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Dataset Open Access

The RE-Europe data set

Jensen, Tue V.; de Sevin, Hugo; Greiner, Martin; Pinson, Pierre

This data set models the continental European electricity system, including demand and renewable energy inflows for the period 2012-2014.

The main features of the data set are:

  • High resolution (~50km, 1 hour) and large extent (Mainland Europe, 3 years)
  • Technical & economic characteristics of generators from real-world data and best available estimates
  • Synthetic wind and solar observations and forecasts from numerical weather prediction models, describing the full spatio-temporal structure of the wind

The transmission system comprises 1494 buses and 2156 lines, and is fitted based on [1].
The location, capacity and fuel type for 969 real-world generators are given based on the information in [2], and these are supplied with full cost specifications estimated based on fuel type [3].
For each bus, signals for load [4, 5], wind and solar production is given for each hour of the three years, with the wind and solar signals based on meteorological weather data from [6,7].
Further, at hour 00 and 12, forecasts for the solar and wind production are given for the following 91 hours, based on weather data from [6].
All spatially-distributed data is aggregated to the nodal domain by summation/averaging over the area closest to each node.

Wind and solar signals and forecast are given as capacity factors, i.e. production relative to rated power. To use the renewable signals, a capacity layout must be specified, which assigns an installed solar and wind capacity to each node.
We supply two sets of capacity layouts, both scaled so the mean yearly production of (solar, wind) is equal the mean yearly load across EU. 
The Uniform layout is scaled to make the capacity in each node proportional to the area aggregated by that node - i.e. capacity is distributed uniformly across EU.
The Proportional layout is scaled to make the capacity in each node proportional to the area aggregated by that node times the mean yearly capacity factor of the resource at that node - i.e. capacity is installed preferentially in nodes with high capacity factors.

The data is intended for use in, e.g:

  • Operational studies on markets
  • Investment studies (generation capacity and transmission)
  • Evaluation of future energy scenarios

Version History:

V1.1: License relaxed to CC-BY

V1.0: Initial Release

The authors are partly supported by the Danish Council for Strategic Research through the project ``5s --- Future Electricity Markets'', no. 12--132636/DSF.
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  • [1] Bialek, JW; Hutcheon, N: _Updated and validated power flow model of the main continental European transmission network_ (2013), available at www.powerworld.com/bialek

  • [2] Data obtained from http://GlobalEnergyObservatory.org/

  • [3] EIA. _Levelized Cost and Levelized Avoided Cost of New Generation Resources_ in the Annual Energy Outlook 2014. Technical Report April, US Energy Information administration, 2014.

  • [4] ENTSO-E. European Network of Transmission System Operators for Electricity.

  • [5] Gridded Population of the World, Version 3 (GPWv3): Population Density Grid, Future Estimates 2010, 2005. DOI: 10.7927/H4ST7MRB. Accessed 01 Nov 2014

  • [6] European Centre for Medium-Range Weather Forecasts (2011): _ECMWF's Operational Model Analysis, starting in 2011._ Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Dataset. http://dx.doi.org/10.5065/D6ZG6Q9F. Accessed 03 Mar 2015.

  • [7] Bollmeyer, C. et.al: _Towards a high-resolution regional reanalysis for the European CORDEX domain._ Quarterly Journal of the Royal Meteorological Society 2014, 40.

  • [8] Gorm B. Andresen, Anders A. Søndergaard, Martin Greiner, _Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis_, Energy, Volume 93, Part 1, 15 December 2015, Pages 1074-1088, ISSN 0360-5442, http://dx.doi.org/10.1016/j.energy.2015.09.071.

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