IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v285y2021ics0306261921000222.html
   My bibliography  Save this article

Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis

Author

Listed:
  • Xiao, Sinan
  • Praditia, Timothy
  • Oladyshkin, Sergey
  • Nowak, Wolfgang

Abstract

Simulation models have been widely used for thermochemical energy storage to better understand its behavior and consequently to improve operational control of the device. However, incomplete knowledge of system properties leads to a significant number of uncertain parameters in the simulation models, which in turn cause uncertainties in system predictions. In this work, we perform global sensitivity analysis to identify the effect of uncertain parameters on the outputs of a thermochemical energy storage model, so that we can better understand the predictive uncertainties, proceed with targeted data acquisition or even simplify the corresponding uncertainty quantification. To get reliable sensitivity analysis results, we use both variance-based and regional sensitivity analysis since they focus on different probabilistic features of model outputs. Since the simulation model is computationally expensive, we use model reduction via the (arbitrary) polynomial chaos expansion. Then, to further confirm the results, the regional sensitivity index is also estimated based on the original model with the same given sample set. Based on the results of both sensitivity analysis methods, we can find that there are 8 unimportant parameters among 16 analyzed parameters. Thus, we can focus resources on investigating the important uncertain parameters. Also, we can ignore the uncertainty of unimportant parameters to simplify the corresponding uncertainty quantification.

