IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v241y2019icp313-330.html
   My bibliography  Save this article

Uncertainty Quantification in high-density fluid radial-inflow turbines for renewable low-grade temperature cycles

Author

Listed:
  • Zou, Aihong
  • Chassaing, Jean-Camille
  • Persky, Rodney
  • Gu, YuanTong
  • Sauret, Emilie

Abstract

The inclusion of uncertainties in the design of turbines for renewable low-grade temperature power cycles is becoming a crucial aspect in the development of robust and reliable power blocks capable of handling a better range of efficiencies over a wider range of operational conditions. Modelling high-density fluids using existing Equations of State adds complexity to improving the system efficiency and little is known on the effect that the uncertainties of Equations of State parameters may have on the turbine efficiency. The purpose of this paper is to quantify the influence of coupled uncertain variables on the total-to-static efficiency of a radial-inflow Organic Rankine Cycle turbine with a high-density fluid R143a in a low-grade temperature renewable power block. To this end, a stochastic solution is obtained by combining a multi-dimensional generalized Polynomial Chaos approach with a full three-dimensional viscous turbulent Computational Fluid Dynamics solver for high-density radial-inflow turbines. Both operational conditions (inlet total temperature, rotational speed and mass flow rate) and Equations of State parameters (critical pressure and critical temperature) are investigated, highlighting their importance for turbine efficiency based on the consideration of three Equations of State, namely, Peng-Robinson, Soave-Redlich-Kwong, and HHEOS. This study, which is performed for both nominal and off-design operational conditions, highlights the inlet temperature as the most influential operational uncertain parameters, while the critical pressure is the most sensitive parameter for the three Equations of State tested. More importantly, it demonstrates a higher level of sensitivity of the SRK Equations of State, in particular at off-design operational conditions. This is a crucial aspect to take into account for the robust designs of Organic Rankine Cycle turbines for low-grade temperature renewable power cycles working at various conditions. It is expected that the proposed stochastic approach may consequently positively support the renewable energy sector to develop more robust and viable systems.

