Assessment of wind resource considering local turbulence based on data acquisition with SODAR

被引:1
作者
Silva, Reginaldo N. [1 ,3 ]
Fantini, Dario G. [1 ]
Mendes, Rafael C. F. [1 ]
Guimaraes, Marlos [2 ]
Oliveira, Taygoara [1 ]
Brasil Junior, Antonio [1 ]
机构
[1] Univ Brasilia, Dept Mech Engn, Energy & Environm Lab, Brasilia, DF, Brazil
[2] DSBE, Dept Dam Safety & Technol, Furnas Appl Aerodynam Lab, Aparecida De Goiania, Brazil
[3] Univ Brasilia, Dept Mech Engn, Energy & Environm Lab, Campus Univ Darcy Ribeiro, BR-70910 Brasilia, DF, Brazil
关键词
Wind energy; turbulence; Weibull distribution; renewable energy; SODAR; SPEED; MERRA-2; SCALE; LIDAR;
D O I
10.1177/0309524X231156451
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
This work presents a new methodology to evaluate the influence of wind speed data corrections in the fit of the Weibull distribution. Corrections are made for data measured by Sonic Detection and Ranging (SODAR) and MERRA-2 base data. SODAR data are corrected through Turbulence Intensity (TI). The MERRA-2 data correction uses National Institute of Meteorology (INMET) weather station data to find a local scale factor. The results showed that the corrected data present a better fit in the Weibull distribution and evidence that corrections are necessary when wind speed averages are used to evaluate the wind resource. Wind speed data were also applied to simulate the energy production by a commercial turbine to demonstrate the contrast in the total energy generated. The new methodology shows that IT must be considered in the evaluation of wind resources.
引用
收藏
页码:747 / 765
页数:19
相关论文
共 40 条
  • [1] Wind resource assessment considering the influence of humidity
    Al Mubarok, Abdul Goffar
    Tian, De
    [J]. WIND ENGINEERING, 2022, 46 (06) : 1838 - 1852
  • [2] Analysis of Hydro-Wind Complementarity in State of Pernambuco, Brazil by means of Weibull Parameters
    Araujo, P.
    Marinho, M.
    [J]. IEEE LATIN AMERICA TRANSACTIONS, 2019, 17 (04) : 556 - 563
  • [3] Baring-Gould I., 2014, WIND ENERGY DEPLOYME
  • [4] Wind Speed Data Analysis Using Weibull and Rayleigh Distribution Functions, Case Study: Five Cities Northern Morocco
    Bidaoui, Hicham
    El Abbassi, Ikram
    El Bouardi, Abdelmajid
    Darcherif, Abdelmoumen
    [J]. 12TH INTERNATIONAL CONFERENCE INTERDISCIPLINARITY IN ENGINEERING (INTER-ENG 2018), 2019, 32 : 786 - 793
  • [5] Effects of energetic coherent motions on the power and wake of an axial-flow turbine
    Chamorro, L. P.
    Hill, C.
    Neary, V. S.
    Gunawan, B.
    Arndt, R. E. A.
    Sotiropoulos, F.
    [J]. PHYSICS OF FLUIDS, 2015, 27 (05)
  • [6] Turbulence effects on a full-scale 2.5 MW horizontal-axis wind turbine under neutrally stratified conditions
    Chamorro, Leonardo P.
    Lee, S-J.
    Olsen, D.
    Milliren, C.
    Marr, J.
    Arndt, R. E. A.
    Sotiropoulos, F.
    [J]. WIND ENERGY, 2015, 18 (02) : 339 - 349
  • [7] Chaurasiya Prem Kumar, 2017, Resource-Efficient Technologies, V3, P495, DOI 10.1016/j.reffit.2017.07.001
  • [8] A new formulation for rotor equivalent wind speed for wind resource assessment and wind power forecasting
    Choukulkar, Aditya
    Pichugina, Yelena
    Clack, Christopher T. M.
    Calhoun, Ronald
    Banta, Robert
    Brewer, Alan
    Hardesty, Michael
    [J]. WIND ENERGY, 2016, 19 (08) : 1439 - 1452
  • [9] de Andrade C, 2018, IEEE LAT AM T, V16, P2513, DOI 10.1109/TLA.2018.8795130
  • [10] On the spectral behaviour of the turbulence-driven power fluctuations of horizontal-axis turbines
    Deskos, Georgios
    Payne, Gregory S.
    Gaurier, Benoit
    Graham, Michael
    [J]. JOURNAL OF FLUID MECHANICS, 2020, 904