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Fuzzy Nonlinear Dynamic Evaporator Model in Supercritical Organic Rankine Cycle Waste Heat Recovery Systems

Author

Listed:
  • Jahedul Islam Chowdhury

    (School of Water, Energy and Environment, Cranfield University, Bedford MK43 0AL, UK
    School of Management, Cranfield University, Bedford MK43 0AL, UK)

  • Bao Kha Nguyen

    (School of Engineering and Informatics, University of Sussex, Brighton BN1 9QT, UK)

  • David Thornhill

    (School of Mechanical and Aerospace Engineering, Queen’s University Belfast, Belfast BT9 5AH, UK)

  • Yukun Hu

    (School of Management, Cranfield University, Bedford MK43 0AL, UK)

  • Payam Soulatiantork

    (School of Mechanical and Aerospace Engineering, Queen’s University Belfast, Belfast BT9 5AH, UK)

  • Nazmiye Balta-Ozkan

    (School of Water, Energy and Environment, Cranfield University, Bedford MK43 0AL, UK)

  • Liz Varga

    (School of Management, Cranfield University, Bedford MK43 0AL, UK)

Abstract

The organic Rankine cycle (ORC)-based waste heat recovery (WHR) system operating under a supercritical condition has a higher potential of thermal efficiency and work output than a traditional subcritical cycle. However, the operation of supercritical cycles is more challenging due to the high pressure in the system and transient behavior of waste heat sources from industrial and automotive engines that affect the performance of the system and the evaporator, which is the most crucial component of the ORC. To take the transient behavior into account, the dynamic model of the evaporator using renowned finite volume (FV) technique is developed in this paper. Although the FV model can capture the transient effects accurately, the model has a limitation for real-time control applications due to its time-intensive computation. To capture the transient effects and reduce the simulation time, a novel fuzzy-based nonlinear dynamic evaporator model is also developed and presented in this paper. The results show that the fuzzy-based model was able to capture the transient effects at a data fitness of over 90%, while it has potential to complete the simulation 700 times faster than the FV model. By integrating with other subcomponent models of the system, such as pump, expander, and condenser, the predicted system output and pressure have a mean average percentage error of 3.11% and 0.001%, respectively. These results suggest that the developed fuzzy-based evaporator and the overall ORC-WHR system can be used for transient simulations and to develop control strategies for real-time applications.

Suggested Citation

  • Jahedul Islam Chowdhury & Bao Kha Nguyen & David Thornhill & Yukun Hu & Payam Soulatiantork & Nazmiye Balta-Ozkan & Liz Varga, 2018. "Fuzzy Nonlinear Dynamic Evaporator Model in Supercritical Organic Rankine Cycle Waste Heat Recovery Systems," Energies, MDPI, vol. 11(4), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:901-:d:140596
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    References listed on IDEAS

