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Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage

Author

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  • Bram van der Heijde

    (EnergyVille, Thor Park 8310, 3600 Genk, Belgium
    Department of Mechanical Engineering, KU Leuven, Celestijnenlaan 300, Box 2421, 3001 Leuven, Belgium
    VITO NV, Boeretang 200, 5800 Mol, Belgium)

  • Annelies Vandermeulen

    (EnergyVille, Thor Park 8310, 3600 Genk, Belgium
    Department of Mechanical Engineering, KU Leuven, Celestijnenlaan 300, Box 2421, 3001 Leuven, Belgium
    VITO NV, Boeretang 200, 5800 Mol, Belgium)

  • Robbe Salenbien

    (EnergyVille, Thor Park 8310, 3600 Genk, Belgium
    VITO NV, Boeretang 200, 5800 Mol, Belgium)

  • Lieve Helsen

    (EnergyVille, Thor Park 8310, 3600 Genk, Belgium
    Department of Mechanical Engineering, KU Leuven, Celestijnenlaan 300, Box 2421, 3001 Leuven, Belgium)

Abstract

In the quest to increase the share of renewable and residual energy sources in our energy system, and to reduce its greenhouse gas emissions, district heating networks and seasonal thermal energy storage have the potential to play a key role. Different studies prove the techno-economic potential of these technologies but, due to the added complexity, it is challenging to design and control such systems. This paper describes an integrated optimal design and control algorithm, which is applied to the design of a district heating network with solar thermal collectors, seasonal thermal energy storage and excess heat injection. The focus is mostly on the choice of the size and location of these technologies and less on the network layout optimisation. The algorithm uses a two-layer program, namely with a design optimisation layer implemented as a genetic algorithm and an optimal control evaluation layer implemented using the Python optimal control problem toolbox called modesto. This optimisation strategy is applied to the fictional district energy system case of the city of Genk in Belgium. We show that this algorithm can find optimal designs with respect to multiple objective functions and that even in the cheaper, less renewable solutions, seasonal thermal energy storage systems are installed in large quantities.

Suggested Citation

  • Bram van der Heijde & Annelies Vandermeulen & Robbe Salenbien & Lieve Helsen, 2019. "Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage," Energies, MDPI, vol. 12(14), pages 1-34, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2766-:d:249664
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    References listed on IDEAS

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    1. Dahash, Abdulrahman & Ochs, Fabian & Tosatto, Alice & Streicher, Wolfgang, 2020. "Toward efficient numerical modeling and analysis of large-scale thermal energy storage for renewable district heating," Applied Energy, Elsevier, vol. 279(C).
    2. Anna Grzegórska & Piotr Rybarczyk & Valdas Lukoševičius & Joanna Sobczak & Andrzej Rogala, 2021. "Smart Asset Management for District Heating Systems in the Baltic Sea Region," Energies, MDPI, vol. 14(2), pages 1-25, January.
    3. Zhiyuan Liu & Hang Yu & Rui Liu & Meng Wang & Chaoen Li, 2020. "Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations," Energies, MDPI, vol. 13(2), pages 1-22, January.
    4. Thibaut Résimont & Quentin Louveaux & Pierre Dewallef, 2021. "Optimization Tool for the Strategic Outline and Sizing of District Heating Networks Using a Geographic Information System," Energies, MDPI, vol. 14(17), pages 1-24, September.
    5. Dorotić, Hrvoje & Pukšec, Tomislav & Schneider, Daniel Rolph & Duić, Neven, 2021. "Evaluation of district heating with regard to individual systems – Importance of carbon and cost allocation in cogeneration units," Energy, Elsevier, vol. 221(C).
    6. Gjorgievski, Vladimir Z. & Cundeva, Snezana & Georghiou, George E., 2021. "Social arrangements, technical designs and impacts of energy communities: A review," Renewable Energy, Elsevier, vol. 169(C), pages 1138-1156.
    7. Saloux, Etienne & Candanedo, José A., 2021. "Model-based predictive control to minimize primary energy use in a solar district heating system with seasonal thermal energy storage," Applied Energy, Elsevier, vol. 291(C).
    8. Vandermeulen, Annelies & Van Oevelen, Tijs & van der Heijde, Bram & Helsen, Lieve, 2020. "A simulation-based evaluation of substation models for network flexibility characterisation in district heating networks," Energy, Elsevier, vol. 201(C).
    9. Annelies Vandermeulen & Ina De Jaeger & Tijs Van Oevelen & Dirk Saelens & Lieve Helsen, 2020. "Analysis of Building Parameter Uncertainty in District Heating for Optimal Control of Network Flexibility," Energies, MDPI, vol. 13(23), pages 1-25, November.
    10. Jann Michael Weinand, 2020. "Reviewing Municipal Energy System Planning in a Bibliometric Analysis: Evolution of the Research Field between 1991 and 2019," Energies, MDPI, vol. 13(6), pages 1-18, March.
    11. Edmund Widl & Benedikt Leitner & Daniele Basciotti & Sawsan Henein & Tarik Ferhatbegovic & René Hofmann, 2020. "Combined Optimal Design and Control of Hybrid Thermal-Electrical Distribution Grids Using Co-Simulation," Energies, MDPI, vol. 13(8), pages 1-21, April.
    12. Daniel Akinyele & Abraham Amole & Elijah Olabode & Ayobami Olusesi & Titus Ajewole, 2021. "Simulation and Analysis Approaches to Microgrid Systems Design: Emerging Trends and Sustainability Framework Application," Sustainability, MDPI, vol. 13(20), pages 1-26, October.
    13. Minuto, Francesco Demetrio & Lanzini, Andrea, 2022. "Energy-sharing mechanisms for energy community members under different asset ownership schemes and user demand profiles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    14. Arnaudo, Monica & Dalgren, Johan & Topel, Monika & Laumert, Björn, 2021. "Waste heat recovery in low temperature networks versus domestic heat pumps - A techno-economic and environmental analysis," Energy, Elsevier, vol. 219(C).
    15. Friebe, Maximilian & Karasu, Arda & Kriegel, Martin, 2023. "Methodology to compare and optimize district heating and decentralized heat supply for energy transformation on a municipality level," Energy, Elsevier, vol. 282(C).

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