As part of Saudi Vision 2030, a major strategic framework developed by the Council of Economic and Development Affairs of Saudi Arabia, the country aims to reduce its dependency on oil and promote renewable energy for domestic power generation. Among the sustainable energy resources, solar energy is one of the leading resources because of the endowment of Saudi Arabia with plentiful sunlight exposure and year-round clear skies. This essentializes to forecast and simulate solar irradiance, in particular global horizontal irradiance (GHI), as accurately as possible, mainly to be utilized by the power system operators among many others. Motivated by a dataset of hourly solar GHIs, this article proposes a model for short-term point forecast and simulation of GHIs. Two key points, that make our model competent, are: (1) the consideration of the strong dependency of GHIs on aerosol optical depths and (2) the identification of the periodic correlation structure or cyclostationarity of GHIs. The proposed model is shown to produce better forecasts and more realistic simulations than a classical model, which fails to recognize the GHI data as cyclostationary. Further, simulated samples from both the models as well as the original GHI data are used to calculate the corresponding photovoltaic power outputs to provide a comprehensive comparison among them.

中文翻译：

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用于太阳全球水平辐照度时间预测和模拟的循环平稳模型

作为沙特愿景 2030 的一部分是沙特阿拉伯经济与发展事务委员会制定的一项重大战略框架，该国旨在减少对石油的依赖并促进可再生能源用于国内发电。在可持续能源中，太阳能是主要资源之一，因为沙特阿拉伯拥有充足的阳光照射和全年晴朗的天空。这对于尽可能准确地预测和模拟太阳辐照度，特别是全球水平辐照度 (GHI) 至关重要，主要供电力系统运营商等使用。受每小时太阳能 GHI 数据集的启发，本文提出了一种用于 GHI 的短期点预测和模拟的模型。使我们的模型胜任的两个关键点是：(1) 考虑到 GHI 对气溶胶光学深度的强烈依赖性； (2) 识别 GHI 的周期性相关结构或循环平稳性。与无法将 GHI 数据识别为循环平稳的经典模型相比，所提出的模型可以产生更好的预测和更逼真的模拟。此外，模型中的模拟样本以及原始 GHI 数据用于计算相应的光伏功率输出，以提供它们之间的综合比较。