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Integral techno-economic design & operational optimization for district heating networks with a Mixed Integer Linear Programming strategy

Author

Listed:
  • Rojer, Jim
  • Janssen, Femke
  • van der Klauw, Thijs
  • van Rooyen, Jacobus

Abstract

The Netherlands, with over 90% of homes heated by natural gas is currently in the early phases of the heat transition to find alternative solutions towards 2050. According to ambitions of the Dutch government up to 50% of future implemented heating systems in the built environment will use District Heat Networks. The investment-heavy nature for District Heating System (DHS) makes it challenging to establish viable business-cases as supply-side parties require security of demand. However, resident participation is lacking as there is no integral estimate for the cost of heat over the lifetime in the early planning phase. This paper proposes a network integral techno-economic optimization with minimal a-priori assumptions. An integral network cost optimization enables to achieve a considerably more reliable cost of heat in the early planning phase. Both the investments and operational strategy are optimized with a Mixed Integer Linear Programming approach that captures the physics as well as the financial choices. Linearization of the physics are chosen to have a conservative impact on the costs estimates. The end scenario network is designed where the placement and size of sources, storage components and pipes are optimized together with the operational strategy, e.g. thermal allocation time-series, for all assets. The workflow was applied to a greenfield network for the Dutch municipality of Rijswijk. It was shown that a 18% reduction in Total Cost of Ownership in the primary grid could be achieved by introducing decentralized sources, decentralized storages and seasonal storage.

Suggested Citation

  • Rojer, Jim & Janssen, Femke & van der Klauw, Thijs & van Rooyen, Jacobus, 2024. "Integral techno-economic design & operational optimization for district heating networks with a Mixed Integer Linear Programming strategy," Energy, Elsevier, vol. 308(C).
  • Handle: RePEc:eee:energy:v:308:y:2024:i:c:s0360544224024848
    DOI: 10.1016/j.energy.2024.132710
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