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Assessing the Uncertainties of Simulation Approaches for Solar Thermal Systems Coupled to Industrial Processes

Author

Listed:
  • José M. Cardemil

    (Department of Mechanical and Metallurgical Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

  • Ignacio Calderón-Vásquez

    (Department of Mechanical and Metallurgical Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

  • Alan Pino

    (Department of Energy Engineering, University of Seville, 41092 Sevilla, Spain)

  • Allan Starke

    (LEPTEN—Laboratory of Energy Conversion Engineering and Energy Technology, Department of Mechanical Engineering, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil)

  • Ian Wolde

    (Department of Mechanical and Metallurgical Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

  • Carlos Felbol

    (Center for Solar Energy Technologies, Fraunhofer Chile Research, Santiago 8580704, Chile)

  • Leonardo F. L. Lemos

    (LEPTEN—Laboratory of Energy Conversion Engineering and Energy Technology, Department of Mechanical Engineering, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil)

  • Vinicius Bonini

    (LEPTEN—Laboratory of Energy Conversion Engineering and Energy Technology, Department of Mechanical Engineering, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil)

  • Ignacio Arias

    (Department of Mechanical and Metallurgical Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

  • Javier Iñigo-Labairu

    (German Aerospace Center (DLR), Institute of Solar Research, Linder Höhe, 51147 Köln, Germany)

  • Jürgen Dersch

    (German Aerospace Center (DLR), Institute of Solar Research, Linder Höhe, 51147 Köln, Germany)

  • Rodrigo Escobar

    (Department of Mechanical and Metallurgical Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

Abstract

Industrial energy accounts for a large percentage of global consumption and, thus, it is a target for decarbonization by renewable and in particular solar energy adoption. Low uncertainty simulation tools can reduce the financial risk of solar projects, fostering the transition to a sustainable energy system. Several simulation tools are readily available to developers; differences exist in the format of input data and complexity of physical and numerical models. These tools can provide a variety of results from technical to financial and sensitivity analysis, often producing significant differences in yield assessment and uncertainty levels. IEA SHC Task 64/SolarPACES Task IV—Subtask C aims to address the lack of standard simulation tools for Solar Heating of Industrial Processes (SHIP) plants. This article describes the collaborative work developed by the researchers participating in the task. The identification and classification of several currently available simulation tools are performed on the basis of their capabilities and simulation approaches. A case study of solar heat supply to a copper mining operation is defined, allowing a comparison of the results produced by equivalent simulation tools. The proposed methodology identifies the main sources of differences among the simulation tools, the assessment of the deviation considering a series of statistical metrics for different time scales, and identifies their limitations and bias. The effects of physical characteristics of SHIP plants and different simulation approaches are discussed and quantified. The obtained results allow us to develop a basic guideline for a standardized yield assessment procedure with known uncertainties. Creating this common framework could partially reduce the risk perceived by the finance industry regarding SHIP systems.

Suggested Citation

  • José M. Cardemil & Ignacio Calderón-Vásquez & Alan Pino & Allan Starke & Ian Wolde & Carlos Felbol & Leonardo F. L. Lemos & Vinicius Bonini & Ignacio Arias & Javier Iñigo-Labairu & Jürgen Dersch & Rod, 2022. "Assessing the Uncertainties of Simulation Approaches for Solar Thermal Systems Coupled to Industrial Processes," Energies, MDPI, vol. 15(9), pages 1-29, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3333-:d:808063
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    References listed on IDEAS

    as
    1. Schoeneberger, Carrie A. & McMillan, Colin A. & Kurup, Parthiv & Akar, Sertac & Margolis, Robert & Masanet, Eric, 2020. "Solar for industrial process heat: A review of technologies, analysis approaches, and potential applications in the United States," Energy, Elsevier, vol. 206(C).
    2. Lugo, S. & García-Valladares, O. & Best, R. & Hernández, J. & Hernández, F., 2019. "Numerical simulation and experimental validation of an evacuated solar collector heating system with gas boiler backup for industrial process heating in warm climates," Renewable Energy, Elsevier, vol. 139(C), pages 1120-1132.
    3. Castillejo-Cuberos, Armando & Escobar, Rodrigo, 2020. "Understanding solar resource variability: An in-depth analysis, using Chile as a case of study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    4. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
    5. Eddouibi, Jaouad & Abderafi, Souad & Vaudreuil, Sébastien & Bounahmidi, Tijani, 2022. "Dynamic simulation of solar-powered ORC using open-source tools: A case study combining SAM and coolprop via Python," Energy, Elsevier, vol. 239(PA).
    6. Sanzana Tabassum & Tanvin Rahman & Ashraf Ul Islam & Sumayya Rahman & Debopriya Roy Dipta & Shidhartho Roy & Naeem Mohammad & Nafiu Nawar & Eklas Hossain, 2021. "Solar Energy in the United States: Development, Challenges and Future Prospects," Energies, MDPI, vol. 14(23), pages 1-65, December.
    7. jia, Teng & Huang, Junpeng & Li, Rui & He, Peng & Dai, Yanjun, 2018. "Status and prospect of solar heat for industrial processes in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 475-489.
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