Use of MinMaxEnt distributions defined on basis of MaxEnt method in wind power study

Energy Conversion and Management

Volumn 49, Issue 4, 2008, Pages 660-677

  Shamilov, Aladdin ^a   Kantar, Yeliz Mert ^a   Usta, Ilhan ^a  

^a ANADOLU UNIVERSITY   (Turkey)

Author keywords

Kullback Leibler measure; MaxEnt distribution; MaxEnt method; Wind power; Wind speed data

Indexed keywords

DATA REDUCTION; ELECTRIC POWER DISTRIBUTION; STATISTICAL METHODS; WEIBULL DISTRIBUTION; WIND EFFECTS;

WIND POWER DENSITY; WIND POWER POTENTIAL; WIND SPEED DISTRIBUTION;

WIND POWER;

EID: 39749164485     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2007.07.045     Document Type: Article

References (44)

1. Patel M.R. Wind and solar power systems (1999), CRC Press p. 351
2. Justus C.G., Hargraves W.R., and Yalcin A. Nationwide assessment of potential output from wind powered generators. J Appl Meteorol 15 (1976) 673-678
3. Celik A.N. Assessing the suitability of wind speed probability distribution functions based on wind power density. Renew Energy 28 (2003) 1563-1574
4. 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 (2003) 593-604
5. Hennessey J.P. A comparison of the Weibull and Rayleigh distributions for estimating wind power potential. Wind Eng 2 (1978) 156-164
6. Joseph P., and Hennesessey J. Some aspects of wind power statistics. J Appl Meteorol 16 2 (1977) 119-128
7. Harris R.I. Errors in GEV analysis of wind epoch maxima from Weibull parents. Wind Struct 9 3 (2006) 179-191
8. Takle E.S., and Brown J.M. Note on the use of Weibull statistics to characterize wind-speed data. J Appl Meteorol 17 (1978) 556-559
9. 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
10. Akpi{dotless}nar E.K., and Akpi{dotless}nar S. Determination of the wind energy potential for Maden, Turkey. Energy Convers Manage 45 18-19 (2004) 2901-2914
11. Ulgen K., and Hepbasli A. Determination of Weibull parameters for wind energy analysis of Izmir, Turkey. Int J Energy Res 26 (2002) 495-506
12. Weisser D. A wind energy analysis of Grenada: an estimation using the 'Weibull' density function. Renew Energy 28 (2003) 1803-1812
13. Akpinar E.K., and Akpinar S. An assessment on seasonal analysis of wind energy characteristics and wind turbine characteristics. Energy Convers Manage 46 (2005) 1848-1867
14. Garcýa A., Torres J.L., Prieto E., and De Francisco A. Fitting wind speed distributions: a case study. Solar Energy 62 (1998) 139-144
15. Rosen K., van Buskirk R., and Garbesi K. Wind energy potential of Coastal Eritrea: an analysis of sparse wind data. Solar Energy 66 (1999) 201-213
16. Persaud S., Flynn D., and Fox B. Potential for wind generation on the Guyana coastlands. Renew Energy 18 (1999) 175-189
17. Al-Nassar W., Alhajraf S., Al-Enizi A., and Al-Awadhi L. Potential wind power generation in the State of Kuwait. Renew Energy 30 (2005) 2149-2161
18. Al-Hasan M., and Nigmatullin R.R. Identification of the generalized Weibull distribution in wind speed data by the eigencoordinates method. Renew Energy 28 (2003) 93-110
19. 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
20. Ramazan K., Ozgur M.A., Erbas O., and Tugcu A. The analysis of wind data and wind energy potential in Kutahya, Turkey. Renew Sustain Energy Rev 8 (2004) 277-288
21. Genç A., Esiroglu M., Pekgor A., Oturanc G., Hepasli A., and Ulgen K. Estimation of the wind power potential using Weibull distribution. Energy Sources 27 (2005) 809-822
22. Tuller S.E., and Brett A.C. The characteristics of wind velocity that favor the fitting of a Weibull distribution in wind speed analysis. J Appl Meteorol 23 (1984) 124-134
23. Ebrahimi N. The maximum entropy method for lifetime distributions. Sankhya: The Indian J Stat 62 (2000) 236-243
24. Lind N.C., Hong H.P., and Solana V.A. A cross-entropy method for flood probability analysis. Stochast Hydrol Hydraul 3 3 (1989) 191-202
25. Pandey M.D. Direct estimation of quantile functions using the maximum entropy principle. Struct Saf 22 1 (2000) 61-79
26. Pandey M.D. Minimum cross entropy method for extreme value estimation using peaks-over-threshold data. Struct Saf 23 (2001) 345-363
27. Wu X. Calculation of maximum entropy densities with application to income distribution. J Econom 115 (2003) 347-354
28. Li M., and Li X. On the probabilistic distribution of wind speeds: theoretical development and comparison with data. Int J Energy 1 2 (2004) 237-255
29. Li M., and Li X. Investigation of wind characteristics and assessment of wind energy potential for Waterloo Region, Canada. Energy Convers Manage 46 (2005) 3014-3033
30. Li M., and Li X.G. MEP-type distribution function: a better alternative to Weibull function for wind speed distributions. Renew Energy 30 8 (2005) 1221-1240
31. 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 15-16 (2005) 2564-2577
32. Shannon C.E. A mathematical theory of communications. Bell Syst Tech J (1948) 379-623
33. Jaynes ET. Papers on probability, statistics and statistical physics. Netherlands: D. Reidel, Dordrecht, 1983.
34. Kapur J.N., and Kesavan H.K. Entropy optimization principles with applications (1992), Academic Press, Inc., London
35. Srikanth M., Kesavan H.K., and Roe P.H. Probability density function estimation using the MinMax measure. IEEE Trans Syst Man Cybernetics - Part C: Appl Rev 30 (2000) 77-83
36. Miller G, Horn D. Maximum entropy approach to probability density estimation. In: IEEE 1998 second international conference on knowledge-based intelligent electronic system, 21-23 April, 1998. p. 225-30.
37. Li M., and Li X. A second-order Newton-Raphson method for improved numerical stability in the determination of droplet size distribution in sprays. Atomization Spray 16 1 (2006) 71-82
38. Akpinar E.K., and Akpinar S. Wind energy analysis based on maximum entropy principle (MEP) type distribution function. Energy Convers Manage 48 4 (2007) 1140-1149
39. Groutage D. A fast algorithm for computing minimum cross-entropy positive time-frequency distributions. IEEE Trans Signal Process 45 8 (1997) 1954-1970
40. The Anadolu Meydan Meteorology Office, The Directorate of Eskisehir Meteorological Office, Turkey.
41. Seguro J.V., and Lambert T.W. Modern estimation of the parameters of the Weibull probability density distribution. J Wind Eng Ind Aerodyn 85 (2000) 75-84
42. Shamilov A, Mert Kantar Y. On a true method obtaining probability distributions based on maximum entropy principle, The Scientific and Pedagogical News of Odlar Yurdu University (Series of physical, mathematical technical and natural sciences) vol. 16, 2006.
43. Shamilov A., Usta I., and Kantar Y.M. The distribution of minimizing maximum entropy: alternative to Weibull distribution for wind speed. WSEAS Trans Math 5 (2006) 695-700
44. Shamilov A. A development of entropy optimization methods. WSEAS Trans Math 5 (2006) 568-575