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Improved correlations for working fluid properties prediction and their application in performance evaluation of sub-critical Organic Rankine Cycle

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  • Luo, Xianglong
  • Wang, Yupeng
  • Liang, Junwei
  • Qi, Ji
  • Su, Wen
  • Yang, Zhi
  • Chen, Jianyong
  • Wang, Chao
  • Chen, Ying

Abstract

The utilization of renewable energy resources (e.g., solar energy, geothermal energy, and biomass energy) or recovery of waste heat (e.g., industrial waste heat and engine waste heat) is an effective way to deal with current energy and environmental problems. Organic Rankine cycle (ORC) is a promising technology among multiple heat-to-power methods. Working fluid is a key component of an ORC to complete the heat-to-power process and the screening of the existing working fluids and the design of new working fluids have been always the focus of the ORC research. Computer-aided molecular design (CAMD)-based working fluid screening simultaneously with the process optimization is an essential and promising way of improve the ORC performance. In the CAMD process, the prediction accuracy of working fluid properties is significant for the accurate working fluid screening, working fluid design, and cycle performance evaluation. In this study, an artificial neural network (ANN)-based property prediction method is developed and the property correlations with improved accuracy for critical pressure (Pc) and normal boiling temperature (Tb) are achieved. Based on the proposed prediction methods and correlations, a systematic methodology is proposed for fast performance evaluation of ORC using existing or new fluids. The proposed property prediction method, property correlations and ORC performance evaluation method are validated by comparing with REFPROP 9.1 database and/or previous methods. The validation results show that the absolute average deviation (AAD) of existing working fluid thermophysical properties calculated using the proposed method is significantly reduced. The AAD of the thermal efficiency of the cycle using existing working fluid calculated using the proposed method is 26%–81% lower than those results achieved using the previous methods. In addition, the calculation time using the proposed method for ORC performance evaluation is 0.28s which is several orders of magnitude lower than those of the previous methods.

