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Optimization of Organic Rankine Cycle using low-gwp refrigerants with a multi-objective optimization algorithm.

Number: 1223

Author(s) : YANG J., HWANG Y., YE Z., YU B., CHEN J.

Summary

Organic Rankine cycle (ORC) is classified as one of the advanced combined heat and power (CHP) technologies. It enables to recover low-grade waste heat and generates high-grade electricity. Conventional refrigerants HFCs will be phased out soon because of the significant impact on climate change. Screening of alternatives to HFCs is necessary, which is aimed to reduce the carbon dioxide emission and maintain the cycle efficiency simultaneously. For low-temperature ORC application, environmental-friendly refrigerants are proposed as potential replacements to R245fa such as R1233zd(E), R1234ze(Z), R1336mzz(Z), R1224yd(Z) and R515B. This paper is targeted to present an overall comparison of the afore-mentioned refrigerants in ORC system, where both thermodynamic performance and economic cost are taken into consideration. Furthermore, multi-objective optimization of ORC using different refrigerants is implemented based on a non-dominated sorting genetic algorithm (NSGA-II). Five decision variables are examined including evaporator outlet temperature, condensing temperature, pinch-point temperatures in heat exchangers and superheating degree. Cycle thermal efficiency and levelized electricity cost (LEC) are two objectives. The obtained Pareto-optimum frontiers are sorted by TOPSIS decision-making method to determine the optimal solution for each alternative. The proposed comprehensive evaluation method provides a reference for preliminary evaluation of working fluids in ORC.

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Details

  • Original title: Optimization of Organic Rankine Cycle using low-gwp refrigerants with a multi-objective optimization algorithm.
  • Record ID : 30027767
  • Languages: English
  • Subject: Technology, HFCs alternatives
  • Source: IIR Rankine Conference 2020.
  • Publication date: 2020/07/31
  • DOI: http://dx.doi.org/10.18462/iir.rankine.2020.1223

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