Binary-objective optimization of latest low-GWP alternatives to R245fa for organic Rankine cycle application

Jingye Yang, Lei Gao, Zhenhong Ye, Yunho Hwang, Jiangping Chen

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Organic Rankine cycle (ORC) enables to harness waste heat resource to generate electrical power. R245fa is assumed as an appropriate working fluid for low-temperature waste heat recovery. However, strict regulations of CO2 emissions stimulate scientists to search for potential alternatives to R245fa. This paper presents a comparative analysis of various latest low-GWP refrigerants for ORC application. An energetic-economic-environmental evaluation model is established and further integrated into the non-sorted genetic algorithm (NSGA-II) for multi-objective optimization (MOO). A classic decision-making method is employed to screen out the optimal refrigerant for current study. Apart from that, the whole-year ambient conditions in Sydney are taken into consideration to screen refrigerants. Comparing the cycle thermal efficiency, R1224yd(Z) leads to 3.3% higher than R245fa. Comparing the economic cost, it saves 10.4% more than R245fa. Comparing the whole year's performance, R1224yd(Z) exhibits 11.2% higher cycle thermal efficiency than R245fa while R1234ze(Z) saves 9.85% more economic cost than R245fa. R1224yd(Z) is considered as the optimal working fluid for current ORC system. R1224yd(Z) leads to 16% higher LECTs than R245fa. Comparing the maximum LECTs, R1224yd(Z), R1234ze(Z) and R1233zd(E) is 16%, 9.2% and 13.5% higher than R245fa, respectively.

Original languageEnglish
Article number119336
JournalEnergy
Volume217
DOIs
StatePublished - Feb 15 2021
Externally publishedYes

Keywords

  • Decision-making
  • LECT
  • Multi-objective optimization
  • NSGA-II
  • Organic Rankine cycle
  • TEWI

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