A collection and categorization of open‐source wind and wind power datasets. Issue 10 (4th July 2022)

• Record Type: Journal Article
• Authors: Effenberger, Nina; Ludwig, Nicole
• Is Part Of: Wind energy. Volume 25:Issue 10(2022)
• Page Start: 1659
• Page End: 1683
• Publication Date: 2022-07-04
• Subjects: open‐source data -- time series forecasting -- wind power forecasting; Wind power -- Periodicals; 621.312136
• DOI: 10.1002/we.2766
• Languages: English
• ISSNs: 1095-4244

Abstract

Abstract: 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.