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Multi-criteria analysis of storages integration and operation solutions into the district heating network of Aarhus – A simulation case study

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  • Marguerite, C.
  • Andresen, G.B.
  • Dahl, M.

Abstract

This paper assesses possibilities of integration of centralised and decentralised storages in the district heating network (DHN) of Aarhus, Denmark and their operation strategy, with the objective to smooth the heat demand during peak hours (Peak-based strategy) or to reduce the operational costs of the DHN (Price-based strategy). The analysis is carried out using a dynamic plant scheduling optimisation algorithm implemented in MATLAB to simulate and optimise the network behaviour. The results show that both strategies present similar costs reduction when applied to centralised storages. With the Peak-based strategy applied to the decentralised storages, the system runs with the cheapest costs. Additionally decentralised storages lead to different network performances depending on the scenario, from −2% to +1% of CO2 emissions and primary energy consumption. In this analysis where the performances indicators are very close, the investment costs and payback time are key criteria in order to choose the most convenient storage solution.

Suggested Citation

  • Marguerite, C. & Andresen, G.B. & Dahl, M., 2018. "Multi-criteria analysis of storages integration and operation solutions into the district heating network of Aarhus – A simulation case study," Energy, Elsevier, vol. 158(C), pages 81-88.
    • Handle: RePEc:eee:energy:v:158:y:2018:i:c:p:81-88
    DOI: 10.1016/j.energy.2018.06.013
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    Cited by:

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    3. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    4. Li, Haoran & Zhang, Chenghui & Sun, Bo, 2021. "Optimal design for component capacity of integrated energy system based on the active dispatch mode of multiple energy storages," Energy, Elsevier, vol. 227(C).
    5. Nielsen, Tore Bach & Lund, Henrik & Østergaard, Poul Alberg & Duic, Neven & Mathiesen, Brian Vad, 2021. "Perspectives on energy efficiency and smart energy systems from the 5th SESAAU2019 conference," Energy, Elsevier, vol. 216(C).
    6. Wei Wei & Yusong Guo & Kai Hou & Kai Yuan & Yi Song & Hongjie Jia & Chongbo Sun, 2021. "Distributed Thermal Energy Storage Configuration of an Urban Electric and Heat Integrated Energy System Considering Medium Temperature Characteristics," Energies, MDPI, vol. 14(10), pages 1-34, May.
    7. Janis Edmunds Daugavietis & Raimonda Soloha & Elina Dace & Jelena Ziemele, 2022. "A Comparison of Multi-Criteria Decision Analysis Methods for Sustainability Assessment of District Heating Systems," Energies, MDPI, vol. 15(7), pages 1-23, March.
    8. Lund, Henrik & Duic, Neven & Østergaard, Poul Alberg & Mathiesen, Brian Vad, 2018. "Future district heating systems and technologies: On the role of smart energy systems and 4th generation district heating," Energy, Elsevier, vol. 165(PA), pages 614-619.
    9. Jebamalai, Joseph Maria & Marlein, Kurt & Laverge, Jelle, 2020. "Influence of centralized and distributed thermal energy storage on district heating network design," Energy, Elsevier, vol. 202(C).
    10. Manservigi, Lucrezia & Bahlawan, Hilal & Losi, Enzo & Morini, Mirko & Spina, Pier Ruggero & Venturini, Mauro, 2022. "A diagnostic approach for fault detection and identification in district heating networks," Energy, Elsevier, vol. 251(C).

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