Suggested Citation

  • Zou, Aihong & Chassaing, Jean-Camille & Persky, Rodney & Gu, YuanTong & Sauret, Emilie, 2019. "Uncertainty Quantification in high-density fluid radial-inflow turbines for renewable low-grade temperature cycles," Applied Energy, Elsevier, vol. 241(C), pages 313-330.
    • Handle: RePEc:eee:appene:v:241:y:2019:i:c:p:313-330
    DOI: 10.1016/j.apenergy.2019.03.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919304180
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.03.021?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. Nithesh, K.G. & Chatterjee, Dhiman & Oh, Cheol & Lee, Young-Ho, 2016. "Design and performance analysis of radial-inflow turboexpander for OTEC application," Renewable Energy, Elsevier, vol. 85(C), pages 834-843.
    2. Connolly, D. & Lund, H. & Mathiesen, B.V., 2016. "Smart Energy Europe: The technical and economic impact of one potential 100% renewable energy scenario for the European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1634-1653.
    3. Da Lio, Luca & Manente, Giovanni & Lazzaretto, Andrea, 2017. "A mean-line model to predict the design efficiency of radial inflow turbines in organic Rankine cycle (ORC) systems," Applied Energy, Elsevier, vol. 205(C), pages 187-209.
    4. Merle, X. & Cinnella, P., 2015. "Bayesian quantification of thermodynamic uncertainties in dense gas flows," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 305-323.
    5. Kim, Do-Yeop & Kim, You-Taek, 2017. "Preliminary design and performance analysis of a radial inflow turbine for ocean thermal energy conversion," Renewable Energy, Elsevier, vol. 106(C), pages 255-263.
    6. Merle, X. & Cinnella, P., 2019. "Robust prediction of dense gas flows under uncertain thermodynamic models," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 400-421.
    7. Costall, A.W. & Gonzalez Hernandez, A. & Newton, P.J. & Martinez-Botas, R.F., 2015. "Design methodology for radial turbo expanders in mobile organic Rankine cycle applications," Applied Energy, Elsevier, vol. 157(C), pages 729-743.
    8. Fiaschi, Daniele & Manfrida, Giampaolo & Maraschiello, Francesco, 2012. "Thermo-fluid dynamics preliminary design of turbo-expanders for ORC cycles," Applied Energy, Elsevier, vol. 97(C), pages 601-608.
    9. Sauret, Emilie & Gu, Yuantong, 2014. "Three-dimensional off-design numerical analysis of an organic Rankine cycle radial-inflow turbine," Applied Energy, Elsevier, vol. 135(C), pages 202-211.
    10. Al Jubori, Ayad M. & Al-Dadah, Raya K. & Mahmoud, Saad & Daabo, Ahmed, 2017. "Modelling and parametric analysis of small-scale axial and radial-outflow turbines for Organic Rankine Cycle applications," Applied Energy, Elsevier, vol. 190(C), pages 981-996.
    11. Alshammari, Fuhaid & Pesyridis, Apostolos & Karvountzis-Kontakiotis, Apostolos & Franchetti, Ben & Pesmazoglou, Yagos, 2018. "Experimental study of a small scale organic Rankine cycle waste heat recovery system for a heavy duty diesel engine with focus on the radial inflow turbine expander performance," Applied Energy, Elsevier, vol. 215(C), pages 543-555.
    12. Kang, Seok Hun, 2012. "Design and experimental study of ORC (organic Rankine cycle) and radial turbine using R245fa working fluid," Energy, Elsevier, vol. 41(1), pages 514-524.
    13. Razaaly, Nassim & Persico, Giacomo & Congedo, Pietro Marco, 2019. "Impact of geometric, operational, and model uncertainties on the non-ideal flow through a supersonic ORC turbine cascade," Energy, Elsevier, vol. 169(C), pages 213-227.
    14. Sauret, Emilie & Rowlands, Andrew S., 2011. "Candidate radial-inflow turbines and high-density working fluids for geothermal power systems," Energy, Elsevier, vol. 36(7), pages 4460-4467.
    15. Fiaschi, Daniele & Manfrida, Giampaolo & Maraschiello, Francesco, 2015. "Design and performance prediction of radial ORC turboexpanders," Applied Energy, Elsevier, vol. 138(C), pages 517-532.
    16. Chen, Qicheng & Xu, Jinliang & Chen, Hongxia, 2012. "A new design method for Organic Rankine Cycles with constraint of inlet and outlet heat carrier fluid temperatures coupling with the heat source," Applied Energy, Elsevier, vol. 98(C), pages 562-573.
    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. Fuhaid Alshammari & Apostolos Pesyridis & Mohamed Elashmawy, 2020. "Generation of 3D Turbine Blades for Automotive Organic Rankine Cycles: Mathematical and Computational Perspectives," Mathematics, MDPI, vol. 9(1), pages 1-30, December.
    2. Qyyum, Muhammad Abdul & Duong, Pham Luu Trung & Minh, Le Quang & Lee, Sanggyu & Lee, Moonyong, 2019. "Dual mixed refrigerant LNG process: Uncertainty quantification and dimensional reduction sensitivity analysis," Applied Energy, Elsevier, vol. 250(C), pages 1446-1456.
    3. Zou, Aihong & Zeng, Yupei & Luo, Ercang, 2023. "New generation hydrogen liquefaction technology by transonic two-phase expander," Energy, Elsevier, vol. 272(C).
    4. Tang, Xinzi & Yuan, Keren & Gu, Nengwei & Li, Pengcheng & Peng, Ruitao, 2022. "An interval quantification-based optimization approach for wind turbine airfoil under uncertainties," Energy, Elsevier, vol. 244(PA).