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    1. Ziviani, Davide & Beyene, Asfaw & Venturini, Mauro, 2014. "Advances and challenges in ORC systems modeling for low grade thermal energy recovery," Applied Energy, Elsevier, vol. 121(C), pages 79-95.
    2. Jahedul Islam Chowdhury & Bao Kha Nguyen & David Thornhill, 2015. "Modelling of Evaporator in Waste Heat Recovery System using Finite Volume Method and Fuzzy Technique," Energies, MDPI, vol. 8(12), pages 1-20, December.
    3. Lecompte, S. & Huisseune, H. & van den Broek, M. & De Paepe, M., 2015. "Methodical thermodynamic analysis and regression models of organic Rankine cycle architectures for waste heat recovery," Energy, Elsevier, vol. 87(C), pages 60-76.
    4. Zhang, Jianhua & Zhou, Yeli & Wang, Rui & Xu, Jinliang & Fang, Fang, 2014. "Modeling and constrained multivariable predictive control for ORC (Organic Rankine Cycle) based waste heat energy conversion systems," Energy, Elsevier, vol. 66(C), pages 128-138.
    5. Declaye, Sébastien & Quoilin, Sylvain & Guillaume, Ludovic & Lemort, Vincent, 2013. "Experimental study on an open-drive scroll expander integrated into an ORC (Organic Rankine Cycle) system with R245fa as working fluid," Energy, Elsevier, vol. 55(C), pages 173-183.
    6. Glover, Stephen & Douglas, Roy & De Rosa, Mattia & Zhang, Xiaolei & Glover, Laura, 2015. "Simulation of a multiple heat source supercritical ORC (Organic Rankine Cycle) for vehicle waste heat recovery," Energy, Elsevier, vol. 93(P2), pages 1568-1580.
    7. Shu, Gequn & Yu, Guopeng & Tian, Hua & Wei, Haiqiao & Liang, Xingyu, 2014. "A Multi-Approach Evaluation System (MA-ES) of Organic Rankine Cycles (ORC) used in waste heat utilization," Applied Energy, Elsevier, vol. 132(C), pages 325-338.
    8. Quoilin, Sylvain & Aumann, Richard & Grill, Andreas & Schuster, Andreas & Lemort, Vincent & Spliethoff, Hartmut, 2011. "Dynamic modeling and optimal control strategy of waste heat recovery Organic Rankine Cycles," Applied Energy, Elsevier, vol. 88(6), pages 2183-2190, June.
    9. Chen, Huijuan & Goswami, D. Yogi & Rahman, Muhammad M. & Stefanakos, Elias K., 2011. "A supercritical Rankine cycle using zeotropic mixture working fluids for the conversion of low-grade heat into power," Energy, Elsevier, vol. 36(1), pages 549-555.
    10. Wang, Z.Q. & Zhou, N.J. & Guo, J. & Wang, X.Y., 2012. "Fluid selection and parametric optimization of organic Rankine cycle using low temperature waste heat," Energy, Elsevier, vol. 40(1), pages 107-115.
    11. Yağlı, Hüseyin & Koç, Yıldız & Koç, Ali & Görgülü, Adnan & Tandiroğlu, Ahmet, 2016. "Parametric optimization and exergetic analysis comparison of subcritical and supercritical organic Rankine cycle (ORC) for biogas fuelled combined heat and power (CHP) engine exhaust gas waste heat," Energy, Elsevier, vol. 111(C), pages 923-932.
    12. Bamgbopa, Musbaudeen O. & Uzgoren, Eray, 2013. "Numerical analysis of an organic Rankine cycle under steady and variable heat input," Applied Energy, Elsevier, vol. 107(C), pages 219-228.
    13. Gheith, Ramla & Aloui, Fethi & Ben Nasrallah, Sassi, 2015. "Determination of adequate regenerator for a Gamma-type Stirling engine," Applied Energy, Elsevier, vol. 139(C), pages 272-280.
    14. Hong Gao & Chao Liu & Chao He & Xiaoxiao Xu & Shuangying Wu & Yourong Li, 2012. "Performance Analysis and Working Fluid Selection of a Supercritical Organic Rankine Cycle for Low Grade Waste Heat Recovery," Energies, MDPI, vol. 5(9), pages 1-15, August.
    15. Schuster, A. & Karellas, S. & Aumann, R., 2010. "Efficiency optimization potential in supercritical Organic Rankine Cycles," Energy, Elsevier, vol. 35(2), pages 1033-1039.
    16. Tian, Hua & Shu, Gequn & Wei, Haiqiao & Liang, Xingyu & Liu, Lina, 2012. "Fluids and parameters optimization for the organic Rankine cycles (ORCs) used in exhaust heat recovery of Internal Combustion Engine (ICE)," Energy, Elsevier, vol. 47(1), pages 125-136.
    17. Braimakis, Konstantinos & Preißinger, Markus & Brüggemann, Dieter & Karellas, Sotirios & Panopoulos, Kyriakos, 2015. "Low grade waste heat recovery with subcritical and supercritical Organic Rankine Cycle based on natural refrigerants and their binary mixtures," Energy, Elsevier, vol. 88(C), pages 80-92.
    18. Le, Van Long & Feidt, Michel & Kheiri, Abdelhamid & Pelloux-Prayer, Sandrine, 2014. "Performance optimization of low-temperature power generation by supercritical ORCs (organic Rankine cycles) using low GWP (global warming potential) working fluids," Energy, Elsevier, vol. 67(C), pages 513-526.
    19. Zhang, Jianhua & Zhou, Yeli & Li, Ying & Hou, Guolian & Fang, Fang, 2013. "Generalized predictive control applied in waste heat recovery power plants," Applied Energy, Elsevier, vol. 102(C), pages 320-326.
    20. Emanuel Feru & Frank Willems & Bram De Jager & Maarten Steinbuch, 2014. "Modeling and Control of a Parallel Waste Heat Recovery System for Euro-VI Heavy-Duty Diesel Engines," Energies, MDPI, vol. 7(10), pages 1-22, October.
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    3. Yıldız Koç & Hüseyin Yağlı & Ali Koç, 2019. "Exergy Analysis and Performance Improvement of a Subcritical/Supercritical Organic Rankine Cycle (ORC) for Exhaust Gas Waste Heat Recovery in a Biogas Fuelled Combined Heat and Power (CHP) Engine Thro," Energies, MDPI, vol. 12(4), pages 1-22, February.
    4. Chowdhury, Jahedul Islam & Hu, Yukun & Haltas, Ismail & Balta-Ozkan, Nazmiye & Matthew, George Jr. & Varga, Liz, 2018. "Reducing industrial energy demand in the UK: A review of energy efficiency technologies and energy saving potential in selected sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1153-1178.
    5. Wanming Pan & Junkang Li & Guotao Zhang & Le Zhou & Ming Tu, 2022. "Multi-Objective Optimization of Organic Rankine Cycle (ORC) for Tractor Waste Heat Recovery Based on Particle Swarm Optimization," Energies, MDPI, vol. 15(18), pages 1-24, September.

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