Analysis of Wind Characteristics using ARMA & Weibull Distribution

A. Nayak, K. Mohanty
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引用次数: 1

Abstract

Rapid growth of population demands huge increase of electrical power that can’t be fulfilled with the expansion of conventional generation due to environmental concern. To meet the aggregating power demand, alternative generation like wind energy is getting more importance. Wind energy conversion system (WECS) transforms available speed at a location into electricity. But the problem associated with WECS is the uncertainty in the speed of the wind. Thus, efforts have to be made to showcase the randomness of the wind speed. Two famous methods time based auto regressive moving average (ARMA) and frequency based Weibull distribution are generally followed to fulfill the purpose. Both methods are used to develop models to fit to the observed speed. The accuracy of fitting in case of ARMA is checked through Box-Jenkins guidelines and F-Criterion. But in case of Weibull distribution, the parameters are determined with the estimation of statistical errors.
基于ARMA和威布尔分布的风特性分析
人口的快速增长需要大量的电力,由于环境问题,传统发电的扩张无法满足需求。为了满足综合电力需求,风能等替代能源越来越受到重视。风能转换系统(WECS)将某地的可用速度转换为电能。但与wcs相关的问题是风速的不确定性。因此,必须努力展示风速的随机性。通常采用基于时间的自回归移动平均(ARMA)和基于频率的威布尔分布两种著名的方法来实现这一目的。这两种方法都用来建立模型来拟合观测到的速度。在ARMA的情况下,拟合的准确性通过Box-Jenkins指南和f标准进行检查。但在威布尔分布情况下,参数是通过统计误差估计来确定的。
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