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Thermal energy storage sizing for industrial waste-heat utilization in district heating: A model predictive control approach

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  • Knudsen, Brage Rugstad
  • Rohde, Daniel
  • Kauko, Hanne

Abstract

Thermal energy storage (TES) is a key technology for enabling increased utilization of industrial waste heat in district heating. The ability of TES to equalize offsets in demand and supply depends strongly on the sizing, control and integration in a heating plant. We consider the problem of sizing TES in heating plants utilizing a varying waste-heat source. To this end, we propose a combined dynamic simulation and model predictive control approach that accounts for the dynamics and optimal control of the heating plant with TES. A case study has been carried out on a district-heating plant located in Norway, with 90% of its annual heat production being heat recovered from the off-gas from a ferrosilicon plant. We evaluate the effective peak-heating reduction with different TES sizes and the energy-to-heat-flow-ratio for the TES discharging periods as performance metrics. For the case study, our results suggest that a modest TES tank volume of 1500 m3 is sufficient to achieve a half-year peak-heating reduction of 12% and comparable performance with larger volumes. The proposed methodology constitutes a numerically tractable means of incorporating the impact of model predictive control on the sizing of TES for heating plants with time-varying waste-heat supply and demand.

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  • 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).
    • Handle: RePEc:eee:energy:v:234:y:2021:i:c:s0360544221014481
    DOI: 10.1016/j.energy.2021.121200
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    as
    1. Cao, Muwen & Cao, Jiacong, 2006. "Optimal design of thermal-energy stores for boiler plants," Applied Energy, Elsevier, vol. 83(1), pages 55-68, January.
    2. Miró, Laia & Brückner, Sarah & Cabeza, Luisa F., 2015. "Mapping and discussing Industrial Waste Heat (IWH) potentials for different countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 847-855.
    3. Wheatcroft, Edward & Wynn, Henry P. & Lygnerud, Kristina & Bonvicini, Giorgio & Bonvicini, Giorgio & Lenote, Daniela, 2020. "The role of low temperature waste heat recovery in achieving 2050 goals: a policy positioning paper," LSE Research Online Documents on Economics 104136, London School of Economics and Political Science, LSE Library.
    4. 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.
    5. Schweiger, Gerald & Larsson, Per-Ola & Magnusson, Fredrik & Lauenburg, Patrick & Velut, Stéphane, 2017. "District heating and cooling systems – Framework for Modelica-based simulation and dynamic optimization," Energy, Elsevier, vol. 137(C), pages 566-578.
    6. 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.
    7. Zerrahn, Alexander & Schill, Wolf-Peter, 2017. "Long-run power storage requirements for high shares of renewables: review and a new model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1518-1534.
    8. Das, Choton K. & Bass, Octavian & Kothapalli, Ganesh & Mahmoud, Thair S. & Habibi, Daryoush, 2018. "Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1205-1230.
    9. 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.
    10. Guelpa, Elisa & Marincioni, Ludovica & Capone, Martina & Deputato, Stefania & Verda, Vittorio, 2019. "Thermal load prediction in district heating systems," Energy, Elsevier, vol. 176(C), pages 693-703.
    11. 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.
    12. 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).
    13. Pérez-Iribarren, E. & González-Pino, I. & Azkorra-Larrinaga, Z. & Gómez-Arriarán, I., 2020. "Optimal design and operation of thermal energy storage systems in micro-cogeneration plants," Applied Energy, Elsevier, vol. 265(C).
    14. Brage Rugstad Knudsen & Hanne Kauko & Trond Andresen, 2019. "An Optimal-Control Scheme for Coordinated Surplus-Heat Exchange in Industry Clusters," Energies, MDPI, vol. 12(10), pages 1-22, May.
    15. 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.
    16. van der Heijde, Bram & Vandermeulen, Annelies & Salenbien, Robbe & Helsen, Lieve, 2019. "Representative days selection for district energy system optimisation: a solar district heating system with seasonal storage," Applied Energy, Elsevier, vol. 248(C), pages 79-94.
    17. Persson, U. & Möller, B. & Werner, S., 2014. "Heat Roadmap Europe: Identifying strategic heat synergy regions," Energy Policy, Elsevier, vol. 74(C), pages 663-681.
    18. Edward Wheatcroft & Henry Wynn & Kristina Lygnerud & Giorgio Bonvicini & Daniela Leonte, 2020. "The Role of Low Temperature Waste Heat Recovery in Achieving 2050 Goals: A Policy Positioning Paper," Energies, MDPI, vol. 13(8), pages 1-19, April.
    19. Eligius M. T. Hendrix & Boglárka G.-Tóth, 2010. "Nonlinear Programming algorithms," Springer Optimization and Its Applications, in: Introduction to Nonlinear and Global Optimization, chapter 5, pages 91-136, Springer.
    20. Simeoni, Patrizia & Nardin, Gioacchino & Ciotti, Gellio, 2018. "Planning and design of sustainable smart multi energy systems. The case of a food industrial district in Italy," Energy, Elsevier, vol. 163(C), pages 443-456.
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