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Setup and testing of smart controllers for small-scale district heating networks: An integrated framework

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  • De Lorenzi, Andrea
  • Gambarotta, Agostino
  • Morini, Mirko
  • Rossi, Michele
  • Saletti, Costanza

Abstract

Nowadays, the growing availability of renewable energy resources is an opportunity to reduce carbon emissions but also a challenge, as advanced control technologies are required. The new generation of smart district heating and cooling networks, for instance, pledges efficient energy distribution, flexibility and low-carbon energy integration. However, in the literature it is hard to find comprehensive frameworks for the integrated setup and testing of smart control strategies. This paper defines and demonstrates a framework that involves all steps of the controller development for small-scale district heating networks: from conceptualization to prototype testing. The innovative controller prototype, which relies on Model Predictive Control and aims to minimize operating costs and/or energy, is demonstrated in three original case studies, one in a simulation environment and two in real systems of different complexity in operational conditions. Compared to the control approaches previously adopted, based on predefined rules and operator experience, the smart solution achieves 6% reduction in cost and up to 34% reduction in energy consumption while meeting user requirements. The fast replicability of the proposed integrated methodology can foster the transition toward the next generation of smart heating networks.

Suggested Citation

  • De Lorenzi, Andrea & Gambarotta, Agostino & Morini, Mirko & Rossi, Michele & Saletti, Costanza, 2020. "Setup and testing of smart controllers for small-scale district heating networks: An integrated framework," Energy, Elsevier, vol. 205(C).
  • Handle: RePEc:eee:energy:v:205:y:2020:i:c:s0360544220311610
    DOI: 10.1016/j.energy.2020.118054
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    Cited by:

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    2. De Lorenzi, Andrea & Gambarotta, Agostino & Marzi, Emanuela & Morini, Mirko & Saletti, Costanza, 2022. "Predictive control of a combined heat and power plant for grid flexibility under demand uncertainty," Applied Energy, Elsevier, vol. 314(C).
    3. Saletti, Costanza & Morini, Mirko & Gambarotta, Agostino, 2022. "Smart management of integrated energy systems through co-optimization with long and short horizons," Energy, Elsevier, vol. 250(C).
    4. Coccia, Gianluca & Mugnini, Alice & Polonara, Fabio & Arteconi, Alessia, 2021. "Artificial-neural-network-based model predictive control to exploit energy flexibility in multi-energy systems comprising district cooling," Energy, Elsevier, vol. 222(C).
    5. 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).
    6. 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).
    7. 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).
    8. Tobias Kull & Bernd Zeilmann & Gerhard Fischerauer, 2021. "Field-Ready Implementation of Linear Economic Model Predictive Control for Microgrid Dispatch in Small and Medium Enterprises," Energies, MDPI, vol. 14(13), pages 1-23, June.
    9. Fester, Jakob & Østergaard, Peter Friis & Bentsen, Fredrik & Nielsen, Brian Kongsgaard, 2023. "A data-driven method for heat loss estimation from district heating service pipes using heat meter- and GIS data," Energy, Elsevier, vol. 277(C).
    10. Saletti, Costanza & Zimmerman, Nathan & Morini, Mirko & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2021. "Enabling smart control by optimally managing the State of Charge of district heating networks," Applied Energy, Elsevier, vol. 283(C).

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