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Thermodynamic performance optimization of a combined power/cooling cycle

机译:电力/制冷循环的热力学性能优化

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摘要

A combined thermal power and cooling cycle has already been proposed in which thermal energy is used to produce work and to generate a sub-ambient temperature stream that is suitable for cooling applications. The cycle uses ammonia-water mixture as working fluid and is a combination of a Rankine cycle and absorption cycle. The very high ammonia vapor concentration, exiting turbine under certain operating conditions, can provide power output as well as refrigeration. In this paper, the goal is to employ multi-objective algorithms for Pareto approach optimization of thermodynamic performance of the cycle. It has been carried out by varying the selected design variables, namely, turbine inlet pressure (P_h), superheater temperature (T_(superheat)) and condenser temperature (T_(condensor). The important conflicting thermodynamic objective functions that have been considered in this study are turbine work (w_T), cooling capacity (q_(cool)) and thermal efficiency (η_(th)) of the cycle. It is shown that some interesting and important relationships among optimal objective functions and decision variables involved in the combined cycle can be discovered consequently. Such important relationships as useful optimal design principles would have not been obtained without the use of a multi-objective optimization approach.
机译:已经提出了组合的热力和冷却循环,其中热能被用来产生功并产生适合于冷却应用的低于环境的温度流。该循环使用氨水混合物作为工作流体,并且是朗肯循环和吸收循环的组合。在某些工况下离开涡轮机的氨气浓度很高,可以提供功率输出和制冷。在本文中,目标是采用多目标算法来优化循环热力学性能的帕累托方法。通过改变选定的设计变量,即涡轮机入口压力(P_h),过热器温度(T_(过热))和冷凝器温度(T_(冷凝器),可以实现这一点。研究了循环的涡轮功(w_T),冷却能力(q_(cool))和热效率(η_(th)),结果表明,联合循环中涉及的最佳目标函数和决策变量之间存在一些有趣且重要的关系如果不使用多目标优化方法,就不会获得有用的最佳设计原则这样的重要关系。

著录项

  • 来源
    《Energy Conversion & Management》 |2010年第1期|204-211|共8页
  • 作者单位

    Department of Mechanical Engineering, University of Guilan, PO Box 3756, Rasht, Iran;

    Department of Mechanical Engineering, University of Guilan, PO Box 3756, Rasht, Iran;

    Department of Mechanical Engineering, University of Guilan, PO Box 3756, Rasht, Iran;

    Intelligent-based Experimental Mechanics Center of Excellence, School of Mechanical Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    ammonia-water; thermal power; cooling cycle; multi-objective optimization;

    机译:氨水火电;冷却周期多目标优化;

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