A statistical analysis of wind distribution and wind power potential in the coastal region of South Africa

International Journal of Green Energy

Volumn 10, Issue 8, 2013, Pages 814-834

  Ayodele, T R ^a   Jimoh, A A ^a   Munda, J L ^a   Agee, J T ^a  

^a TSHWANE UNIVERSITY OF TECHNOLOGY   (South Africa)

Author keywords

South Africa; Statistical analysis; Weibull distribution; Wind power potential

Indexed keywords

COEFFICIENT OF DETERMINATION; ELECTRICITY GENERATION; POWER POTENTIAL; ROOT MEAN SQUARE ERRORS; SOUTH AFRICA; STATISTICAL DISTRIBUTION MODEL; TURBULENCE INTENSITY; WIND CHARACTERISTICS;

ANEMOMETERS; COASTAL ZONES; MEAN SQUARE ERROR; SEA LEVEL; STATISTICAL METHODS; WEIBULL DISTRIBUTION; WIND EFFECTS;

WIND POWER;

COASTAL ZONE; ELECTRICITY GENERATION; STATISTICAL ANALYSIS; WEIBULL THEORY; WIND POWER; WIND TURBINE; WIND VELOCITY;

SOUTH AFRICA;

EID: 84878332732     PISSN: 15435075     EISSN: 15435083     Source Type: Journal    
DOI: 10.1080/15435075.2012.727112     Document Type: Article

References (28)

1. A.W.E.A 2011. Wind Power Class, accessed (July, 2011), http://www.interwest.org/wiki/index.php?title=Wind-power-classes.
2. Akdag, S.A., and O. Guler. 2010. Wind characteristics analysis and determination of appropriate wind Turbine for Amasra-Black sea region, Turkey. International Journal of Green Energy 7:422-433.
3. Akpinar, E.K., and S. Akpinar. 2005. A statistical analysis of wind speed data used in installation of wind energy conversion system. Energy Conversion and Management 46:515-532.
4. Bilgili, M., B. Sahin, and A. Kahraman. 2004. Wind energy potential in Antakya and Iskenderun region, Turkey. Renewable Energy 29:1733-1745.
5. Celik, A.N. 2004 A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey. Renewable Energy 29:593-604.
6. Di Piazza, A., M.C. Di Piazza, A. Ragusa, and G. Vitale. 2010. Statistical processing of wind speed data for energy forecast and planning. International Conference on Renewable Energies and Power Quality (ICRPQ'10).[Ce: check this ref. style] Eskom 2011. Understanding electricity,http://www.eskom. co.za/live/content.php?.Category-ID=96.
7. Garcia, A., J.L. Torres, E. Prieto, and A. De Francisco. 1998. Fitting wind speed distributions: A case study. Solar Energy 62:139-144.
8. Genca, A., E. Murat, A. Pekgora, G. Oturancb, A. Hepbaslic, and K. Ulgend. 2005. Estimation of wind power potential using weibull distribution energy sources, Part A. Recovery, Utilization, and Environmental Effects 27:809-822.
9. Gupta, R., and A. Biswas. 2010. Wind data analysis of Silchar (Assam, India) by rayleigh's and weibull methods. Journal of mechanical Engineering Research 2:10-24.
10. Haghifam, M.R., and M. Omidvar. 2006.Wind farm modeling in reliability assessment of power system. International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Chicago, IL, pp. 1-5.
11. Inglesi-Lotz, R., and J. Blignant. 2011. South africa's electricity consumption: A sectoral decomposition aAalysis. Working Paper 2003, University of Pretoria.
12. Kaltschmitt, M., W. Streicher, and A. Wiese. 2007. Renewable energy: Technology,economics and environment. Berlin: Springer-Verlag.
13. Li, X. 2011. Green energy: Basic concepts and fundamentals. London: Springer-Verlag, ISBN 978- 1-84882-646-5.
14. Lu, L., H. Yang, and J. Burnett. 2002. Investigation on wind power potential on Hong Kong Islands-an analysis of wind power and wind turbine characteristic. Renewable Energy 27: 1-12.
15. Manwell, J.F., J.G. McGowan, and A.L. Rogers. 2002. Wind energy explained, theory, design and application. England: John Wiley and Sons.
16. Najid, S., A. Zaharim, A.M. Razali, M.S. Zainol, K. Ibrahim, and K. Sopian. 2009. Analzing the east coast Malaysia wind speed data. International Journal of Energy and Environment 3: 53-60.
17. NERSA. 2011. Rules on selection criteria for renewable energy projects under the REFIT www.ner.org.za/Admin?Document/Editor/Electricity/Legislation/ Regulatory%20Rule.
18. NIASA. 2011. Nuclear energy development in South Africa: http://www.word.nuclear.org/info.inf88.html.
19. Nigim, K.A., and P. Parker. 2007. Heuristic and probabilistic wind power availability estimation procedures: Improved tools for technology and site selection. Renewable Energy 32:638-648.
20. Sahin, B., and M. Bilgili. 2009. Wind characteristics and energy potential in Belen-Hatay, Turkey. International Journal of Green Energy. 6:157-172.
21. Santhyajith, M. 2006. Wind energy fundamentals, resources analysis and Economic. Springer Publisher.
22. Seguro, J.V., and T.W. Lambert. 2000. Modern estimation of the parameters of weibull wind speed distribution for wind energy analysis. Journal of Wind Engineering and Industrial Aerodynamics 85:75-84.
23. South. Africa. info. 2010. South Africa energy supply, http://www.southafrica.info/business/economy/infrastructure/energy.htm.
24. Szewczuk, S. 2010. Wind atlas for South Africa: Wind measurements and micro-scale modelling. Industrial and Commercial Use of Energy Conference. Cape Town. South Africa.
25. Ulgen, K. and A. Hepbasli. 2002. Determination of weibull parameters for wind energy analysis of Izmir, Turkey. International Journal of Energy Research 26:495-506.
26. WASA 2011. Data files: www.wasa.csir.co.za.
27. Weisser, D. 2003. A wind energy analysis of Grenada: An estimation using the weibull density function. Renewable Energy 28:1803-1812.
28. Zaharim, A., A.M. Razali, R.Z. Abidin, and K. Sopian. 2009. Fitting of statistical distributions to wind speed data in Malysia. European Journal of Scientific Research 26:6-12.