As wind energy penetration is expected to grow in the future, wind resource assessment becomes important in modern power grid operations. Selecting an appropriate wind farm site can benefit from understanding nonstationary characteristics of wind speeds. In particular, wind speed exhibits a diurnal pattern and the pattern varies, day-by-day and site-by-site. The goal of this article is to develop a new probabilistic modeling approach for quantifying variation in the wind diurnal pattern for assessing wind resource at unmonitored locations. Specifically, we formulate the coefficient of wind model as a latent random process and incorporate both day-to-day and spatial variability into the latent process. The estimation performance of the proposed approach is validated with actual data collected in west Texas. The results demonstrate that our approach can capture both spatially- and daily-varying patterns and quantify the uncertainty successfully.

中文翻译：

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风资源评估中风日变化的概率表征

随着风能渗透率预计在未来增长，风能评估在现代电网运营中变得至关重要。了解风速的非平稳特性可以选择合适的风电场站点。尤其是，风速表现为昼夜模式，并且该模式每天和每个站点都在变化。本文的目的是开发一种新的概率建模方法，用于量化风日模式中的变化，以评估未监控位置的风资源。具体来说，我们将风模型的系数公式化为潜在的随机过程，并将日常和空间可变性都纳入潜在过程。所提方法的估计性能已在德克萨斯州西部收集的实际数据中得到验证。