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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 the wind</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\u00a0for 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\u00a0[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.\u00a0<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\u00a0times 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\u00a0transmission)</li>\n\t<li>Evaluation of future energy scenarios</li>\n</ul>\n\n<p>Version History:</p>\n\n<p>V1.1: License relaxed to CC-BY</p>\n\n<p>V1.0: Initial Release</p>", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Technical University of Denmark, Denmark", 
      "@type": "Person", 
      "name": "Jensen, Tue V."
    }, 
    {
      "affiliation": "Technical University of Denmark, Denmark", 
      "@type": "Person", 
      "name": "de Sevin, Hugo"
    }, 
    {
      "affiliation": "Aarhus University, Denmark", 
      "@type": "Person", 
      "name": "Greiner, Martin"
    }, 
    {
      "affiliation": "Technical University of Denmark, Denmark", 
      "@type": "Person", 
      "name": "Pinson, Pierre"
    }
  ], 
  "url": "https://zenodo.org/record/803266", 
  "datePublished": "2017-06-06", 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/04c5a25e-381d-43e8-8f63-545b0f52444b/RE-Europe_dataset_package_v1-1.zip", 
      "encodingFormat": "zip", 
      "@type": "DataDownload"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.803266", 
  "@id": "https://doi.org/10.5281/zenodo.803266", 
  "@type": "Dataset", 
  "name": "The RE-Europe data set"
}
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