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Multi-objective optimization of compression refrigeration cycle of Unit 132 South Pars refineries

机译：南帕尔斯132号炼油厂压缩制冷循环的多目标优化

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The purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. Studied refrigeration cycle is compression refrigeration cycle of unit 132 Third refineries in south pars that provide chilled water for cooling refinery equipment's. Cycle will be performed by the genetic algorithm optimization. Thermodynamic purpose of the cycle Expressed by minimization of Exergy destruction or maximization or coefficient of performance (C.O.P), economic purpose of the cycle Expressed by minimization of cold water production cost by TRR method and environmental purpose of the cycle Expressed by minimization of NOx, CO2 and CO Which is produced by power consumption. Combination of objectives and decision variables with suitable engineering and physical constraints makes a set of the MINLP optimization problem. In EES software. Optimization programming is performed using NSGA-II algorithm. Four optimization scenarios including the thermodynamic single-objective, the economic single-objective, environmental single-objective by power electricity consumption and multi-objective optimizations are performed. The output of the multi-objective optimization is a Pareto frontier that yields a set of optimal points that the final optimal solution has been selected using two decision-making approaches including the LINMAP and TOPSIS methods.. It was shown that the best results in comparison to the simple cycle reduction in Exergy destruction from 264.8 kW to 127.6 kW(Increased coefficient of performance from 3.872 to 7.088), reduction in cold water production cost from 117.5 dollar/hour to 87.19 dollar/hour and reduction in NOx emission from 4958 kg/year to 2645 kg/year.
机译：本文的目的是通过优化循环的所有组件（包括热交换器，空气冷凝器，蒸发器和过热器）来对制冷循环进行多目标优化。研究的制冷循环是位于南部par的132号第三精炼厂的压缩制冷循环，为精炼设备的冷却提供冷冻水。循环将通过遗传算法优化来执行。循环的热力学目的是通过减少火用破坏或最大化或性能系数（COP）来表达的，循环的经济目的是通过用TRR方法使冷水生产成本最小化来表达的，循环的环境目的是通过减少NOx，CO2来表达的以及由功耗产生的CO。将目标和决策变量与适当的工程和物理约束相结合，将产生一组MINLP优化问题。在EES软件中。使用NSGA-II算法执行优化编程。进行了热动力单目标，经济单目标，环境单目标（用电功耗）和多目标优化四个优化方案。多目标优化的输出是一个Pareto边界，它产生一组最优点，该最优点是使用LINMAP和TOPSIS方法这两种决策方法选择的。简化了将“火用”破坏的简单周期从264.8 kW降低到127.6 kW（性能系数从3.872降低到7.088），将冷水生产成本从117.5美元/小时降低到87.19美元/小时并将NOx排放量从4958 kg /小时降低到年至2645公斤/年。

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