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Comparison of clustering algorithms for the selection of typical demand days for energy system synthesis

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  • Schütz, Thomas
  • Schraven, Markus Hans
  • Fuchs, Marcus
  • Remmen, Peter
  • Müller, Dirk

Abstract

The optimal design, sizing and operation of building energy systems is a complex problem due to the variety of available generation and storage devices as well as the high-resolution input data required for considering seasonal and intraday fluctuations in the thermal and electrical loads as well as renewable supply. A common measure to reduce the problem's size and complexity is to cluster the demands into representative periods. There exist many different algorithms for the clustering, but to the best of our knowledge, no comparison has been made that illustrates which algorithms are the most appropriate for such problems.

Suggested Citation

  • Schütz, Thomas & Schraven, Markus Hans & Fuchs, Marcus & Remmen, Peter & Müller, Dirk, 2018. "Comparison of clustering algorithms for the selection of typical demand days for energy system synthesis," Renewable Energy, Elsevier, vol. 129(PA), pages 570-582.
    • Handle: RePEc:eee:renene:v:129:y:2018:i:pa:p:570-582
    DOI: 10.1016/j.renene.2018.06.028
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    References listed on IDEAS

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