论文标题

开源风能和风能数据集的收集和分类

A Collection and Categorization of Open-Source Wind and Wind Power Datasets

论文作者

Effenberger, Nina, Ludwig, Nicole

论文摘要

风能和其他形式的可再生能源在当今电网的能源供应中起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。虽然将很多重点放在新的预测方法上,但对如何比较,复制和将方法转移到其他用例和数据上几乎没有关注。这种缺乏关注的原因之一是开源数据集的可用性有限,因为许多当前使用的数据集没有限制,因此无法进行研究的可重复性。开源数据集的这种不可用,在商业上有趣的领域(例如风力电力预测)中尤其普遍。但是,借助本文,我们希望使研究人员能够通过提供现有开源风力电力数据集的最新概述,并将其分类为可用于风能预测的不同数据集,并将其分类为不同的数据集。我们表明,有足够的公开数据集用于风能预测任务,并讨论了不同的数据组属性,以使研究人员能够选择适当的开源数据集并在其上比较其方法。

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.

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