Wind power and other forms of renewable energy sources play an ever more important role in the energy supply of today's power grids. Forecasting renewable energy sources has therefore become essential in balancing the power grid. While a lot of focus is placed on new forecasting methods, little attention is given on how to compare, reproduce and transfer the methods to other use cases and data. One reason for this lack of attention is the limited availability of open-source datasets, as many currently used datasets are non-disclosed and make reproducibility of research impossible. This unavailability of open-source datasets is especially prevalent in commercially interesting fields such as wind power forecasting. However, with this paper we want to enable researchers to compare their methods on publicly available datasets by providing the, to our knowledge, largest up-to-date overview of existing open-source wind power datasets, and a categorization into different groups of datasets that can be used for wind power forecasting. We show that there are publicly available datasets sufficient for wind power forecasting tasks and discuss the different data groups properties to enable researchers to choose appropriate open-source datasets and compare their methods on them.
翻译:风能和其他形式可再生能源在当今电网的能源供应中发挥着越来越重要的作用。因此,预测可再生能源对于平衡电网至关重要。虽然对新的预测方法给予了很多重视,但很少注意如何比较、复制和将方法转移到其他用途案例和数据。这种缺乏注意的原因之一是开放源数据集的可得性有限,因为许多目前使用的数据集不公开,无法再研究。这种公开源数据集的缺乏在风能预报等商业上有趣的领域尤为普遍。然而,根据本文,我们希望使研究人员能够比较其公开数据集的方法,向我们的知识提供现有开放源的风能数据集的最大最新概览,并对可用于风能预报的不同数据集进行分类。我们显示,公开的数据集足以用于风能预报任务,并讨论不同数据组的特性,使研究人员能够选择适当的公开源数据集,并比较其使用的方法。