Stochastic generation of hourly mean wind speed data

被引:81
|
作者
Aksoy, H [1 ]
Toprak, ZF [1 ]
Aytek, A [1 ]
Ünal, NE [1 ]
机构
[1] Istanbul Tech Univ, Fac Civil Engn, Dept Civil Engn, Hydraul Div, TR-34469 Istanbul, Turkey
关键词
normal distribution; Weibull distribution; autoregressive models; Markov chain; wavelet; hourly mean wind speed;
D O I
10.1016/j.renene.2004.03.011
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Use of wind speed data is of great importance in civil engineering, especially in structural and coastal engineering applications. Synthetic data generation techniques are used in practice for cases where long wind speed data are required. In this study, a new wind speed data generation scheme based upon wavelet transformation is introduced and compared to the existing wind speed generation methods namely normal and Weibull distributed independent random numbers, the first- and second-order autoregressive models, and the first-order Markov chain. Results propose the wavelet-based approach as a wind speed data generation scheme to alternate the existing methods. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2111 / 2131
页数:21
相关论文
共 50 条
  • [11] A methodology for the synthetic generation of hourly wind speed time series based on some known aggregate input data
    Carapellucci, Roberto
    Giordano, Lorena
    [J]. APPLIED ENERGY, 2013, 101 : 541 - 550
  • [12] A comparison of various forecasting techniques applied to mean hourly wind speed time series
    Sfetsos, A
    [J]. RENEWABLE ENERGY, 2000, 21 (01) : 23 - 35
  • [13] Hourly wind speed analysis in Sicily
    Bivona, S
    Burlon, R
    Leone, C
    [J]. RENEWABLE ENERGY, 2003, 28 (09) : 1371 - 1385
  • [14] Global investigation of double periodicity of hourly wind speed for stochastic simulation; application in Greece
    Deligiannis, Ilias
    Dimitriadis, Panayiotis
    Daskalou, Olympia
    Dimakos, Yiannis
    Koutsoyiannis, Demetris
    [J]. EUROPEAN GEOSCIENCES UNION GENERAL ASSEMBLY 2016, 2016, 97 : 278 - 285
  • [15] Stochastic modeling of hourly average wind speed sequences in national observatory of Athens, Greece
    Philippopoulos, K.
    Deligiorgi, D.
    [J]. Proceeding of the 9th International Conference on Environmental Science and Technology Vol B - Poster Presentations, 2005, : B729 - B734
  • [16] Assessing Distributions For Monthly Mean Wind Speed Data
    Kamil, Mira Syahirah
    Razali, Ahmad Mahir
    [J]. 2016 UKM FST POSTGRADUATE COLLOQUIUM, 2016, 1784
  • [17] Generation of Short-term Wind Power Scenarios from an Ensemble of Hourly Wind Speed Forecasts
    Pessanha, J. F. M.
    Melo, A. C. G.
    Maceira, M. E. P.
    Almeida, V. A.
    [J]. 2022 17TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2022,
  • [18] A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models
    Millstein, Dev
    Jeong, Seongeun
    Ancell, Amos
    Wiser, Ryan
    [J]. SCIENTIFIC DATA, 2023, 10 (01)
  • [19] A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models
    Dev Millstein
    Seongeun Jeong
    Amos Ancell
    Ryan Wiser
    [J]. Scientific Data, 10
  • [20] Comparison of the Weibull model with measured wind speed distributions for stochastic wind generation
    van Donk, SJ
    Wagner, LE
    Skidmore, EL
    Tatarko, J
    [J]. TRANSACTIONS OF THE ASAE, 2005, 48 (02): : 503 - 510