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Multi-objective optimization of compression refrigeration cycle of Unit 132 South Pars refineries | ||
| Energy Equipment and Systems | ||
| مقاله 6، دوره 4، شماره 2، اسفند 2016، صفحه 147-160 اصل مقاله (1.24 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ees.2016.59550 | ||
| نویسندگان | ||
| Ali Reza Sheibani Tezerji* ؛ Mohammad Mehdi Keshtkar | ||
| Mechanical Engineering Department, Islamic Azad University, Kerman Branch, Iran | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Compression Refrigeration Cycle؛ Multi-Objective Optimization؛ Genetic Algorithm (GA)؛ TOPSIS and LINMAP Decision-Making | ||
| مراجع | ||
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