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A simple dynamic optimization-based approach for sizing thermal energy storage using process data

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  • Nakama, Caroline S.M.
  • Knudsen, Brage R.
  • Tysland, Agnes C.
  • Jäschke, Johannes

Abstract

Thermal energy storage (TES) can increase waste heat utilization in district heating (DH) by storing excess energy to be used later to compensate for energy deficit. When sizing a TES tank for DH, incorporating operational conditions can prevent suboptimal volumes and improve the utility enabled by the TES. However, the different time scales of the payback period for the tank and DH operation poses a challenge for optimizing the tank volume. We propose a method to optimally design a TES tank considering operational conditions of a DH plant using time varying waste heat. We formulate a multi-objective dynamic optimization model based on heat data for a long period, which is solved with a two-step approach. First, the data is screened by solving the model for short-term periods to detect intervals that allow for peak heating savings. Then, the model is re-solved using all selected intervals to determine an optimal tank volume. We conduct a trade-off analysis of the conflicting objectives, energy-saving and costs. The proposed method is demonstrated on a case study with historical data. Our method can explore the full feasible space of TES tank volumes and efficiently provide a trade-off curve without the need of exhaustive search.

Suggested Citation

  • Nakama, Caroline S.M. & Knudsen, Brage R. & Tysland, Agnes C. & Jäschke, Johannes, 2023. "A simple dynamic optimization-based approach for sizing thermal energy storage using process data," Energy, Elsevier, vol. 268(C).
  • Handle: RePEc:eee:energy:v:268:y:2023:i:c:s0360544223000658
    DOI: 10.1016/j.energy.2023.126671
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    References listed on IDEAS

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    1. Badami, Marco & Fonti, Antonio & Carpignano, Andrea & Grosso, Daniele, 2018. "Design of district heating networks through an integrated thermo-fluid dynamics and reliability modelling approach," Energy, Elsevier, vol. 144(C), pages 826-838.
    2. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimising urban energy systems: Simultaneous system sizing, operation and district heating network layout," Energy, Elsevier, vol. 116(P1), pages 619-636.
    3. Martínez-Lera, S. & Ballester, J. & Martínez-Lera, J., 2013. "Analysis and sizing of thermal energy storage in combined heating, cooling and power plants for buildings," Applied Energy, Elsevier, vol. 106(C), pages 127-142.
    4. Li, Zhi & Lu, Yiji & Huang, Rui & Chang, Jinwei & Yu, Xiaonan & Jiang, Ruicheng & Yu, Xiaoli & Roskilly, Anthony Paul, 2021. "Applications and technological challenges for heat recovery, storage and utilisation with latent thermal energy storage," Applied Energy, Elsevier, vol. 283(C).
    5. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    6. Knudsen, Brage Rugstad & Rohde, Daniel & Kauko, Hanne, 2021. "Thermal energy storage sizing for industrial waste-heat utilization in district heating: A model predictive control approach," Energy, Elsevier, vol. 234(C).
    7. Luca Urbanucci & Francesco D’Ettorre & Daniele Testi, 2019. "A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage," Energies, MDPI, vol. 12(5), pages 1-17, March.
    8. Simeoni, Patrizia & Ciotti, Gellio & Cottes, Mattia & Meneghetti, Antonella, 2019. "Integrating industrial waste heat recovery into sustainable smart energy systems," Energy, Elsevier, vol. 175(C), pages 941-951.
    9. Benalcazar, Pablo, 2021. "Optimal sizing of thermal energy storage systems for CHP plants considering specific investment costs: A case study," Energy, Elsevier, vol. 234(C).
    10. Hanne Kauko & Daniel Rohde & Brage Rugstad Knudsen & Terje Sund-Olsen, 2020. "Potential of Thermal Energy Storage for a District Heating System Utilizing Industrial Waste Heat," Energies, MDPI, vol. 13(15), pages 1-12, July.
    11. Li, Haoran & Hou, Juan & Hong, Tianzhen & Ding, Yuemin & Nord, Natasa, 2021. "Energy, economic, and environmental analysis of integration of thermal energy storage into district heating systems using waste heat from data centres," Energy, Elsevier, vol. 219(C).
    12. Connolly, D. & Lund, H. & Mathiesen, B.V. & Werner, S. & Möller, B. & Persson, U. & Boermans, T. & Trier, D. & Østergaard, P.A. & Nielsen, S., 2014. "Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system," Energy Policy, Elsevier, vol. 65(C), pages 475-489.
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