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Thermodynamic optimization of combined power and refrigeration cycle using binary organic working fluid

机译:使用二元有机工作流体优化动力和制冷循环的热力学优化

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摘要

A combined cycle has been proposed for the production of power and refrigeration simultaneously. The cycle can be driven by low grade heat sources such as solar, geothermal and waste heat sources. In the first part of this paper, a model has been developed to perform a parametric analysis to evaluate the effects of important parameters on the performance of the cycle, which is a combination of Rankine and absorption refrigeration cycle. Propane-decane has been used as an organic dual working fluid. In the second part, multi objective genetic algorithm is applied for Pareto approach optimization of the cycle. There are three important conflicting objectives namely, turbine work (W_t), cooling capacity (Q_c) and thermal efficiency (η_(th)) which have been selected to find the best possible combination of these performance parameters. Optimization has been carried out by varying turbine inlet pressure, superheated temperature and condenser temperature as design variables. Among optimum design parameters, a trade-off point is selected. Turbine inlet pressure, superheated temperature and condenser temperature are assumed to be 29.5 bar, 410 K and 386.6 K respectively as the values assigned to this point. Furthermore, it has been shown that some interesting and important relationships can be discovered among optimal objective functions and decision variables involved, consequently.
机译:已经提出了一种联合循环,用于同时生产动力和制冷。该循环可以由诸如太阳能,地热和废热之类的低级热源来驱动。在本文的第一部分中,开发了一个模型以执行参数分析,以评估重要参数对循环性能的影响,该模型是朗肯制冷和吸收式制冷循环的组合。丙烷癸烷已用作有机双重工作流体。在第二部分中,将多目标遗传算法应用于循环的帕累托方法优化。选择了三个重要的相互矛盾的目标,即涡轮功(W_t),冷却能力(Q_c)和热效率(η_(th)),以找到这些性能参数的最佳组合。通过改变涡轮机入口压力,过热温度和冷凝器温度作为设计变量来进行优化。在最佳设计参数中,选择一个折衷点。涡轮入口压力,过热温度和冷凝器温度分别假定为29.5 bar,410 K和386.6 K,作为分配给该点的值。此外,已经表明,因此可以在最佳目标函数和决策变量之间发现一些有趣且重要的关系。

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