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Estimation of wind energy potential using finite mixture distribution models

机译:使用有限混合分布模型估算风能潜力

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In this paper has been investigated an analysis of wind characteristics of four stations (Eiazig, Elazig-Maden, Elazig-Keban, and Elazig-Agin) over a period of 8 years (1998-2005). The probabilistic distributions of wind speed are a critical piece of information needed in the assessment of wind energy potential, and have been conventionally described by various empirical correlations. Among the empirical correlations, there are the Weibull distribution and the Maximum Entropy Principle. These wind speed distributions can not accurately represent all wind regimes observed in that region. However, this study represents a theoretical approach of wind speed frequency distributions observed in that region through applications of a Singly Truncated from below Normal Weibull mixture distribution and a two component mixture Weibull distribution and offer less relative errors in determining the annual mean wind power density. The parameters of the distributions are estimated using the least squares method and Stattstica software. The suitability of the distributions is judged from the probability plot correlation coefficient plot R~2, RMSE and x~2. Based on the results obtained, we conclude that the two mixture distributions proposed here provide very flexible models for wind speed studies.
机译:在本文中,我们对四个站(Eiazig,Elazig-Maden,Elazig-Keban和Elazig-Agin)的风向进行了为期8年(1998-2005年)的分析。风速的概率分布是评估风能潜力所需的重要信息,并且通常已通过各种经验相关性进行了描述。在经验相关性中,有威布尔分布和最大熵原理。这些风速分布不能准确代表该区域内观察到的所有风况。然而,这项研究代表了通过应用正态截断法从下方的威布尔混合分布和两成分混合威布尔分布在该区域观测到的风速频率分布的理论方法,并且在确定年平均风能密度时提供了相对较小的误差。使用最小二乘法和Stattstica软件估算分布的参数。根据概率图相关系数图R〜2,RMSE和x〜2判断分布的适用性。根据获得的结果,我们得出结论,此处提出的两种混合物分布为风速研究提供了非常灵活的模型。

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