Open Access

ARTICLE

Experimental Study on the Performance of ORC System Based on Ultra-Low Temperature Heat Sources

Tianyu Zhou¹, Liang Hao¹, Xin Xu^2,3, Meng Si^2,3, Lian Zhang^2,3,*

1 College of Mechanical Engineering, Tianjin University of Science & Technology, Tianjin, 300222, China
2 School of Energy Engineering, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China
3 Tianjin “The Belt and Road” Joint Laboratory, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China

* Corresponding Author: Lian Zhang. Email:

Energy Engineering 2024, 121(1), 145-168. https://doi.org/10.32604/ee.2023.042798

Received 12 June 2023; Accepted 01 September 2023; Issue published 27 December 2023

Abstract

This paper discussed the experimental results of the performance of an organic Rankine cycle (ORC) system with an ultra-low temperature heat source. The low boiling point working medium R134a was adopted in the system. The simulated heat source temperature (SHST) in this work was set from 39.51°C to 48.60°C by the simulated heat source module. The influence of load percentage of simulated heat source (LPSHS) between 50% and 70%, the rotary valve opening (RVO) between 20% and 100%, the resistive load between 36 Ω and 180 Ω or the no-load of the generator, as well as the autumn and winter ambient temperature on the system performance were studied. The results showed that the stability of the system was promoted when the generator had a resistive load. The power generation (PG) and generator speed (GS) of the system in autumn were better than in winter, but the expander pressure ratio (EPR) was lower than in winter. Keep RVO unchanged, the SHST, the mass flow rate (MFR) of the working medium, GS, and the PG of the system increased with the increasing of LPSHS for different generator resistance load values. When the RVO was 60%, LPSHS was 70%, the SHST was 44.15°C and the resistive load was 72 Ω, the highest PG reached 15.11 W. Finally, a simulation formula was obtained for LPSHS, resistance load, and PG, and its correlation coefficient was between 0.9818 and 0.9901. The formula can accurately predict the PG. The experimental results showed that the standard deviation between the experimental and simulated values was below 0.0792, and the relative error was within ±5%.

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Keywords

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