The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Harmonised global datasets of wind and solar farm locations and power
Open accessAbstract
Energy systems need decarbonisation in order to limit global warming to within safe limits. While global land planners are promising more of the planet’s limited space to wind and solar photovoltaic, there is little information on where current infrastructure is located. The majority of recent studies use land suitability for wind and solar, coupled with technical and socioeconomic constraints, as a proxy for actual location data. Here, we address this shortcoming. Using readily accessible OpenStreetMap data we present, to our knowledge, the first global, open-access, harmonised spatial datasets of wind and solar installations. We also include user friendly code to enable users to easily create newer versions of the dataset. Finally, we include first order estimates of power capacities of installations. We anticipate these data will be of widespread interest within global studies of the future potential and trade-offs associated with the global decarbonisation of energy systems.
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Cited by
Temporally compounding energy droughts in European electricity systems with hydropower
van der Most, L., van der Wiel, K., Benders, R. M. J., Gerbens-Leenes, P. W., & Bintanja, R. (2024) · Nature Energy · doi:10.1038/s41560-024-01640-5 · Cited by 51
Metadata
- Authors
- Dunnett, S., Sorichetta, A., Taylor, G., & Eigenbrod, F.
- Venue
- Scientific Data
- Published
- 2020-04-29
- Volume
- 7
- Issue
- 1
- Pages
- 130-130
- ISSN
- 2052-4463 (ISSN-L)
- OpenAlex
- W3023149825
- Cited by
- 269
- References
- 28
- Type
- data paper
- Language
- en
- Open access
- gold
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- Dunnett, S., Sorichetta, A., Taylor, G., & Eigenbrod, F. (2020). Harmonised global datasets of wind and solar farm locations and power. Scientific Data. https://doi.org/10.1038/s41597-020-0469-8
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
