A Collection and Categorization of Open-Source Wind and Wind Power Datasets
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 3 of its 99 references that are in the map. First posted on arXiv 17 Feb 2022.
Builds on
3 of 99 references.
References · 3
Built on by
Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 0; 2026: 1.
5 papers.
- 2022SDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting Challenge at KDD Cup 2022cited by 21
- 2023Prediction of wind turbines power with physics-informed neural networks and evidential uncertainty quantificationcited by 2
- 2026WPBench: A Comprehensive Benchmark for Wind Power Forecastingcited by 2
- 2024CARE to Compare: A real-world dataset for anomaly detection in wind turbine datacited by 1
- 2024Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6cited by 1
- 2026WPBench: A Comprehensive Benchmark for Wind Power Forecasting21 Sep 2026
- 2024Turbine location-aware multi-decadal wind power predictions for Germany using CMIP627 Aug 2024
- 2024CARE to Compare: A real-world dataset for anomaly detection in wind turbine data16 Apr 2024
- 2023Prediction of wind turbines power with physics-informed neural networks and evidential uncertainty quantification27 Jul 2023
- 2022SDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting Challenge at KDD Cup 20228 Aug 2022