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Implementing flexibility into energy planning models: Soft-linking of a high-level energy planning model and a short-term operational model

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  • Dominković, Dominik Franjo
  • Junker, Rune Grønborg
  • Lindberg, Karen Byskov
  • Madsen, Henrik

Abstract

The operation of electric and heat grids alike is complicated due to the dynamic demand, with the increasing penetration of renewable energy sources adding to the problem. In order to improve the integration of variable renewable energy sources, the flexibility of the system needs to be improved. This paper proposed a novel characterization of the short-term energy flexibility, which was further utilized for the district heating capacity extension. The soft-linking of the models includes feedback, but the added computational complexity is kept at a minimum. Compared to the other literature in the field, due to the accurate characterization of the dynamics of the energy flexibility, flexibility is utilized much more frequently. The method was demonstrated for the case of the district heating of Zagreb. Results showed that both capital and operational savings can be achieved by adopting the proposed method. In the best performing scenario, which included the capacity extension planning, the savings of the district heating system were 5.4%. The extensive power exchange in the best performing scenario meant that the flexibility was used to help balancing the power grid as well.

Suggested Citation

  • Dominković, Dominik Franjo & Junker, Rune Grønborg & Lindberg, Karen Byskov & Madsen, Henrik, 2020. "Implementing flexibility into energy planning models: Soft-linking of a high-level energy planning model and a short-term operational model," Applied Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919319798
    DOI: 10.1016/j.apenergy.2019.114292
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    8. Manfren, Massimiliano & Nastasi, Benedetto & Tronchin, Lamberto & Groppi, Daniele & Garcia, Davide Astiaso, 2021. "Techno-economic analysis and energy modelling as a key enablers for smart energy services and technologies in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    9. Pfeifer, Antun & Krajačić, Goran & Haas, Reinhard & Duić, Neven, 2020. "Consequences of different strategic decisions of market coupled zones on the development of energy systems based on coal and hydropower," Energy, Elsevier, vol. 210(C).
    10. Natasa Nord & Yiyu Ding & Ola Skrautvol & Stian Fossmo Eliassen, 2021. "Energy Pathways for Future Norwegian Residential Building Areas," Energies, MDPI, vol. 14(4), pages 1-21, February.
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    12. Amaral Lopes, Rui & Grønborg Junker, Rune & Martins, João & Murta-Pina, João & Reynders, Glenn & Madsen, Henrik, 2020. "Characterisation and use of energy flexibility in water pumping and storage systems," Applied Energy, Elsevier, vol. 277(C).
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    14. Yin, Linfei & Qiu, Yao, 2022. "Long-term price guidance mechanism of flexible energy service providers based on stochastic differential methods," Energy, Elsevier, vol. 238(PB).
    15. Schledorn, Amos & Junker, Rune Grønborg & Guericke, Daniela & Madsen, Henrik & Dominković, Dominik Franjo, 2022. "Frigg: Soft-linking energy system and demand response models," Applied Energy, Elsevier, vol. 317(C).
    16. Bergsteinsson, Hjörleifur G. & Møller, Jan Kloppenborg & Nystrup, Peter & Pálsson, Ólafur Pétur & Guericke, Daniela & Madsen, Henrik, 2021. "Heat load forecasting using adaptive temporal hierarchies," Applied Energy, Elsevier, vol. 292(C).
    17. Junker, Rune Grønborg & Kallesøe, Carsten Skovmose & Real, Jaume Palmer & Howard, Bianca & Lopes, Rui Amaral & Madsen, Henrik, 2020. "Stochastic nonlinear modelling and application of price-based energy flexibility," Applied Energy, Elsevier, vol. 275(C).
    18. Schledorn, Amos & Charousset-Brignol, Sandrine & Junker, Rune Grønborg & Guericke, Daniela & Madsen, Henrik & Dominković, Dominik Franjo, 2024. "Frigg 2.0: Integrating price-based demand response into large-scale energy system analysis," Applied Energy, Elsevier, vol. 364(C).

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