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Designed binary mixtures for subcritical organic Rankine cycles based on multiobjective optimization

机译：基于多目标优化设计亚临界有机朗肯循环的二元混合物

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摘要

The use of binary zeotropic mixtures as working fluids applied to Organic Rankine Cycles (ORCs) is investigated in this paper. In total, six (6) hydrocarbons and (2) hydrofluorocarbons are considered, leading to twenty-eight (28) possible binary combinations. The mixtures were tested with a basic Rankine cycle while using the heat source temperature as independent variable, which assumed six different values, ranging from 80 degrees C to 180 degrees C, in steps of 20 degrees C. The simulations aimed to identify the ideal mixtures that maximized the net power and exergetic efficiency, and minimized the heat exchanger's global conductance for a given temperature of the heat source. The optimization process relied on a genetic algorithm and the selection of the best mixtures, on a non-dominated sorting method (NDS), which returned Pareto fronts gathering the best solutions. While no one specific ideal mixture was identified, the results showed that the range of the so-called ideal mixtures narrows as the heat source temperature increases, with mixtures including fluids like R245fa and pentane being good options, whereas at low temperature, a larger number of fluid mixtures perform well. Finally, a scale analysis is proposed and shows that the maximal net power varies linearly with a Number of Transfer Units (NTU) factor while its slope depends on the heat source temperature. The latter analysis is compared with the results obtained with the Pareto front and NDS, showing that both sets of results agree well while correlated by a single constant for the entire temperature range covered in the present study.
机译：本文研究了使用二元共沸混合物作为有机朗肯循环（ORC）的工作流体。总共考虑了六（6）种碳氢化合物和（2）氢氟碳化合物，导致二十八（28）种可能的二元组合。使用基本兰金循环对混合物进行测试，同时使用热源温度作为独立变量，假设温度以80摄氏度至180摄氏度为六个不同值（以20摄氏度为步长）。模拟旨在确定理想的混合物在给定的热源温度下，可以最大程度地提高净功率和能量效率，并最小化热交换器的整体电导率。优化过程依赖于遗传算法和最佳混合物的选择，以及非主导的排序方法（NDS），这使Pareto前沿返回了最佳解决方案。尽管没有发现一种特定的理想混合物，但结果表明，随着热源温度的升高，理想混合物的范围会缩小，其中包括R245fa和戊烷等流体的混合物是不错的选择，而在低温下，理想混合物的数量更大的液体混合物表现良好。最后，提出了规模分析，结果表明，最大净功率随传热单位数（NTU）因子线性变化，而其斜率取决于热源温度。将后面的分析与通过Pareto前沿和NDS获得的结果进行比较，表明两组结果在本研究覆盖的整个温度范围内均一致，同时与单个常数相关。

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