverse Weibull distribution
    Akgul, Fatma Gul
    Senoglu, Birdal
    Arslan, Talha
    ENERGY CONVERSION AND MANAGEMENT, 2016, 114 : 234 - 240
  • [10] Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis
    Seguro, JV
    Lambert, TW
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2000, 85 (01) : 75 - 84