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首页> 外文期刊>Sustainable Energy Technologies and Assessments >Performance analysis of numerical methods for determining Weibull distribution parameters applied to wind speed in Mato Grosso do Sul, Brazil
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Performance analysis of numerical methods for determining Weibull distribution parameters applied to wind speed in Mato Grosso do Sul, Brazil

机译:基于巴西马托克罗索苏莫斯速率测定Weibull分布参数的数值方法的性能分析

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摘要

Brazil is one of the countries that invests the most in renewable energy generation. The share of wind power sources in the Brazilian Electricity Matrix rose from 0.9% in 2012 to 7.6% in 2018. The wind resource assessment is a crucial step in planning a wind energy project. Weibull distribution function is used to determine wind power potential for the investigated site and the distribution parameters are estimated by numerical methods. This study focus on the similarity and analyses of hourly wind speed data series. In this study, six numerical methods (Graphical Method, Maximum Likelihood Method, Modified Maximum Likelihood Method, Moment Method, Empirical Method and Power Density Method) are applied for estimating Weibull distribution parameters in 27 stations in the state of Mato Grosso do Sul, Brazil. The stations were grouped according to the similarity of their data series, and for each group the data series were separated into data series for calibration and data series for the accuracy analysis of the methods. The accuracy of the methods was evaluated using three different statistical analysis techniques. The Maximum Likelihood Method and the Modified Maximum Likelihood Method were the best methods for analyzing most of the data series in the stations.
机译:巴西是投资于可再生能源的国家之一。巴西电力矩阵中的风电源的份额从2012年增加到2018年的0.9%至7.6%。风力资源评估是规划风能项目的关键步骤。 Weibull分布函数用于确定调查部位的风力电位,并通过数值方法估计分布参数。本研究重点是每小时风速数据系列的相似性和分析。在本研究中,六种数值方法(图形方法,最大似然法,改进的最大似然法,矩法,经验方法和功率密度方法,用于估算Mato Grosso Do Sul,巴西Mato Grosso Do Sul州的27站中的Weibull分布参数。该站根据其数据系列的相似性进行分组,对于每个组,数据系列分为数据系列以进行校准和数据序列,以便对方法的准确性分析进行校准和数据序列。使用三种不同的统计分析技术评估方法的准确性。最大似然方法和修改的最大似然方法是用于分析车站中大多数数据系列的最佳方法。

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