Multi-objective optimization and grey relational analysis on configurations of organic Rankine cycle

Y. Z. Wang, J. Zhao, Y. Wang, Q. S. An*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

74 Citations (Scopus)

Abstract

Concerning the comprehensive performance of organic Rankine cycle (ORC), comparisons and optimizations on 3 different configurations of ORC (basic, regenerative and extractive ORCs) are investigated in this paper. Medium-temperature geothermal water is used for comparing the influence of configurations, working fluids and operating parameters on different evaluation criteria. Different evaluation and optimization methods are adopted in evaluation of ORCs to obtain the one with the best comprehensive performance, such as exergoeconomic analysis, bi-objective optimization and grey relational analysis. The results reveal that the basic ORC performs the best among these 3 ORCs in terms of comprehensive thermodynamic and economic performances when using R245fa and driven by geothermal water at 150 °C. Furthermore, R141b shows the best comprehensive performance among 14 working fluids based on the Pareto frontier solutions without considering safe factors. Meanwhile, R141b is the best among all 14 working fluids with the optimal comprehensive performance when regarding all the evaluation criteria as equal by using grey relational analysis.

Original languageEnglish
Pages (from-to)1355-1363
Number of pages9
JournalApplied Thermal Engineering
Volume114
DOIs
Publication statusPublished - 5 Mar 2017
Externally publishedYes

Keywords

  • Exergoeconomic analysis
  • Geothermal resource
  • Grey relational analysis
  • Multi-objective optimization
  • Organic Rankine cycle

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