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General Information
ISSN:
2315-4462 (Print); 2373-3594 (Online)
Abbreviated Title:
Int. J Smart Grid Clean Energy
Frequency:
4 issues per year
Editor-in-Chief:
Prof. Danny Sutanto
DOI:
10.12720/sgce
APC:
500 USD
Indexed by:
Inspec (IET),
CNKI
, Crossref, Google Scholar,
etc
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Editor-in-Chief
Prof. Danny Sutanto
University of Wollongong, Australia
I am very excited to serve as the first Editor-in-Chief of the Journal of Smart Grid and Clean Energy (IJSGCE)and hope that the publication can enrich the readers’ experience .... [
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What's New
2024-03-28
March 28th, 2024 News! Vol. 13, No. 1 has been published online!
2024-01-04
IJSGCE will adopt Article-by-Article Work Flow. For the quarterly journal, each issue will be released at the end of the issue month.
2023-10-09
October 9th, 2023 News! Vol. 11, No. 4 has been published online!
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2021
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Vol. 10, No. 1, January 2021
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Statistical analysis of wind characteristic in Yanco agricultural institute, Australia
Author(s): Nour Khlaifat, Ali Altaee, John Zhou
Centre of Green Technology, University of Technology Sydney, Sydney, NSW 2007, Australia
International Journal of Smart Grid and Clean Energy
, vol. 10, no. 1, January 2021: pp.1-7
ISSN: 2315-4462 (Print)
ISSN: 2373-3594 (Online)
Digital Object Identifier: 10.12720/sgce.10.1.1-7
Abstract
: In this study, energy potential and the wind speed characteristics in Yanco agricultural institute in southwestern New South Wales (Australia) were investigated using wind speed from database at a height of 10 m during the period of April 2018 until August 2019. The objective of this study is to assess the wind speed profile using different probability distribution functions in order to evaluate the most suitable function depending on statistical indicators. The performance of Gamma, Lognormal, Rayleigh, and Weibull were compared with measured data. Results showed that the most accurate function is the Weibull distribution and hence it is used to calculate the wind power density. The annual average wind power is 43.404 W/m2 at an elevation of 10 m. The power-law exponent equation was utilized to create the variations of monthly mean wind speed at the heights of 40 m and 50 m. Finally, wind rose diagram showed that an even distribution of wind direction although the most prevailing wind direction falls between 180° and 240°.
Keywords
: Probability distribution function, wind power density, mean wind speed, wind rose
Full Paper.pdf
Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
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