Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean

Applied Energy

Volumn 87, Issue 8, 2010, Pages 2566-2573

  Akdag S A ^a   Bagiorgas, H S ^b   Mihalakakou, G ^b  

^a ISTANBUL TECHNICAL UNIVERSITY   (Turkey)

^b UNIVERSITY OF IOANNINA   (Greece)

Author keywords

Coefficient of determination; Maximum likelihood method; Mixed Weibull distribution; Mixture distributions; Probability density distribution; Simple Weibull distribution

Indexed keywords

DISTRIBUTION FUNCTIONS; MAXIMUM LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATION; MIXTURES; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; SPEED; WIND; WIND EFFECTS; WIND POWER;

COEFFICIENT OF DETERMINATION; MAXIMUM LIKELIHOOD METHODS; MIXED WEIBULL DISTRIBUTION; MIXTURE DISTRIBUTIONS; PROBABILITY DENSITY DISTRIBUTION;

WEIBULL DISTRIBUTION;

BUOY SYSTEM; ERROR ANALYSIS; MAXIMUM LIKELIHOOD ANALYSIS; PROBABILITY DENSITY FUNCTION; SOFTWARE; WEIBULL THEORY; WIND POWER; WIND VELOCITY;

MEDITERRANEAN SEA; MEDITERRANEAN SEA (EAST);

EID: 77953136645     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2010.02.033     Document Type: Article

References (46)

