首页> 外文会议>2011 IEEE Power and Energy Society General Meeting: the electrification of transportation the grid of the future >Analysis of seasonal wind speed and wind power density distribution in Aimangala wind form at Chitradurga Karnataka using two parameter weibull distribution function
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Analysis of seasonal wind speed and wind power density distribution in Aimangala wind form at Chitradurga Karnataka using two parameter weibull distribution function

机译:利用两参数威布尔分布函数分析卡特拉塔克邦Chitradurga卡纳塔克邦Aimangala风型的季节风速和风功率密度分布。

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Modeling of wind speed variation is an essential requirement in the estimation of wind energy potential for a typical site. In this paper, the average wind from April 2007 to March 2008 in Aimangala at central dry zone part of Karnataka, India have been statistically analyzed to determine wind energy potential for electrical power generation by grouping the seasonal observations. We show that the wind speed distribution is represented by the typical two parameter weibull function for prediction of wind energy out put required for preliminary design and assessment of wind power plant. The shape and scale parameters of weibull function have been estimated seasonal basis to calculate the average wind speed and wind power density for the Aimangala station. The maximum power density was found to be 829.73 W/m2 in monsoon season and the minimum power density was found to be 186.15 W/m2 in winter season. The Weibull function using Weibull parameter estimated in this paper shown to provide more accurate prediction of average wind speed and average power density for the selected station. The seasonal variation of wind speed and wind density studied in this paper is useful to ensure optimum selection of wind turbine generator
机译:风速变化建模是估算典型站点风能潜力的基本要求。在本文中,对印度卡纳塔克邦中部干旱区部分地区阿曼加拉(Aimangala)2007年4月至2008年3月的平均风进行了统计分析,通过对季节观测进行分组,确定了发电的风能潜力。我们表明,风速分布由典型的两参数威布尔函数表示,用于预测风电厂的初步设计和评估所需的风能输出。威布尔函数的形状和比例参数已按季节估算,以计算Aimangala站的平均风速和风能密度。季风季节最大功率密度为829.73 W / m 2 ,冬季最小功率密度为186.15 W / m 2 。使用本文中估计的Weibull参数的Weibull函数显示,可以为所选站点提供更准确的平均风速和平均功率密度的预测。本文研究的风速和风密度的季节性变化有助于确保风力发电机的最佳选择

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