    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. Nithesh, K.G. & Chatterjee, Dhiman, 2016. "Numerical prediction of the performance of radial inflow turbine designed for ocean thermal energy conversion system," Applied Energy, Elsevier, vol. 167(C), pages 1-16.
    2. Al Jubori, Ayad M. & Al-Dadah, Raya K. & Mahmoud, Saad & Daabo, Ahmed, 2017. "Modelling and parametric analysis of small-scale axial and radial-outflow turbines for Organic Rankine Cycle applications," Applied Energy, Elsevier, vol. 190(C), pages 981-996.
    3. Deligant, Michael & Sauret, Emilie & Danel, Quentin & Bakir, Farid, 2020. "Performance assessment of a standard radial turbine as turbo expander for an adapted solar concentration ORC," Renewable Energy, Elsevier, vol. 147(P3), pages 2833-2841.
    4. Zhang, Chengbin & Wu, Zhe & Wang, Jiadian & Ding, Ce & Gao, Tieyu & Chen, Yongping, 2023. "Thermodynamic performance of a radial-inflow turbine for ocean thermal energy conversion using ammonia," Renewable Energy, Elsevier, vol. 202(C), pages 907-920.
    5. Witanowski, Łukasz & Ziółkowski, Paweł & Klonowicz, Piotr & Lampart, Piotr, 2023. "A hybrid approach to optimization of radial inflow turbine with principal component analysis," Energy, Elsevier, vol. 272(C).
    6. Da Lio, Luca & Manente, Giovanni & Lazzaretto, Andrea, 2017. "A mean-line model to predict the design efficiency of radial inflow turbines in organic Rankine cycle (ORC) systems," Applied Energy, Elsevier, vol. 205(C), pages 187-209.
    7. Kaczmarczyk, Tomasz Z. & Żywica, Grzegorz & Ihnatowicz, Eugeniusz, 2017. "The impact of changes in the geometry of a radial microturbine stage on the efficiency of the micro CHP plant based on ORC," Energy, Elsevier, vol. 137(C), pages 530-543.
    8. Wang, Zhiqi & Xie, Baoqi & Xia, Xiaoxia & Luo, Lan & Yang, Huya & Li, Xin, 2023. "Entropy production analysis of a radial inflow turbine with variable inlet guide vane for ORC application," Energy, Elsevier, vol. 265(C).
    9. Peng Li & Zhonghe Han & Xiaoqiang Jia & Zhongkai Mei & Xu Han, 2018. "Analysis of the Effects of Blade Installation Angle and Blade Number on Radial-Inflow Turbine Stator Flow Performance," Energies, MDPI, vol. 11(9), pages 1-15, August.
    10. Nithesh, K.G. & Chatterjee, Dhiman & Oh, Cheol & Lee, Young-Ho, 2016. "Design and performance analysis of radial-inflow turboexpander for OTEC application," Renewable Energy, Elsevier, vol. 85(C), pages 834-843.
    11. Martin T. White & Abdulnaser I. Sayma, 2018. "A Generalised Assessment of Working Fluids and Radial Turbines for Non-Recuperated Subcritical Organic Rankine Cycles," Energies, MDPI, vol. 11(4), pages 1-26, March.
    12. Enhua Wang & Ningjian Peng, 2023. "A Review on the Preliminary Design of Axial and Radial Turbines for Small-Scale Organic Rankine Cycle," Energies, MDPI, vol. 16(8), pages 1-20, April.
    13. Bao, Junjiang & Zhao, Li, 2013. "A review of working fluid and expander selections for organic Rankine cycle," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 325-342.
    14. Fuhaid Alshammari & Apostolos Pesyridis & Mohamed Elashmawy, 2020. "Generation of 3D Turbine Blades for Automotive Organic Rankine Cycles: Mathematical and Computational Perspectives," Mathematics, MDPI, vol. 9(1), pages 1-30, December.
    15. Ningjian Peng & Enhua Wang & Hongguang Zhang, 2021. "Preliminary Design of an Axial-Flow Turbine for Small-Scale Supercritical Organic Rankine Cycle," Energies, MDPI, vol. 14(17), pages 1-20, August.
    16. Lisheng Pan & Huaixin Wang, 2019. "Experimental Investigation on Performance of an Organic Rankine Cycle System Integrated with a Radial Flow Turbine," Energies, MDPI, vol. 12(4), pages 1-20, February.
    17. Al Jubori, Ayad M. & Al-Dadah, Raya & Mahmoud, Saad, 2017. "Performance enhancement of a small-scale organic Rankine cycle radial-inflow turbine through multi-objective optimization algorithm," Energy, Elsevier, vol. 131(C), pages 297-311.
    18. Weiß, Andreas P. & Novotný, Václav & Popp, Tobias & Streit, Philipp & Špale, Jan & Zinn, Gerd & Kolovratník, Michal, 2020. "Customized ORC micro turbo-expanders - From 1D design to modular construction kit and prospects of additive manufacturing," Energy, Elsevier, vol. 209(C).
    19. Li, Xiaoming & Lv, Cui & Yang, Shaoqi & Li, Jian & Deng, Bicai & Li, Qing, 2019. "Preliminary design and performance analysis of a radial inflow turbine for a large-scale helium cryogenic system," Energy, Elsevier, vol. 167(C), pages 106-116.
    20. White, Martin T. & Read, Matthew G. & Sayma, Abdulnaser I., 2020. "Making the case for cascaded organic Rankine cycles for waste-heat recovery," Energy, Elsevier, vol. 211(C).

    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:241:y:2019:i:c:p:313-330. 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.