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Modelling of organic Rankine cycle power systems in off-design conditions: An experimentally-validated comparative study

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  • Dickes, Rémi
  • Dumont, Olivier
  • Daccord, Rémi
  • Quoilin, Sylvain
  • Lemort, Vincent

Abstract

Because of environmental issues and the depletion of fossil fuels, the world energy sector is undergoing many changes toward increased sustainability. Among the many fields of research and development, power generation from low-grade heat sources is gaining interest and the organic Rankine cycle (ORC) is seen as one of the most promising technologies for such applications. In this paper, it is proposed to perform an experimentally-validated comparison of different modelling methods for the off-design simulation of ORC-based power systems. To this end, three types of modelling paradigms (namely a constant-efficiency method, a polynomial-based method and a semi-empirical method) are compared both in terms of their fitting and extrapolation capabilities. Post-processed measurements gathered on two experimental ORC facilities are used as reference for the models calibration and evaluation. The study is first applied at a component level (i.e. each component is analysed individually) and then extended to the characterization of the entire organic Rankine cycle power systems. Benefits and limitations of each modelling method are discussed. The results show that semi-empirical models are the most reliable for simulating the off-design working conditions of ORC systems, while constant-efficiency and polynomial-based models are both demonstrating lack of accuracy and/or robustness.

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  • Dickes, Rémi & Dumont, Olivier & Daccord, Rémi & Quoilin, Sylvain & Lemort, Vincent, 2017. "Modelling of organic Rankine cycle power systems in off-design conditions: An experimentally-validated comparative study," Energy, Elsevier, vol. 123(C), pages 710-727.
    • Handle: RePEc:eee:energy:v:123:y:2017:i:c:p:710-727
    DOI: 10.1016/j.energy.2017.01.130
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    5. Dickes, Rémi & Dumont, Olivier & Guillaume, Ludovic & Quoilin, Sylvain & Lemort, Vincent, 2018. "Charge-sensitive modelling of organic Rankine cycle power systems for off-design performance simulation," Applied Energy, Elsevier, vol. 212(C), pages 1262-1281.
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    10. Chatzopoulou, Maria Anna & Lecompte, Steven & Paepe, Michel De & Markides, Christos N., 2019. "Off-design optimisation of organic Rankine cycle (ORC) engines with different heat exchangers and volumetric expanders in waste heat recovery applications," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    11. Ancona, Maria Alessandra & Bianchi, Michele & Branchini, Lisa & De Pascale, Andrea & Melino, Francesco & Peretto, Antonio & Poletto, Chiara & Torricelli, Noemi, 2022. "Solar driven micro-ORC system assessment for residential application," Renewable Energy, Elsevier, vol. 195(C), pages 167-181.
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    13. Petrollese, Mario & Cau, Giorgio & Cocco, Daniele, 2020. "The Ottana solar facility: dispatchable power from small-scale CSP plants based on ORC systems," Renewable Energy, Elsevier, vol. 147(P3), pages 2932-2943.
    14. Kutlu, Cagri & Erdinc, Mehmet Tahir & Li, Jing & Su, Yuehong & Pei, Gang & Gao, Guangtao & Riffat, Saffa, 2020. "Evaluate the validity of the empirical correlations of clearance and friction coefficients to improve a scroll expander semi-empirical model," Energy, Elsevier, vol. 202(C).
    15. Fabio Fatigati & Diego Vittorini & Yaxiong Wang & Jian Song & Christos N. Markides & Roberto Cipollone, 2020. "Design and Operational Control Strategy for Optimum Off-Design Performance of an ORC Plant for Low-Grade Waste Heat Recovery," Energies, MDPI, vol. 13(21), pages 1-23, November.
    16. Liu, Liuchen & Zhu, Tong & Wang, Tiantian & Gao, Naiping, 2019. "Experimental investigation on the effect of working fluid charge in a small-scale Organic Rankine Cycle under off-design conditions," Energy, Elsevier, vol. 174(C), pages 664-677.
    17. Osman Özkaraca & Pınar Keçebaş & Cihan Demircan & Ali Keçebaş, 2017. "Thermodynamic Optimization of a Geothermal- Based Organic Rankine Cycle System Using an Artificial Bee Colony Algorithm," Energies, MDPI, vol. 10(11), pages 1-28, October.
    18. Petrollese, Mario & Cocco, Daniele, 2020. "A multi-scenario approach for a robust design of solar-based ORC systems," Renewable Energy, Elsevier, vol. 161(C), pages 1184-1194.
    19. Wang, Z.X. & Du, S. & Wang, L.W. & Chen, X., 2020. "Parameter analysis of an ammonia-water power cycle with a gravity assisted thermal driven “pump” for low-grade heat recovery," Renewable Energy, Elsevier, vol. 146(C), pages 651-661.
    20. Wei, Youxing & Luo, Xianglong & Liang, Yingzong & Chen, Jianyong & Yang, Zhi & He, Jiacheng & Wang, Chao & Chen, Ying, 2022. "Time series aggregation-based design and operation optimization of a solar-driven organic Rankine cycle incorporating variation of environmental temperature and solar radiation," Renewable Energy, Elsevier, vol. 192(C), pages 87-106.
    21. Lecompte, Steven & Gusev, Sergei & Vanslambrouck, Bruno & De Paepe, Michel, 2018. "Experimental results of a small-scale organic Rankine cycle: Steady state identification and application to off-design model validation," Applied Energy, Elsevier, vol. 226(C), pages 82-106.
    22. Liu, Changwei & Gao, Tieyu, 2019. "Off-design performance analysis of basic ORC, ORC using zeotropic mixtures and composition-adjustable ORC under optimal control strategy," Energy, Elsevier, vol. 171(C), pages 95-108.
    23. Imran, Muhammad & Pili, Roberto & Usman, Muhammad & Haglind, Fredrik, 2020. "Dynamic modeling and control strategies of organic Rankine cycle systems: Methods and challenges," Applied Energy, Elsevier, vol. 276(C).
    24. Bianchi, M. & Branchini, L. & De Pascale, A. & Melino, F. & Ottaviano, S. & Peretto, A. & Torricelli, N., 2020. "Replacement of R134a with low-GWP fluids in a kW-size reciprocating piston expander: Performance prediction and design optimization," Energy, Elsevier, vol. 206(C).

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