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

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

Renewable Energy, 2018, vol. 129, issue PA, 570-582

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.

Keywords: Building energy system; Clustering; Mixed integer linear programming; Renewable energies; Typical demand days (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (39)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:129:y:2018:i:pa:p:570-582

DOI: 10.1016/j.renene.2018.06.028

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