How to rapidly predict the performance of ORC: Optimal empirical correlation based on cycle separation

Jun Zhao, Likai Hu, Yongzhen Wang*, Hongmei Yin, Shuai Deng, Wenjia Li, Yanping Du, Qingsong An

*此作品的通讯作者

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摘要

This paper establishes an empirical correlation based on the separability of thermodynamic cycle, which could characterize the thermodynamic performance of organic Rankine cycle (ORC), resembling heat transfer empirical correlation. In this research, we found that the thermal efficiency, exergy efficiency and net output power of ORC can be expressed by the heat source characteristics (Ths, heat source temperature) and two key physical properties of working fluids (Tcri, critical temperature; ω acentric factor). That is, ΩORC,opt=Cwf·Tcrim·ωwfn·Thso.Taking subcritical ORC as an example, the empirical correlation of the optimal power generation and its corresponding optimal evaporation temperature could be provided through proposed method. The results reveal that the empirical correlations have the high prediction accuracies (the determination coefficient R2 are both about 0.97) when comparing with traditional numerical calculation. The application of correlation could avoid the complex process of iteration for calculation convergence and calling properties, so it is more convenient and faster than traditional methods when used to predict the performance of ORC or to select and design the working fluids.

源语言英语
页(从-至)86-93
页数8
期刊Energy Conversion and Management
188
DOI
出版状态已出版 - 15 5月 2019
已对外发布

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Zhao, J., Hu, L., Wang, Y., Yin, H., Deng, S., Li, W., Du, Y., & An, Q. (2019). How to rapidly predict the performance of ORC: Optimal empirical correlation based on cycle separation. Energy Conversion and Management, 188, 86-93. https://doi.org/10.1016/j.enconman.2019.02.095