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Methodology for estimating thermodynamic parameters and performance of working fluids for organic Rankine cycles

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  • Brown, J. Steven
  • Brignoli, Riccardo
  • Daubman, Samantha

Abstract

In this paper, a simple methodology of applying the Peng–Robinson (P–R) EoS (Equation of State) to easily, quickly, and inexpensively evaluate and screen the performance potentials of many thousands of working fluids in ORC (organic Rankine cycles) is presented. The P–R EoS can be applied both to well-described (considerable experimental data is available) and not-so-well-described (little or no experimental data is available) working fluids. For not-so-well-described working fluids the P–R EoS can be constructed from thermodynamic parameter estimates using simple group contribution methods. In particular, they can be used to estimate the critical state properties, ideal gas specific heat at constant pressure, and acentric factor from knowing only a working fluid's molecular structure and its NBP (normal boiling point) temperature. The simulations presented in this paper represent a large variety and number of working fluids for several different ORC applications and operating conditions. The simulations using the P–R EoS based on knowing only a working fluid's molecular structure and its NBP temperature showed comparable accuracies to simulations based on using much more complex EoS based on large amounts of experimental data.

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  • Brown, J. Steven & Brignoli, Riccardo & Daubman, Samantha, 2014. "Methodology for estimating thermodynamic parameters and performance of working fluids for organic Rankine cycles," Energy, Elsevier, vol. 73(C), pages 818-828.
    • Handle: RePEc:eee:energy:v:73:y:2014:i:c:p:818-828
    DOI: 10.1016/j.energy.2014.06.088
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    1. Liu, Wei & Meinel, Dominik & Wieland, Christoph & Spliethoff, Hartmut, 2014. "Investigation of hydrofluoroolefins as potential working fluids in organic Rankine cycle for geothermal power generation," Energy, Elsevier, vol. 67(C), pages 106-116.
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    4. Yachao Pan & Fubin Yang & Hongguang Zhang & Yinlian Yan & Anren Yang & Jia Liang & Mingzhe Yu, 2022. "Performance Prediction and Working Fluid Active Design of Organic Rankine Cycle Based on Molecular Structure," Energies, MDPI, vol. 15(21), pages 1-22, November.
    5. Wang, Xiu & Zhao, Liang & Zhang, Lihui & Zhang, Menghui & Dong, Hui, 2019. "A novel combined system for LNG cold energy utilization to capture carbon dioxide in the flue gas from the magnesite processing industry," Energy, Elsevier, vol. 187(C).
    6. Imran, Muhammad & Usman, Muhammad & Park, Byung-Sik & Yang, Youngmin, 2016. "Comparative assessment of Organic Rankine Cycle integration for low temperature geothermal heat source applications," Energy, Elsevier, vol. 102(C), pages 473-490.
    7. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Zhang, Wujie & Wang, Yan, 2022. "Evaluation of hybrid forecasting methods for organic Rankine cycle: Unsupervised learning-based outlier removal and partial mutual information-based feature selection," Applied Energy, Elsevier, vol. 311(C).
    8. Petr, Philipp & Raabe, Gabriele, 2015. "Evaluation of R-1234ze(Z) as drop-in replacement for R-245fa in Organic Rankine Cycles – From thermophysical properties to cycle performance," Energy, Elsevier, vol. 93(P1), pages 266-274.
    9. Sun, Dayu & Gao, Lijing & Wei, Ruiping & Pan, Xiaomei & Xiao, Guomin, 2023. "Mechanical vapor recompression coupling organic rankine cycle process for purification of crude biodiesel obtained by solid base-catalyzed transesterification," Energy, Elsevier, vol. 266(C).
    10. Frutiger, Jérôme & Andreasen, Jesper & Liu, Wei & Spliethoff, Hartmut & Haglind, Fredrik & Abildskov, Jens & Sin, Gürkan, 2016. "Working fluid selection for organic Rankine cycles – Impact of uncertainty of fluid properties," Energy, Elsevier, vol. 109(C), pages 987-997.
    11. Brignoli, Riccardo & Brown, J. Steven, 2015. "Organic Rankine cycle model for well-described and not-so-well-described working fluids," Energy, Elsevier, vol. 86(C), pages 93-104.

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