CFP last date
20 May 2024
Reseach Article

Optimal selection of Wind Turbine Generators

by M. Bencherif, B. N. Brahmi, A. Chikhaoui
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 92 - Number 10
Year of Publication: 2014
Authors: M. Bencherif, B. N. Brahmi, A. Chikhaoui
10.5120/16042-4717

M. Bencherif, B. N. Brahmi, A. Chikhaoui . Optimal selection of Wind Turbine Generators. International Journal of Computer Applications. 92, 10 ( April 2014), 1-10. DOI=10.5120/16042-4717

@article{ 10.5120/16042-4717,
author = { M. Bencherif, B. N. Brahmi, A. Chikhaoui },
title = { Optimal selection of Wind Turbine Generators },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 92 },
number = { 10 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume92/number10/16042-4717/ },
doi = { 10.5120/16042-4717 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:13:54.361957+05:30
%A M. Bencherif
%A B. N. Brahmi
%A A. Chikhaoui
%T Optimal selection of Wind Turbine Generators
%J International Journal of Computer Applications
%@ 0975-8887
%V 92
%N 10
%P 1-10
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper examines optimum selection of wind turbines between site and wind turbine generators. An analysis methodology is done at the planning and development stages of installation of wind power stations will enable the wind power developer or the power utilities to make a judicious and rapid choice of suitable wind energy conversion system from the available potential sites. The methodology of analysis is based on the computations of annual capacity factors, which are done using the Weibull distribution function and power curve model. The methodology helps to the determination of the speeds characteristic range of the wind machines and to make easy the choice of the suitable wind turbine for a given site, in order to maximize the delivered energy for a given amount of available wind energy. This methodology is applied to install a wind energy conversion system at four sites in Algeria.

References
  1. C. G. Justus: Nationwide assessment of potential power output from aero-generators. in Proc. 2nd U. S. Nat. Conf. Wind Engineering Research, Ft. Collins, CO, Jun. 22–25, 1975.
  2. J. P. Hennessey, Jr: Some aspects of wind power statistics and performance analysis of a 6MWwind turbine-generator. J. Appl. Meteorol. , vol. 16, no. 2, pp. 119–28, Feb. 1997.
  3. R. B. Corotis: Stochastic Modeling of Site Wind Characteristics. ERDA Rep. RLO/2342-77/2, Sep. 1977.
  4. R. B. Corotis, A. B. Sigl, and J. Klein: Probability modeling of wind velocity magnitude and persistence. Sol. Energy, vol. 20, no. 6, pp. 483–93, 1978.
  5. Rosen KR, Van Buskirk R, Garbesi K: Wind energy potential of coastal Eritrea: an analysis of sparse wind data. Solar Energy 1999; 66 (3):201–13.
  6. Li G: Feasibility of large scale offshore wind power for Hong Kong a preliminary study. Renewable Energy, 21; 2000; pp 387- 402.
  7. Lu L, Yang H, Burnett J: Investigation on wind power potential on Hong Kong an analysis of wind power and wind turbine characteristics. Renewable Energy 27; 2002; pp 1–12.
  8. Mathew S, Pandey KP, Kumar A: Analysis of wind regimes for energy estimation. Renewable Energy 25: 2002; pp 81–99.
  9. Corotis RB, Sigl AB, Klein J: Probability models of wind velocity magnitude and persistence. Solar Energy 1978; 20:483–93.
  10. Rehman S, Halawani TO, Husain T: Weibull parameters for wind speed distribution in Saudi Arabia. Solar Energy 1994; 53(6):473–9.
  11. Beyer HG, Nottebaum K: Synthesis of long-term hourly wind speed time series on the basis of European Wind Atlas data. Solar Energy 1995; 54(5):351–5.
  12. Lun IYF, Lam JC: A study of Weibull parameters using long-term wind observations. Renewable Energy 2000; 20:145–53.
  13. Tsang-Jung Chang, Yu-Ting Wu, Hua-Yi Hsu, Chia-Ren Chu, Chun-Min Liao: Assessment of wind characteristics and wind turbine characteristics in Taiwan. Renewable Energy 28 (2003) 851–871
  14. Pallabazzer R: Evaluation of wind-generator potentiality. Sol Energy, 1995; 55:49–59.
  15. Stevens MJM, Smulders PT: The estimation of the parameters of the Weibull wind speed distribution for wind energy utilization purpose. Wind Eng 1979; 3(2):132–45.
  16. Akpinar, EK, Akpinar, S: An assessment on seasonal analysis of wind energy characteristics and wind turbine characteristics. Energy Conversion and Management 46, 1848–67 (2005)
  17. N. Vaughn: Renewable Energy and the Environment. Press, Ed. 2009 pp 63 -101
  18. Gary L. Johnson: Wind energy systems. Electronic Edition Manhattan, October 10, 2006, pp. 61-70-157
  19. O. A. Jaramillo, M. A. Borja: Wind speed analysis in La Ventosa Mexico a bimodal probability distribution case. Renewable Energy 29 (2004), Elsevier, pp. 1624-1628
  20. Balouktsis, A, Chassapis, D, Karapantsios, TD: A nomogram method for estimating the energy produced by wind turbine generators. Solar Energy 72, 251–259 (2002)
  21. Mathew Sathyajith et al. Wind Energy: Fundamentals, Resource Analysis and Economics. Springer-Verlag Berlin Heidelberg 2006; 169-170
  22. Justus C. G. , Mikhail W. R: Height variation of wind Speed and wind distributions statistics. Geophysical Research Letters. 1976. Vol. 3, No 5. P. 261-264
  23. Tenneekes A. : The logarithmic wind profile. J. of Atmospheric sciences, vol. 30, pp. 234:238, 1973.
  24. Mikhail A. S:Height Extrapolation of Wind Data. ASME, vol. 107, pp. 10- 14, 1985.
  25. Poje S. , B. Cividini: Assessment of Wind Energy Potential in Croatia. Solar Energy, Vol. 41 N°6 pp 543 554, 1988.
Index Terms

Computer Science
Information Sciences

Keywords

Probability density function power curve law capacity factors wind turbine generators optimum siting energy output.