NDLI: Statistical analysis and Hurst parameter estimation for wind speed in Kirklareli area of Turkey

Content Provider	IEEE Xplore Digital Library
Author	Akinci, T.C. Guseinoviene, E. Seker, S. Nayir, A.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., Klaipeda Univ., Klaipeda, Lithuania (Guseinoviene, E.) \|\| Dept. of Comput. Program., Fatih Univ., Istanbul, Turkey (Nayir, A.) \|\| Electr. Eng. Dept., Istanbul Tech. Univ., Istanbul, Turkey (Seker, S.) \|\| Dept. of Electr. & Electron. Eng., Kirklareli Univ., Kirklareli, Turkey (Akinci, T.C.)
Abstract	In this study, a wind speed data of the Kirklareli region of Turkey is considered and Hurst parameter is calculated for this data. For this purpose at first statistical parameters of the wind speed data are calculated. And, as a result of this analysis it is determined as a non-gaussian distribution. After that, it is shown as Weibull distribution and its statistical parameters are computed. The Hurst parameter is a special indicator to present the long range dependency and self-similarity. According to the results of this analysis, it can be determined as 0.256 and it is used as an indicator of long range dependency as well as its fractal dimension. In this manner, this is an original study to this field as well as the statistical analysis. As a one of the most important results, the finding of this study shows that the wind speed data has an autocorrelation function hyperbolically.
Sponsorship	IEEE Ind. Appl. Soc.
Starting Page	1
Ending Page	5
File Size	728122
Page Count	5
File Format	PDF
ISBN	9781467352697
e-ISBN	9781467352710
DOI	10.1109/EVER.2013.6521592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-03-27
Publisher Place	Monaco
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wind energy Statistical analysis Wind speed Statistical parameters Hurst parameter Educational institutions Weibull distribution Standards
Content Type	Text
Resource Type	Article

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