Suggested Citation

  • Xiao, Sinan & Praditia, Timothy & Oladyshkin, Sergey & Nowak, Wolfgang, 2021. "Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis," Applied Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:appene:v:285:y:2021:i:c:s0306261921000222
    DOI: 10.1016/j.apenergy.2021.116456
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921000222
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.116456?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shao, H. & Nagel, T. & Roßkopf, C. & Linder, M. & Wörner, A. & Kolditz, O., 2013. "Non-equilibrium thermo-chemical heat storage in porous media: Part 2 – A 1D computational model for a calcium hydroxide reaction system," Energy, Elsevier, vol. 60(C), pages 271-282.
    2. Sinan Xiao & Zhenzhou Lu & Pan Wang, 2018. "Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2703-2721, December.
    3. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    4. Seitz, Gabriele & Helmig, Rainer & Class, Holger, 2020. "A numerical modeling study on the influence of porosity changes during thermochemical heat storage," Applied Energy, Elsevier, vol. 259(C).
    5. Garcia-Cabrejo, Oscar & Valocchi, Albert, 2014. "Global Sensitivity Analysis for multivariate output using Polynomial Chaos Expansion," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 25-36.
    6. Schmidt, Matthias & Gutierrez, Andrea & Linder, Marc, 2017. "Thermochemical energy storage with CaO/Ca(OH)2 – Experimental investigation of the thermal capability at low vapor pressures in a lab scale reactor," Applied Energy, Elsevier, vol. 188(C), pages 672-681.
    7. Emanuele Borgonovo & Gordon B. Hazen & Elmar Plischke, 2016. "A Common Rationale for Global Sensitivity Measures and Their Estimation," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1871-1895, October.
    8. Scapino, Luca & Zondag, Herbert A. & Van Bael, Johan & Diriken, Jan & Rindt, Camilo C.M., 2017. "Energy density and storage capacity cost comparison of conceptual solid and liquid sorption seasonal heat storage systems for low-temperature space heating," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1314-1331.
    9. Oladyshkin, Sergey & Nowak, Wolfgang, 2018. "Incomplete statistical information limits the utility of high-order polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 137-148.
    10. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    11. Xiao, Sinan & Lu, Zhenzhou & Wang, Pan, 2018. "Multivariate global sensitivity analysis for dynamic models based on wavelet analysis," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 20-30.
    12. Oladyshkin, S. & Nowak, W., 2012. "Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 179-190.
    13. E. E. Koks & M. Bočkarjova & H. de Moel & J. C. J. H. Aerts, 2015. "Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 882-900, May.
    14. Nagel, T. & Shao, H. & Roßkopf, C. & Linder, M. & Wörner, A. & Kolditz, O., 2014. "The influence of gas–solid reaction kinetics in models of thermochemical heat storage under monotonic and cyclic loading," Applied Energy, Elsevier, vol. 136(C), pages 289-302.
    15. Saltelli A. & Tarantola S., 2002. "On the Relative Importance of Input Factors in Mathematical Models: Safety Assessment for Nuclear Waste Disposal," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 702-709, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ziemba, Paweł, 2022. "Uncertain Multi-Criteria analysis of offshore wind farms projects investments – Case study of the Polish Economic Zone of the Baltic Sea," Applied Energy, Elsevier, vol. 309(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sinan Xiao & Zhenzhou Lu & Pan Wang, 2018. "Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2703-2721, December.
    2. Timothy Praditia & Thilo Walser & Sergey Oladyshkin & Wolfgang Nowak, 2020. "Improving Thermochemical Energy Storage Dynamics Forecast with Physics-Inspired Neural Network Architecture," Energies, MDPI, vol. 13(15), pages 1-26, July.
    3. Zhang, Kaichao & Lu, Zhenzhou & Cheng, Kai & Wang, Laijun & Guo, Yanling, 2020. "Global sensitivity analysis for multivariate output model and dynamic models," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    4. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    5. Shang, Xiaobing & Su, Li & Fang, Hai & Zeng, Bowen & Zhang, Zhi, 2023. "An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    6. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    7. Soha Saad & Florence Ossart & Jean Bigeon & Etienne Sourdille & Harold Gance, 2021. "Global Sensitivity Analysis Applied to Train Traffic Rescheduling: A Comparative Study," Energies, MDPI, vol. 14(19), pages 1-29, October.
    8. Xing Liu & Enrico Zio & Emanuele Borgonovo & Elmar Plischke, 2024. "A Systematic Approach of Global Sensitivity Analysis and Its Application to a Model for the Quantification of Resilience of Interconnected Critical Infrastructures," Energies, MDPI, vol. 17(8), pages 1-24, April.
    9. Risthaus, Kai & Bürger, Inga & Linder, Marc & Schmidt, Matthias, 2020. "Numerical analysis of the hydration of calcium oxide in a fixed bed reactor based on lab-scale experiments," Applied Energy, Elsevier, vol. 261(C).
    10. Yicheng Zhou & Zhenzhou Lu & Yan Shi & Kai Cheng, 2019. "A vine copula–based method for analyzing the moment-independent importance measure of the multivariate output," Journal of Risk and Reliability, , vol. 233(3), pages 338-354, June.
    11. Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
    12. Isadora Antoniano‐Villalobos & Emanuele Borgonovo & Sumeda Siriwardena, 2018. "Which Parameters Are Important? Differential Importance Under Uncertainty," Risk Analysis, John Wiley & Sons, vol. 38(11), pages 2459-2477, November.
    13. Seitz, Gabriele & Helmig, Rainer & Class, Holger, 2020. "A numerical modeling study on the influence of porosity changes during thermochemical heat storage," Applied Energy, Elsevier, vol. 259(C).
    14. Elmar Plischke & Emanuele Borgonovo, 2020. "Fighting the Curse of Sparsity: Probabilistic Sensitivity Measures From Cumulative Distribution Functions," Risk Analysis, John Wiley & Sons, vol. 40(12), pages 2639-2660, December.
    15. Nagel, Thomas & Beckert, Steffen & Lehmann, Christoph & Gläser, Roger & Kolditz, Olaf, 2016. "Multi-physical continuum models of thermochemical heat storage and transformation in porous media and powder beds—A review," Applied Energy, Elsevier, vol. 178(C), pages 323-345.
    16. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    17. Wang, Wenqing & Kolditz, Olaf & Nagel, Thomas, 2017. "Parallel finite element modelling of multi-physical processes in thermochemical energy storage devices," Applied Energy, Elsevier, vol. 185(P2), pages 1954-1964.
    18. Tobias Fissler & Silvana M. Pesenti, 2022. "Sensitivity Measures Based on Scoring Functions," Papers 2203.00460, arXiv.org, revised Jul 2022.
    19. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    20. Xuefei Lu & Alessandro Rudi & Emanuele Borgonovo & Lorenzo Rosasco, 2020. "Faster Kriging: Facing High-Dimensional Simulators," Operations Research, INFORMS, vol. 68(1), pages 233-249, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:285:y:2021:i:c:s0306261921000222. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.