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Thermodynamic analysis and optimization of a geothermal Kalina cycle system using Artificial Bee Colony algorithm

机译:基于人工蜂群算法的地热卡利纳循环系统热力学分析与优化

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In this paper, thermodynamic analysis is carried out for a geothermal Kalina cycle employed in Husavic power plant. Afterwards, the optimum operating conditions in which the cycle is at its best performance are calculated. In order to reach the optimum thermal and exergy efficiencies of the cycle, Artificial Bee Colony (ABC) algorithm, a new powerful multi-objective and multi-modal optimization algorithm, is conducted. Regarding the mechanism of ABC algorithm, convergence speed and precision of solutions have been remarkably improved when compared to those of GA, PSO and DE algorithms. Such a relative improvement is indicated by a limit parameter and declining probability of premature convergence. In this research, exergy efficiency including chemical and physical exergies and thermal efficiency are chosen as the objective functions of ABC algorithm where optimum values of the efficiencies for the Kalina cycle are found to be 48.18 and 2036%, respectively, while the empirical thermal efficiency of the cycle is about 14%. At the optimum thermal and exergy efficiencies, total exergy destruction rates are respectively 4.17 and 3.48 MW. Finally, effects of the separator inlet pressufe, temperature, basic ammonia mass fraction and mass flow rate on the first and second law efficiencies are investigated. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文对胡萨维奇电厂采用的地热卡利纳循环进行了热力学分析。然后,计算出循环处于最佳状态的最佳运行条件。为了达到循环的最佳热效率和火用效率,进行了人工蜂群算法(ABC),这是一种新的强大的多目标多模式优化算法。在算法方面,与GA,PSO和DE算法相比,ABC算法的收敛速度和精度都有了显着提高。这样的相对改善由极限参数和过早收敛的概率下降表示。在这项研究中,选择包括化学和物理能用的热能效率和热效率作为ABC算法的目标函数,其中发现Kalina循环效率的最佳值分别为48.18和2036%,而经验热效率为周期约为14%。在最佳的热效率和火用效率下,总火用破坏率分别为4.17和3.48 MW。最后,研究了分离器入口压力,温度,基本氨质量分数和质量流量对第一定律和第二定律效率的影响。 (C)2015 Elsevier Ltd.保留所有权利。

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