Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, Australia

Modelling wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyze wind patterns in Melbourne, Australia. Three-hourly wind data during 2004-2008 was obtained from the Australian Government, Bureau of Meteorology, for Avalon Airport...

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Main Author: Mayuening Eso, Prashanth Gururaja and Rhysa McNeil
Format: Article
Language:English
Published: Technoscience Publications 2021-06-01
Series:Nature Environment and Pollution Technology
Subjects:
Online Access:https://neptjournal.com/upload-images/(25)B-1137.pdf
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spelling doaj-3e50c24be4e84192930981e99bcaf41f2021-06-14T07:25:55ZengTechnoscience PublicationsNature Environment and Pollution Technology0972-62682395-34542021-06-0120266567310.46488/NEPT.2021.v20i02.025Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, AustraliaMayuening Eso, Prashanth Gururaja and Rhysa McNeilModelling wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyze wind patterns in Melbourne, Australia. Three-hourly wind data during 2004-2008 was obtained from the Australian Government, Bureau of Meteorology, for Avalon Airport, Essendon Airport, Point Wilson, and View Bank stations. A logistic regression model was used to investigate the pattern of 3-hourly winds and gust prevalence while a linear regression model was applied to investigate wind speed trends. The 3-hour periods of the day, month, and year were used as the independent variables in the analysis. At four stations, wind speed and wind gust prevalence were mostly high between 9 AM and 6 PM. The monthly wind and wind gust prevalence were high from November to January while the highest annual prevalence occurred in 2007. The wind speed increased from 7 AM to 6 PM within which the maximum occurred. The monthly wind speed increased from November to January where it attained the maximum, decreasing to a minimum in May. The annual mean wind speed was highest in 2007.https://neptjournal.com/upload-images/(25)B-1137.pdfwind prevalence, wind gust, wind speed, logistic and linear regression
collection DOAJ
language English
format Article
sources DOAJ
author Mayuening Eso, Prashanth Gururaja and Rhysa McNeil
spellingShingle Mayuening Eso, Prashanth Gururaja and Rhysa McNeil
Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, Australia
Nature Environment and Pollution Technology
wind prevalence, wind gust, wind speed, logistic and linear regression
author_facet Mayuening Eso, Prashanth Gururaja and Rhysa McNeil
author_sort Mayuening Eso, Prashanth Gururaja and Rhysa McNeil
title Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, Australia
title_short Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, Australia
title_full Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, Australia
title_fullStr Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, Australia
title_full_unstemmed Statistical Modelling of 3-Hourly Wind Patterns in Melbourne, Australia
title_sort statistical modelling of 3-hourly wind patterns in melbourne, australia
publisher Technoscience Publications
series Nature Environment and Pollution Technology
issn 0972-6268
2395-3454
publishDate 2021-06-01
description Modelling wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyze wind patterns in Melbourne, Australia. Three-hourly wind data during 2004-2008 was obtained from the Australian Government, Bureau of Meteorology, for Avalon Airport, Essendon Airport, Point Wilson, and View Bank stations. A logistic regression model was used to investigate the pattern of 3-hourly winds and gust prevalence while a linear regression model was applied to investigate wind speed trends. The 3-hour periods of the day, month, and year were used as the independent variables in the analysis. At four stations, wind speed and wind gust prevalence were mostly high between 9 AM and 6 PM. The monthly wind and wind gust prevalence were high from November to January while the highest annual prevalence occurred in 2007. The wind speed increased from 7 AM to 6 PM within which the maximum occurred. The monthly wind speed increased from November to January where it attained the maximum, decreasing to a minimum in May. The annual mean wind speed was highest in 2007.
topic wind prevalence, wind gust, wind speed, logistic and linear regression
url https://neptjournal.com/upload-images/(25)B-1137.pdf
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