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Design optimization of a district heating and cooling system with a borehole seasonal thermal energy storage

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  • Fiorentini, Massimo
  • Heer, Philipp
  • Baldini, Luca

Abstract

The optimal design of borehole thermal energy storage systems can ensure their techno-economical goals are met. Current design optimization methods either employ detailed modelling unsuitable for numerical optimization or use simplified models that do not consider operational conditions. This paper proposes an optimization-oriented model and a non-convex optimization formulation that, differently from other studies in the literature, can consider the influence of the seasonal storage size and temperature on its capacity, losses, heat transfer rate, and efficiency of connected heat pumps or chillers. This methodology was applied to a case study, considering two scenarios: storing only the rejected heat from cooling and integrating solar thermal generation. Results show that, with varying boundary conditions such as the electricity CO2 intensity profile, cooling demand, and price of carbon emissions, not only the optimal seasonal storage size changes but also its optimal operating conditions. The potential reduction of CO2 emissions was found, under standard boundary conditions, to be limited (up to 6.7%), but an increase in cooling demand and an enhancement of the CO2 intensity seasonal variation led to a reduction of 27.1%. Integration of solar generation further improved it to 43.7%, with a comparably small increase in annual cost, up to 6.1%.

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  • Fiorentini, Massimo & Heer, Philipp & Baldini, Luca, 2023. "Design optimization of a district heating and cooling system with a borehole seasonal thermal energy storage," Energy, Elsevier, vol. 262(PB).
  • Handle: RePEc:eee:energy:v:262:y:2023:i:pb:s0360544222023465
    DOI: 10.1016/j.energy.2022.125464
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    References listed on IDEAS

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    1. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    2. Buffa, Simone & Cozzini, Marco & D’Antoni, Matteo & Baratieri, Marco & Fedrizzi, Roberto, 2019. "5th generation district heating and cooling systems: A review of existing cases in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 504-522.
    3. Petkov, Ivalin & Gabrielli, Paolo, 2020. "Power-to-hydrogen as seasonal energy storage: an uncertainty analysis for optimal design of low-carbon multi-energy systems," Applied Energy, Elsevier, vol. 274(C).
    4. Leśko, Michał & Bujalski, Wojciech & Futyma, Kamil, 2018. "Operational optimization in district heating systems with the use of thermal energy storage," Energy, Elsevier, vol. 165(PA), pages 902-915.
    5. Omu, Akomeno & Hsieh, Shanshan & Orehounig, Kristina, 2016. "Mixed integer linear programming for the design of solar thermal energy systems with short-term storage," Applied Energy, Elsevier, vol. 180(C), pages 313-326.
    6. Antoniadis, Christodoulos N. & Martinopoulos, Georgios, 2019. "Optimization of a building integrated solar thermal system with seasonal storage using TRNSYS," Renewable Energy, Elsevier, vol. 137(C), pages 56-66.
    7. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    8. Shah, Sheikh Khaleduzzaman & Aye, Lu & Rismanchi, Behzad, 2020. "Multi-objective optimisation of a seasonal solar thermal energy storage system for space heating in cold climate," Applied Energy, Elsevier, vol. 268(C).
    9. Tulus, Victor & Boer, Dieter & Cabeza, Luisa F. & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2016. "Enhanced thermal energy supply via central solar heating plants with seasonal storage: A multi-objective optimization approach," Applied Energy, Elsevier, vol. 181(C), pages 549-561.
    10. Dahash, Abdulrahman & Ochs, Fabian & Janetti, Michele Bianchi & Streicher, Wolfgang, 2019. "Advances in seasonal thermal energy storage for solar district heating applications: A critical review on large-scale hot-water tank and pit thermal energy storage systems," Applied Energy, Elsevier, vol. 239(C), pages 296-315.
    11. Evins, Ralph, 2013. "A review of computational optimisation methods applied to sustainable building design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 230-245.
    12. Steen, David & Stadler, Michael & Cardoso, Gonçalo & Groissböck, Markus & DeForest, Nicholas & Marnay, Chris, 2015. "Modeling of thermal storage systems in MILP distributed energy resource models," Applied Energy, Elsevier, vol. 137(C), pages 782-792.
    13. Elhashmi, Rodwan & Hallinan, Kevin P. & Chiasson, Andrew D., 2020. "Low-energy opportunity for multi-family residences: A review and simulation-based study of a solar borehole thermal energy storage system," Energy, Elsevier, vol. 204(C).
    14. Wirtz, Marco & Kivilip, Lukas & Remmen, Peter & Müller, Dirk, 2020. "5th Generation District Heating: A novel design approach based on mathematical optimization," Applied Energy, Elsevier, vol. 260(C).
    15. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2014. "A detailed MILP optimization model for combined cooling, heat and power system operation planning," Energy, Elsevier, vol. 74(C), pages 12-26.
    16. Xu, Qingqing & Dubljevic, Stevan, 2017. "Modelling and control of solar thermal system with borehole seasonal storage," Renewable Energy, Elsevier, vol. 100(C), pages 114-128.
    17. Prasanna, Ashreeta & Dorer, Viktor & Vetterli, Nadège, 2017. "Optimisation of a district energy system with a low temperature network," Energy, Elsevier, vol. 137(C), pages 632-648.
    18. Wirtz, Marco & Neumaier, Lisa & Remmen, Peter & Müller, Dirk, 2021. "Temperature control in 5th generation district heating and cooling networks: An MILP-based operation optimization," Applied Energy, Elsevier, vol. 288(C).
    19. Miglani, Somil & Orehounig, Kristina & Carmeliet, Jan, 2018. "Integrating a thermal model of ground source heat pumps and solar regeneration within building energy system optimization," Applied Energy, Elsevier, vol. 218(C), pages 78-94.
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    2. Yang, Tianrun & Liu, Wen & Sun, Qie & Hu, Weihao & Kramer, Gert Jan, 2023. "Techno-economic-environmental analysis of seasonal thermal energy storage with solar heating for residential heating in China," Energy, Elsevier, vol. 283(C).
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    4. Salenbien, R. & Wack, Y. & Baelmans, M. & Blommaert, M., 2023. "Geographically informed automated non-linear topology optimization of district heating networks," Energy, Elsevier, vol. 283(C).

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