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Optimal Scheduling of Combined Heat and Power Generation Units Using the Thermal Inertia of the Connected District Heating Grid as Energy Storage

Author

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  • Lennart Merkert

    (ABB Corporate Research Center Germany, 68526 Ladenburg, Germany)

  • Ashvar Abdoul Haime

    (ABB Corporate Research Center Germany, 68526 Ladenburg, Germany)

  • Sören Hohmann

    (Institute for Control Systems, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany)

Abstract

A better integration across sectors is an essential element of 4th generation district heating and smart energy systems allowing to react to volatile renewable energy generation. This sector coupling enables to use more cost-efficient storage as storage prices differ for different forms of energy. Thermal energy for example can be stored in comparably cheap storage tanks. Besides such dedicated storage, the thermal inertia of a heating grid can be used as thermal storage as well. In this paper, a classic unit commitment optimization for scheduling of combined heat and power units not considering grid dynamics is extended to cover thermal dynamics of heating grids. First an outer approximation of the grid storage capabilities is developed. Second, a very efficient formulation for the storage dynamics of a heating grid is introduced and its capabilities are shown in a motivating case study. In this study additional savings of several thousand Euros per day are achieved using the thermal inertia of a heating grid as storage.

Suggested Citation

  • Lennart Merkert & Ashvar Abdoul Haime & Sören Hohmann, 2019. "Optimal Scheduling of Combined Heat and Power Generation Units Using the Thermal Inertia of the Connected District Heating Grid as Energy Storage," Energies, MDPI, vol. 12(2), pages 1-9, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:2:p:266-:d:198163
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    References listed on IDEAS

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    Cited by:

    1. Ksenija Stepanovic & Jichen Wu & Rob Everhardt & Mathijs de Weerdt, 2022. "Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning," Energies, MDPI, vol. 15(9), pages 1-25, April.
    2. 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).
    3. Rakesh Sinha & Birgitte Bak-Jensen & Jayakrishnan Radhakrishna Pillai, 2019. "Autonomous Controller for Flexible Operation of Heat Pumps in Low-Voltage Distribution Network," Energies, MDPI, vol. 12(8), pages 1-19, April.
    4. 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).
    5. Omid Sadeghian & Arash Moradzadeh & Behnam Mohammadi-Ivatloo & Mehdi Abapour & Fausto Pedro Garcia Marquez, 2020. "Generation Units Maintenance in Combined Heat and Power Integrated Systems Using the Mixed Integer Quadratic Programming Approach," Energies, MDPI, vol. 13(11), pages 1-25, June.
    6. Jiajia Li & Jinfu Liu & Peigang Yan & Xingshuo Li & Guowen Zhou & Daren Yu, 2021. "Operation Optimization of Integrated Energy System under a Renewable Energy Dominated Future Scene Considering Both Independence and Benefit: A Review," Energies, MDPI, vol. 14(4), pages 1-36, February.
    7. Merkert, Lennart & Listmann, Kim & Hohmann, Sören, 2019. "Optimization of thermo-hydraulic systems using multiparametric delay modeling," Energy, Elsevier, vol. 189(C).
    8. Hamdi Abdi, 2023. "A Survey of Combined Heat and Power-Based Unit Commitment Problem: Optimization Algorithms, Case Studies, Challenges, and Future Directions," Mathematics, MDPI, vol. 11(19), pages 1-36, October.
    9. Joong Yong Yi & Kyung Min Kim & Jongjun Lee & Mun Sei Oh, 2019. "Exergy Analysis for Utilizing Latent Energy of Thermal Energy Storage System in District Heating," Energies, MDPI, vol. 12(7), pages 1-13, April.

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