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Optimization of the boiler pressure and working fluid in a binary organic Rankine cycle for different heat sources

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  • Kazemiani-Najafabadi, Parisa
  • Amiri Rad, Ehsan

Abstract

ORC is a common power generation system that is driven by different heat source temperatures. Boiler pressure and working fluid are effective factors on the cycle performance. The use of mixtures can improve performance. Selecting a proportionate mixture is a great challenge. In this paper, the waste heat recovered from an industrial complex was utilized to generate power by an ORC. A large number of binary mixtures were considered as the working fluid. Based on the optimization algorithms such as Genetic Algorithm and Particle Swarm Optimization, the effects of various components and their concentrations in the mixture and boiler pressure were simultaneously optimized. The optimal conditions including components of the binary mixture, mixture concentration, and boiler pressure were presented for different heat source temperatures in the range of 80–190 °C. R32-R290 with a concentration of 0.69–0.31 at the pressure of 37.06 bar had the highest net power and exergy efficiency for heat source temperature of 80 °C. For temperatures of 100 °C and 130 °C, R290-R143a and R290-R152a with concentrations of 0.2–0.8 and 0.57–0.43 were the most appropriate mixtures at their optimal pressures, respectively. The optimum binary mixtures for heat source temperatures of 160 °C and 190 °C were R600-R21 (0.31–0.69) and R600-R245fa (0.33–0.67), respectively.

Suggested Citation

  • Kazemiani-Najafabadi, Parisa & Amiri Rad, Ehsan, 2022. "Optimization of the boiler pressure and working fluid in a binary organic Rankine cycle for different heat sources," Energy, Elsevier, vol. 238(PA).
  • Handle: RePEc:eee:energy:v:238:y:2022:i:pa:s0360544221019198
    DOI: 10.1016/j.energy.2021.121671
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    2. Zhu, Meng & Zhou, Jing & Chen, Lei & Su, Sheng & Hu, Song & Qing, Haoran & Li, Aishu & Wang, Yi & Zhong, Wenqi & Xiang, Jun, 2022. "Economic analysis and cost modeling of supercritical CO2 coal-fired boiler based on global optimization," Energy, Elsevier, vol. 239(PD).

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