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Journal article

ENSPRESO - an open, EU-28 wide, transparent and coherent database of wind, solar and biomass energy potentials

From

European Commission Joint Research Centre Institute1

German Biomass Resarch Centre gGmbH2

Helmholtz Centre for Environmental Research3

Department of Mechanical Engineering, Technical University of Denmark4

Center for Nuclear Technologies, Technical University of Denmark5

German Aerospace Center6

Energy Research Centre of the Netherlands7

Paul Scherrer Institute8

Resource Assessment Modelling, Department of Wind Energy, Technical University of Denmark9

Department of Wind Energy, Technical University of Denmark10

Wageningen University & Research11

...and 1 more

Data on the potential generation of energy from wind, solar and biomass is crucial for analysing their development, as it sets the limits on how much additional capacity it is feasible to install. This paper presents the methodologies used for the development of ENSPRESO, ENergy System Potentials for Renewable Energy SOurces, an EU-28 wide, open dataset for energy models on renewable energy potentials, at national and regional levels for the 2010–2050 period.

In ENSPRESO, coherent GIS-based land-restriction scenarios are developed. For wind, resource evaluation also considers setback distances, as well as high resolution geo-spatial wind speed data. For solar, potentials are derived from irradiation data and available area for solar applications. Both wind and solar have separately a potential electricity production which is equivalent to three times the EU's 2016 electricity demand, with wind onshore and solar requiring 16% and 1.4% of total land, respectively.

For biomass, agriculture, forestry and waste sectors are considered. Their respective sustainable potentials are equivalent to a minimum 10%, 1.5% and 1% of the total EU primary energy use. ENSPRESO can enrich the results of any energy model (e.g. JRC-EU-TIMES) by improving its analyses of the competition and complementarity of energy technologies.

Language: English
Publisher: Elsevier
Year: 2019
Pages: 100379
ISSN: 22114688 and 2211467x
Types: Journal article
DOI: 10.1016/j.esr.2019.100379
ORCIDs: 0000-0002-3148-7339 , 0000-0001-6439-5775 and Badger, Jake

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