Modeling Wind Speed Using Parametric and Non-Parametric Distribution Functions

被引:2
|
作者
Ncwane, Siyanda [1 ]
Folly, Komla A. [1 ]
机构
[1] Univ Cape Town, Dept Elect Engn, ZA-7700 Cape Town, South Africa
基金
新加坡国家研究基金会;
关键词
Probability density function; Wind speed; Measurement; Distribution functions; Shape; Wind power generation; Estimation; Goodness-of-fit metrics; kernel density estimation; logspline density estimation; wind speed modeling; wind speed range;
D O I
10.1109/ACCESS.2021.3099985
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The variability of wind speed is modeled in the literature using probability distribution functions (PDFs). In many papers, the selection of PDFs is based solely on goodness-of-fit metrics without giving proper consideration to whether these PDFs can model the wind speed range. A PDF's ability to model the wind speed range ensures that it can synthesize both the minimum and the maximum wind speed at a site. A methodology to select PDFs that can be used to model wind speed is presented in this paper. The proposed methodology considers not only the goodness-of-fit metrics when selecting PDFs, but also their ability to model the wind speed range. The proposed methodology is compared with a commonly used methodology in the literature that selects PDFs based solely on goodness-of-fit metrics. Simulation results show that the proposed methodology chooses better PDFs than the commonly used methodology. Furthermore, it is shown that selecting PDFs using the commonly used methodology does not guarantee that the chosen PDFs will model the wind speed range.
引用
收藏
页码:104501 / 104512
页数:12
相关论文
共 50 条
  • [1] A non-parametric approach for wind speed distribution mapping
    Houndekindo, Freddy
    Ouarda, Taha B. M. J.
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2023, 296
  • [2] Parametric and Non-parametric Wind Distribution Model for Tangier Region
    Sefian, Hind
    Bahraoui, Fatima
    Bahraoui, Zuhair
    Batmi, Abdeladim
    [J]. ADVANCED INTELLIGENT SYSTEMS FOR SUSTAINABLE DEVELOPMENT (AI2SD'2019): VOL 7 - ADVANCED INTELLIGENT SYSTEMS FOR SUSTAINABLE DEVELOPMENT APPLIED IN ENERGY AND ELECTRICAL ENGINEERING, 2020, 624 : 213 - 220
  • [3] Non-parametric hybrid models for wind speed forecasting
    Han, Qinkai
    Meng, Fanman
    Hu, Tao
    Chu, Fulei
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2017, 148 : 554 - 568
  • [4] To be parametric or non-parametric, that is the question Parametric and non-parametric statistical tests
    Van Buren, Eric
    Herring, Amy H.
    [J]. BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY, 2020, 127 (05) : 549 - 550
  • [5] A modeling paradigm incorporating parametric and non-parametric methods
    Song, D
    Wang, Z
    Marmarelis, VZ
    Berger, TW
    [J]. PROCEEDINGS OF THE 26TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2004, 26 : 647 - 650
  • [6] Non-parametric bootstrap tests for parametric distribution families
    Szucs, Gabor
    [J]. ACTA SCIENTIARUM MATHEMATICARUM, 2011, 77 (3-4): : 703 - 723
  • [7] Non-parametric bootstrap tests for parametric distribution families
    Gábor Szűcs
    [J]. Acta Scientiarum Mathematicarum, 2011, 77 (3-4): : 703 - 723
  • [8] Comparison of Parametric and Non-Parametric Approaches for Vehicle Speed Prediction
    Lefevre, Stephanie
    Sun, Chao
    Bajcsy, Ruzena
    Laugier, Christian
    [J]. 2014 AMERICAN CONTROL CONFERENCE (ACC), 2014, : 3494 - 3499
  • [9] An omnibus non-parametric test of equality in distribution for unknown functions
    Luedtke, Alex
    Carone, Marco
    van der Laan, Mark J.
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2019, 81 (01) : 75 - 99
  • [10] Software Reliability Prediction Modeling: A Comparison of Parametric and Non-Parametric Modeling
    Choudhary, Ankur
    Baghel, Anurag Singh
    Sangwan, Om Prakash
    [J]. 2016 6TH INTERNATIONAL CONFERENCE - CLOUD SYSTEM AND BIG DATA ENGINEERING (CONFLUENCE), 2016, : 649 - 653