1. Jaramillo O.A., and Borja M.A. Bimodal versus Weibull wind speed distributions: an analysis of wind energy potential in La Venta, Mexico. Wind Eng 28 2 (2004) 225-234
2. Jaramillo O.A., and Borja M.A. Wind speed analysis in La Ventosa, Mexico: a bimodal probability distribution case. Renew Energy 29 (2004) 1613-1630
3. Maqsood A., and Aslam M. A comparative study to estimate the parameters of mixed-Weibull distribution. Pak J State Oper Res IV 1 (2008) 1-8
4. Carta J.A., and Ramirez P. Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions. Renew Energy 32 (2007) 518-531
5. Titterington D.M., Smith A.F.M., and Makov U.E. Statistical analysis of finite mixture distributions. 2nd ed. (1995), Wiley, New York
6. Johnson N.L., Kotz S., and Balakrishnan N. Continuous univariate distributions. 2nd ed. (1994), Wiley, New York
7. Kaylan A.R., and Harris C.M. Efficient algorithms to derive maximum-likelihood estimates for finite exponential and Weibull mixtures. Comput Oper Res 3 (1981) 97-104
8. Chandanie Wijayalatha Perera W. Estimation and tests of fit for two component Weibull mixtures. Master Thesis, Simon Fraser University Dept. of Mathematics and Statistics; August 1992.
9. Carta J.A., Ramirez P., and Velazquez S. A review of wind speed probability distributions used in wind energy analysis - case studies in the Canary Islands. Renew Sustain Energy Rev 13 (2009) 933-955
10. Burton T., Sharpe D., Jenkins N., and Bossanyi E. Wind energy handbook. 1st ed. (2001), Wiley, New York
11. Ramirez P., and Carta J.A. The use of wind probability distributions derived from the maximum entropy principle in the analysis of wind energy. A case study. Energy Convers Manage 47 (2006) 2564-2577
12. Carta J.A., and Ramirez P. Use of finite mixture distribution models in the analysis of wind energy in the Canarian Archipelago. Energy Convers Manage 48 (2007) 281-291
13. Kececioglu DB, Wang W. Parameter estimation for mixed-Weibull distribution. In: Proceedings of the reliability and maintainability symposium. Anaheim (CA) USA; 19-22 January 1998. p. 247-252.
14. Justus C.G. Winds and wind system performance. 1st ed. (1978), Franklin Institute Press, USA
15. Bury K. Statistical distributions in engineering. 1st ed. (1999), Cambridge University Press, UK
16. Thompson W.J. Atlas for computing mathematical functions. 1st ed. (1997), Wiley, New York
17. Poulos S.E., Drakopoulos P.G., and Collins M.B. Seasonal variability in sea surface oceanographic conditions in the Aegean Sea (Eastern Mediterranean): an overview. J Mar Syst 13 1-4 (1997) 225-244
18. Incecik S., and Erdogmus F. An investigation of the wind power potential on the western coast of Anatolia. Renew Energy 6 7 (1995) 863-865
19. Klaić Z.B., Pasarić Z., and Tudor M. On the interplay between sea-land breezes and Etesian winds over the Adriatic. J Mar Syst 78 1 (2009) S101-S118
20. Borhan Y. Mesoscale interactions on wind energy potential in the northern Aegean region: a case study. Renew Sustain Energy Rev 2 4 (1998) 353-360
21. Hamad N., Millot C., and Taupier-Letage I. The surface circulation in the eastern basin of the Mediterranean Sea. Sci Mar 70 3 (2006) 457-503
22. Rider P.R. Estimating the parameters of mixed, Poisson, Binomial and Weibull Distributions by the method of moments. Bull Inst Int Stat 39 Part 2 (1961)
23. Kao J.H.K. A graphical estimation of mixed Weibull parameters in life-testing of electron tubes. Technometrics 1 (1959) 389-407
24. McLachlan G., and Krishnan T. The EM algorithm and extensions. 1st ed. (1996), Wiley, UK
25. McLachlan G., and Peel D. Finite mixture models. 1st ed. (2000), Wiley, UK
26. Schunn CD, Wallach D. Evaluating goodness-of-fit in comparison of models to data. In: Tack W. editor. Psychologie der kognition. Saarbrueken, Germany: Reden and Vorträge anlässlich der Emeritierung von Werner Tack University of Saarland Press; 2005. p. 115-54.
27. Garcia A., Torres J.L., Prieto E., and De Francisco A. Fitting wind speed distributions; a case study. Sol Energy 62 (1998) 139-144
28. Celik A.N. Assessing the suitability of wind speed probability distribution functions based on wind power density. Renew Energy 28 (2003) 1563-1574
29. Akpinar E.K., and Akpinar S. Determination of the wind energy potential for Maden-Elazig, Turkey. Energy Convers Manage 45 (2004) 2901-2914
30. US Dept. of Energy. Wind powering America; September 2009. .
31. Manwell JF, McGowan JG, Rogers AL. Wind energy explained: theory, design and application; 2002.
32. Harris R.I. Generalised pareto methods for wind extremes. Useful tool or mathematical mirage?. J Wind Eng Ind Aerodyn 93 (2005) 341-360
33. Harris R.I. Errors in gev analysis of wind epoch maxima from weibull parents. Wind Struct 9 (2006) 179-191
34. Ramirez P., and Carta J.A. Influence of the data sampling interval in the estimation of the parameters of the weibull wind speed probability density distribution: a case study. Energy Convers Manage 46 (2005) 2419-2438
35. Hennessey J.P. Some aspects of wind power statistics. J Appl Meteorol 16 (1977) 119-128
36. Celik A.N. A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey. Renew Energy 29 (2004) 593-604
37. Stewart D.A., and Essenwanger O.M. Frequency distribution of wind speed near the surface. J Appl Meteorol 17 (1978) 1633-1642
38. Auwera L.V., Meyer F., and Malet L.M. The use of the Weibull three-parameter model for estimating mean wind power densities. J Appl Meteorol 19 (1980) 819-825
39. Winger W.K. Estimating wind power feasibility. Power Eng August (1976) 58-61
40. Winger W.K. Estimations of wind speed frequency distributions using only the monthly average and fastest mile data. J Appl Meteorol 16 (1977) 244-247
41. Carta J.A., Ramirez P., and Velazquez S. Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation. Energy Convers Manage 49 (2008) 2647-2655
42. Luna R.E., and Church H.W. Estimation of long-term concentrations using a ''Universal'' wind speed distribution. J Appl Meteorol 13 (1974) 910-916
43. Bardsley W.E. Note on the use of inverse Gaussian distribution for wind energy applications. J Appl Meteorol 19 (1980) 1126-1130
44. Lavagnini A., Stellato G., and Tosato G.C. Climatological analysis of Italian data wind energy applications. In: Palz W., and Schnell W. (Eds). Wind energy vol. 2 (1983), D. Reider Publishing Company, Holland 97-103
45. Kiss P., and Janosi I.M. Comprehensive empirical analysis of ERA-40 surface wind speed distribution over Europe. Energy Convers Manage 49 (2008) 2142-2151
46. Chang T.-J., and Tu Y.-L. Evaluation of monthly capacity factor of WECS using chronological and probabilistic wind speed data: a case study of Taiwan. Renew Energy 32 (2007) 1999-2010