Statistical Modelling of 4-hourly Wind Patterns in Calcutta, India
The rising energy demands of the world and minimal availability of conservative energy sources have considerably increased the role of non-conventional sources of energy like solar and wind. The modelling of the prevalence of wind speed and trends helps in estimating the energy produced from wind fa...
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Veröffentlicht in: | Nature environment and pollution technology 2019-03, Vol.18 (1), p.73-80 |
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description | The rising energy demands of the world and minimal availability of conservative energy sources have considerably increased the role of non-conventional sources of energy like solar and wind. The modelling of the prevalence of wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyse the wind patterns in India. Hourly wind data during 2004-2008 were obtained from the National Renewable Energy Laboratory for the study. A logistic regression model was initially used to investigate 4-hourly wind prevalence and the pattern of wind gust. A linear regression model was then applied to investigate wind speed trends. The 4-hour periods of the day, months, and year factors of wind were used as the independent variables in the statistical analysis. The results showed that wind prevalence was mostly higher between 4 AM to 4 PM within the day (90%). Analysis of the monthly wind prevalence revealed higher percentage between April to June (90%), while higher annual prevalence was revealed in 2007 and 2008 (85%). Wind speed trends (4-hourly periods) was observed to increasing from 4 AM to 4 PM within which the maximum occurred. Monthly wind speed was seen to be increasing from January to April where it attains the maximum (13 ms-1) and reduces it to minimum in November (3 ms-1). Annual mean wind speed has reduced by 4 ms-1 between 2004 and 2008. |
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The modelling of the prevalence of wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyse the wind patterns in India. Hourly wind data during 2004-2008 were obtained from the National Renewable Energy Laboratory for the study. A logistic regression model was initially used to investigate 4-hourly wind prevalence and the pattern of wind gust. A linear regression model was then applied to investigate wind speed trends. The 4-hour periods of the day, months, and year factors of wind were used as the independent variables in the statistical analysis. The results showed that wind prevalence was mostly higher between 4 AM to 4 PM within the day (90%). Analysis of the monthly wind prevalence revealed higher percentage between April to June (90%), while higher annual prevalence was revealed in 2007 and 2008 (85%). Wind speed trends (4-hourly periods) was observed to increasing from 4 AM to 4 PM within which the maximum occurred. Monthly wind speed was seen to be increasing from January to April where it attains the maximum (13 ms-1) and reduces it to minimum in November (3 ms-1). 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The modelling of the prevalence of wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyse the wind patterns in India. Hourly wind data during 2004-2008 were obtained from the National Renewable Energy Laboratory for the study. A logistic regression model was initially used to investigate 4-hourly wind prevalence and the pattern of wind gust. A linear regression model was then applied to investigate wind speed trends. The 4-hour periods of the day, months, and year factors of wind were used as the independent variables in the statistical analysis. The results showed that wind prevalence was mostly higher between 4 AM to 4 PM within the day (90%). Analysis of the monthly wind prevalence revealed higher percentage between April to June (90%), while higher annual prevalence was revealed in 2007 and 2008 (85%). Wind speed trends (4-hourly periods) was observed to increasing from 4 AM to 4 PM within which the maximum occurred. Monthly wind speed was seen to be increasing from January to April where it attains the maximum (13 ms-1) and reduces it to minimum in November (3 ms-1). 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The modelling of the prevalence of wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyse the wind patterns in India. Hourly wind data during 2004-2008 were obtained from the National Renewable Energy Laboratory for the study. A logistic regression model was initially used to investigate 4-hourly wind prevalence and the pattern of wind gust. A linear regression model was then applied to investigate wind speed trends. The 4-hour periods of the day, months, and year factors of wind were used as the independent variables in the statistical analysis. The results showed that wind prevalence was mostly higher between 4 AM to 4 PM within the day (90%). Analysis of the monthly wind prevalence revealed higher percentage between April to June (90%), while higher annual prevalence was revealed in 2007 and 2008 (85%). Wind speed trends (4-hourly periods) was observed to increasing from 4 AM to 4 PM within which the maximum occurred. Monthly wind speed was seen to be increasing from January to April where it attains the maximum (13 ms-1) and reduces it to minimum in November (3 ms-1). Annual mean wind speed has reduced by 4 ms-1 between 2004 and 2008.</abstract><cop>Karad</cop><pub>Technoscience Publications</pub><tpages>8</tpages></addata></record> |
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subjects | Alternative energy sources Climate change Ecosystems Energy Energy sources Independent variables Mathematical models Modelling Probability distribution Regression analysis Regression models Renewable energy Science Solar energy Statistical analysis Statistical models Studies Topography Trends Weather Wind farms Wind power Wind speed |
title | Statistical Modelling of 4-hourly Wind Patterns in Calcutta, India |
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