Bayesian analysis of geo-dependencies in wind speed

Daniel Canton, J. Perez, H. Jimenez
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Abstract

The estimation of the wind resource had a large increase in recent years due to the strong demand for renewable energy. Wind estimation is a dynamic problem due to its stochastic nature. Consequently, the study of wind speed in different places helps to know the geospatial dependencies that exist between them. In this paper, we present a stochastic process that analyzes the geographic dependencies in eight sites in the Metropolitan Area of Queretaro using a statistical approach using the Expectation-Maximization (EM) algorithm. The Spearman correlation coefficient is then used to determine the intensity in the relationship between each of the sites. The results of the experimentation were carried out in three scenarios, in different periods, in this way we can know the type of association in the sites during each period. In this way, the sites where wind power can be used to obtain wind energy are known.
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风速地理相关性的贝叶斯分析
近年来,由于对可再生能源的强烈需求,风能资源的估计有了很大的增长。由于风的随机性,风的估计是一个动态问题。因此,研究不同地方的风速有助于了解它们之间存在的地理空间依赖关系。在本文中,我们提出了一个随机过程,利用期望最大化(EM)算法的统计方法分析了克雷塔罗大都市区八个站点的地理依赖性。然后使用斯皮尔曼相关系数来确定每个站点之间关系的强度。实验结果在三个场景中进行,在不同的时期,通过这种方式,我们可以了解每个时期站点的关联类型。通过这种方式,可以利用风力发电获得风能的地点是已知的。
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