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Optimization of the Variable Refrigerant Flow Systems by use of Genetic Algorithm and Energy, Exergy, and Economic Analysis for Three Coolant Fluids

机译:通过使用遗传算法和能量,漏洞和三种冷却剂流体的经济分析来优化可变制冷剂流量系统

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The current study aimed at investigation of the Variable Refrigerant Flow (VRF). Energy, exergy, and economic model for R11, R22, and R134a refrigerants. The genetic algorithm was used for optimization of the cycle. The objective functions in the current study were the second law efficiency and cooling cost. The cooling cost was a new economic function that was defined in this paper for the first time. Results showed that the highest Coefficient of Performance (COP) and second law’s efficiency as well as the lowest cooling cost and exergy loss belonged to the refrigerant R134a, and second and third to it were R11 and R22. The optimum values of condenser pressure and evaporators 1, 2, and 3 for the refrigerant R134a were 799.7, 706.2, 925.2, and 23122 (kPa), and the mass discharge of the evaporators 1 and 2, was 0.1 and 0.072 (kg/s).
机译:目前的研究旨在调查可变制冷剂流量(VRF)。 R11,R22和R134A制冷剂的能量,漏洞和经济模式。遗传算法用于优化循环。目前研究中的客观职能是第二律效率和冷却成本。冷却成本是本文首次定义的新经济功能。结果表明,最高的性能系数(COP)和第二种法律的效率以及最低的冷却成本和丧失损失属于制冷剂R134A,第二和第三个是R11和R22。用于制冷剂R134a的冷凝器压力和蒸发器1,2和3的最佳值为799.7,706.2,925.2和23122(KPA),蒸发器1和2的质量排放为0.1和0.072(kg / s )。

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