Suggested Citation

  • Luo, Xianglong & Wang, Yupeng & Liang, Junwei & Qi, Ji & Su, Wen & Yang, Zhi & Chen, Jianyong & Wang, Chao & Chen, Ying, 2019. "Improved correlations for working fluid properties prediction and their application in performance evaluation of sub-critical Organic Rankine Cycle," Energy, Elsevier, vol. 174(C), pages 122-137.
  • Handle: RePEc:eee:energy:v:174:y:2019:i:c:p:122-137
    DOI: 10.1016/j.energy.2019.02.124
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    1. Wang, Enhua & Yu, Zhibin & Zhang, Hongguang & Yang, Fubin, 2017. "A regenerative supercritical-subcritical dual-loop organic Rankine cycle system for energy recovery from the waste heat of internal combustion engines," Applied Energy, Elsevier, vol. 190(C), pages 574-590.
    2. Saleh, Bahaa & Koglbauer, Gerald & Wendland, Martin & Fischer, Johann, 2007. "Working fluids for low-temperature organic Rankine cycles," Energy, Elsevier, vol. 32(7), pages 1210-1221.
    3. White, M.T. & Oyewunmi, O.A. & Chatzopoulou, M.A. & Pantaleo, A.M. & Haslam, A.J. & Markides, C.N., 2018. "Computer-aided working-fluid design, thermodynamic optimisation and thermoeconomic assessment of ORC systems for waste-heat recovery," Energy, Elsevier, vol. 161(C), pages 1181-1198.
    4. Liu, Qiang & Duan, Yuanyuan & Yang, Zhen, 2014. "Effect of condensation temperature glide on the performance of organic Rankine cycles with zeotropic mixture working fluids," Applied Energy, Elsevier, vol. 115(C), pages 394-404.
    5. 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.
    6. Oyewunmi, Oyeniyi A. & Taleb, Aly I. & Haslam, Andrew J. & Markides, Christos N., 2016. "On the use of SAFT-VR Mie for assessing large-glide fluorocarbon working-fluid mixtures in organic Rankine cycles," Applied Energy, Elsevier, vol. 163(C), pages 263-282.
    7. 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.
    8. 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.
    9. Wang, E.H. & Zhang, H.G. & Fan, B.Y. & Ouyang, M.G. & Zhao, Y. & Mu, Q.H., 2011. "Study of working fluid selection of organic Rankine cycle (ORC) for engine waste heat recovery," Energy, Elsevier, vol. 36(5), pages 3406-3418.
    10. Palma-Flores, Oscar & Flores-Tlacuahuac, Antonio & Canseco-Melchorb, Graciela, 2016. "Simultaneous molecular and process design for waste heat recovery," Energy, Elsevier, vol. 99(C), pages 32-47.
    11. Lecompte, Steven & Huisseune, Henk & van den Broek, Martijn & Vanslambrouck, Bruno & De Paepe, Michel, 2015. "Review of organic Rankine cycle (ORC) architectures for waste heat recovery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 448-461.
    12. Xia, Guanghui & Sun, Qingxuan & Cao, Xu & Wang, Jiangfeng & Yu, Yizhao & Wang, Laisheng, 2014. "Thermodynamic analysis and optimization of a solar-powered transcritical CO2 (carbon dioxide) power cycle for reverse osmosis desalination based on the recovery of cryogenic energy of LNG (liquefied n," Energy, Elsevier, vol. 66(C), pages 643-653.
    13. 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.
    14. Rayegan, R. & Tao, Y.X., 2011. "A procedure to select working fluids for Solar Organic Rankine Cycles (ORCs)," Renewable Energy, Elsevier, vol. 36(2), pages 659-670.
    15. Chang, Huawei & Wan, Zhongmin & Zheng, Yao & Chen, Xi & Shu, Shuiming & Tu, Zhengkai & Chan, Siew Hwa & Chen, Rui & Wang, Xiaodong, 2017. "Energy- and exergy-based working fluid selection and performance analysis of a high-temperature PEMFC-based micro combined cooling heating and power system," Applied Energy, Elsevier, vol. 204(C), pages 446-458.
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    Cited by:

    1. Qiang Liu & Ran Chen & Xinliu Yang & Xiao Xiao, 2023. "Thermodynamic Analyses of Sub- and Supercritical ORCs Using R1234yf, R236ea and Their Mixtures as Working Fluids for Geothermal Power Generation," Energies, MDPI, vol. 16(15), pages 1-22, July.
    2. Zhan, Taotao & Chen, Yuhang & Dong, Ao & He, Maogang & Zhang, Ying, 2023. "Intrinsic-group-contribution PC-SAFT and its application in performance analysis of high-temperature organic Rankine cycle with siloxanes and alkanes," Energy, Elsevier, vol. 278(PA).
    3. 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).
    4. Luo, Xianglong & Wei, Youxing & Qiu, Guanfu & Liang, Yingzong & Chen, Jianyong & Yang, Zhi & Wang, Chao & Chen, Ying, 2020. "Simultaneous design and off-design operation optimization of a waste heat-driven organic Rankine cycle using a multi-period mathematical programming method," Energy, Elsevier, vol. 213(C).
    5. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Xing, Chengda & Yao, Baofeng & Wang, Yan, 2022. "An outlier removal and feature dimensionality reduction framework with unsupervised learning and information theory intervention for organic Rankine cycle (ORC)," Energy, Elsevier, vol. 254(PB).
    6. Mohan, Sooraj & Dinesha, P. & Campana, Pietro Elia, 2022. "ANN-PSO aided selection of hydrocarbons as working fluid for low-temperature organic Rankine cycle and thermodynamic evaluation of optimal working fluid," Energy, Elsevier, vol. 259(C).

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    Keywords

    ANN; GCM; CAMD; ORC; Working fluid;
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