利用Python编程建模进行韦伯分布拟合

Using Python Programming to Model Weber Distribution Fitting

风力发电量与风速的关系一直是电力行业从业者研究的热点之一,研究人员积极探索风力发电量与风速之间的关系。本次研究中,相关工作人员利用Python编程技术,计算风场的风速频率分布,由于研究过程中涉及大量随机变量以及连续变量,这些变量符合韦伯分布的特点,因此,研究人员引入了最小二乘法对风频数据进行韦伯分布拟合,通过这种方法求得c和k的具体数值。

The relationship between wind power generation and wind speed has always been a hot research topic for practitioners in the power industry,and researchers are actively exploring the relationship between wind power generation and wind speed.In this study,relevant personnel used Python programming technology to calculate the wind speed frequency distribution of the wind field.Due to the involvement of a large number of random and continuous variables in the research process,which conform to the characteristics of the Weber distribution,the researchers introduced the least squares method to fit the wind frequency data with the Weber distribution,and obtained the specific values of c and k.