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Load profile data of 50 industrial plants in Germany for one year

Braeuer, Fritz


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    "description": "<p>This dataset holds the electric load profiles of 50 small and mid-size enterprises in Germany. The load profiles are in 15-minute time resolution for one year. The load is shown in kW as an average over 15 minutes.</p>\n\n<p>The dataset is divided into two:</p>\n\n<ul>\n\t<li>LoadProfile_20IPs_2016 shows load profiles of 20 industrial plants (IP) for the year 2016.</li>\n\t<li>LoadProfile_30IPs_2017 shows load profiles of 30 industrial plants (IP) for the year 2017.</li>\n</ul>\n\n<p>The IPs from the dataset for 2016 do not reappear in the dataset for 2017.</p>\n\n<p>&nbsp;</p>\n\n<p>The dataset LoadProfile_20IPs_2016 is evaluated in the following publication:</p>\n\n<ul>\n\t<li>Covic, N., Braeuer, F., McKenna, R., Pandzic, H., Optimizing Industrial Facilities&rsquo; Active Participation<br>\n\tin Electricity Markets under Uncertainty, 2020.</li>\n</ul>\n\n<p>Both datasets together are evaluated in multiple publications:</p>\n\n<ul>\n\t<li>Braeuer, F., Finck, R., McKenna, R., Comparing empirical and model-based approaches for calculating dynamic grid emission factors: An application to CO2-minimizing storage dispatch in Germany, Journal of Cleaner Production, Volume 266, 2020, 121588, ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2020.121588.</li>\n\t<li>Braeuer, F., Rominger, J., McKenna, R.,Fichtner, W., Battery storage systems: An economic model-based analysis of parallel revenue streams and general implications for industry, Applied Energy, Volume 239, 2019, Pages 1424-1440, ISSN 0306-2619, https://doi.org/10.1016/j.apenergy.2019.01.050.</li>\n</ul>\n\n<p>Enjoy.</p>", 
    "language": "eng", 
    "title": "Load profile data of 50 industrial plants in Germany for one year", 
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    "keywords": [
      "load profile", 
      "industry", 
      "SME", 
      "electricity demand"
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    "publication_date": "2020-06-17", 
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