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The RE-Europe data set

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


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    "description": "<p>This data set models the continental European electricity system, including demand and renewable energy inflows for the period 2012-2014.</p>\n\n<p>The main features of the data set are:</p>\n\n<ul>\n\t<li>High resolution (~50km, 1 hour) and large extent (Mainland Europe, 3 years)</li>\n\t<li>Technical &amp; economic characteristics of generators from real-world data and best available estimates</li>\n\t<li>Synthetic wind and solar observations and forecasts from numerical weather prediction models, describing the full spatio-temporal structure of potential wind and solar production</li>\n</ul>\n\n<p>The transmission system comprises 1494 buses and 2156 lines, and is fitted based on [1].<br>\nThe location, capacity and fuel type&nbsp;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].<br>\nFor 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&nbsp;[6,7].<br>\nFurther, 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].<br>\nAll spatially-distributed data is aggregated to the nodal domain by summation/averaging over the area closest to each node.</p>\n\n<p>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.<br>\nWe supply two sets of capacity layouts, both scaled so the mean yearly production of (solar, wind) is equal the mean yearly load across EU.&nbsp;<br>\nThe 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.<br>\nThe Proportional layout is scaled to make the capacity in each node proportional to the area aggregated by that node&nbsp;times the mean yearly capacity factor of the resource at that node - i.e. capacity is installed preferentially in nodes with high capacity factors.<br>\n<br>\nThe data is intended for use in, e.g:</p>\n\n<ul>\n\t<li>Operational studies on markets</li>\n\t<li>Investment studies (generation capacity and&nbsp;transmission)</li>\n\t<li>Evaluation of future energy scenarios</li>\n</ul>\n\n<p>The source code used to generate this data is available at [9].</p>\n\n<p>Version History:</p>\n\n<p>V1.2:</p>\n\n<ul>\n\t<li>Line information extended with data on the number of parallel lines in each connection.</li>\n\t<li>Fixed generator capacity typos.</li>\n</ul>\n\n<p>V1.1: License relaxed to CC-BY</p>\n\n<p>V1.0: Initial Release</p>", 
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    "title": "The RE-Europe data set", 
    "notes": "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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    "references": [
      "[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. S\u00f8ndergaard, 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.", 
      "[9] RE-Europe github repository: www.github.com/DTU-ELMA/European_Dataset"
    ], 
    "keywords": [
      "Energy system models", 
      "Electricity markets", 
      "Renewable energy"
    ], 
    "publication_date": "2017-09-29", 
    "creators": [
      {
        "affiliation": "Technical University of Denmark, Denmark", 
        "name": "Jensen, Tue V."
      }, 
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        "affiliation": "Technical University of Denmark, Denmark", 
        "name": "de Sevin, Hugo"
      }, 
      {
        "affiliation": "Aarhus University, Denmark", 
        "name": "Greiner, Martin"
      }, 
      {
        "affiliation": "Technical University of Denmark, Denmark", 
        "name": "Pinson, Pierre"
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