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Grouped Charging of Decentralised Storage to Efficiently Control Collective Heating Systems: Limitations and Opportunities

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  • Stef Jacobs

    (EMIB, Faculty of Applied Engineering, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
    Faculty of Applied Engineering–Electronics ICT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium)

  • Margot De Pauw

    (Kenniscentrum Energie, Thomas More Kempen, Kleinhoefstraat 4, 2440 Geel, Belgium
    Current address: Buildwise, Kleine Kloosterstraat 23, 1932 Zaventem, Belgium.)

  • Senne Van Minnebruggen

    (EMIB, Faculty of Applied Engineering, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium)

  • Sara Ghane

    (IDLab, Faculty of Applied Engineering, University of Antwerp-imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium)

  • Thomas Huybrechts

    (IDLab, Faculty of Applied Engineering, University of Antwerp-imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium)

  • Peter Hellinckx

    (Faculty of Applied Engineering–Electronics ICT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium)

  • Ivan Verhaert

    (EMIB, Faculty of Applied Engineering, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium)

Abstract

Collective heating systems have multiple end-users with time-varying, often different temperature demands. There are several concepts catering to this, e.g., multi-pipe networks and 2-pipe networks with or without decentralised booster systems. In this study, we focus on 2-pipe networks with a changing supply temperature by smart use of decentralised storage. By grouping high-temperature demands, the average supply temperature can be lowered during large parts of the day, which is beneficial for system efficiency. The actual energy-saving potential, however, can be case-specific and is expected to depend on design choices and implemented control strategies. In this paper, these dependencies are assessed and identified by implementing two optimised rule-based control strategies, providing in such a way a bench-mark for other control strategies. The results show that grouping yields energy savings of up to 36% at similar peak demand as with conventional control strategies. The energy-saving potential is greatest for large storage volumes and small networks, but large networks with large storage and proper control choices can also achieve around 30% energy savings. Moreover, high-temperature time can easily be reduced to less than 40% of the day, which could make space cooling without decentralised booster heat pumps possible, but this requires further research.

Suggested Citation

  • Stef Jacobs & Margot De Pauw & Senne Van Minnebruggen & Sara Ghane & Thomas Huybrechts & Peter Hellinckx & Ivan Verhaert, 2023. "Grouped Charging of Decentralised Storage to Efficiently Control Collective Heating Systems: Limitations and Opportunities," Energies, MDPI, vol. 16(8), pages 1-28, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3435-:d:1123085
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    References listed on IDEAS

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