A collection and categorization of open‐source wind and wind power datasets

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.

Multi-modal transformer-based wind power prediction by utilizing heterogeneous sources

“…The wind power dataset used in this study is from the Supervisory Control Furthermore, Data Acquisition (SCADA) systems of the "La Haute Borne" wind farm [17], located in the Meuse department of northeastern France, consisting of four wind turbines (labelled as R80711, R80721, R80736, and R80790), with a rated power of 2050 kW. Variables such as active power, wind speed, ambient temperature are sampled every 10 min.…”

Evaluation of a Database of the Spanish Wind Energy Resources Derived from a Regional Reanalysis

“…A physical model (described in Section 3.1) was used to derive wind power estimates (in CF units) from RetroDB and ERA5 wind estimates. Obtaining observed wind power estimates for model validation purposes is a challenge [48]. Due to owner restrictions, observed values are hardly ever available at a windmill or even wind farm levels; only country aggregate values are usually available, which limits the scope of the models.…”

SDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting over a Large Turbine Array

“…Most datasets that underlie WPF research are not publicly accessible due to confidentiality agreements, as noted by 16 . Publicly available wind power datasets are typically aggregated over spatial regions, lacking turbine-level measurements and turbine-specific power output 17 . The Supervisory Control And Data Acquisition (SCADA) system is responsible for collecting turbine-level measurements, which reflect dynamic contextual factors for each turbine, such as temperature, weather, and turbine internal status.…”