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Optimization of fog inlet air cooling system for combined cycle power plants using genetic algorithm

机译:基于遗传算法的联合循环电厂雾气入口空气冷却系统优化。

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In this research paper, a comprehensive thermodynamic modeling of a combined cycle power plant is first conducted and the effects of gas turbine inlet fogging system on the first and second law efficiencies and net power outputs of combined cycle power plants are investigated. The combined cycle power plant (CCPP) considered for this study consist of a double pressure heat recovery steam generator (HRSG) to utilize the energy of exhaust leaving the gas turbine and produce superheated steam to generate electricity in the Rankine cycle. In order to enhance understanding of this research and come up with optimum performance assessment of the plant, a complete optimization is using a genetic algorithm conducted. In order to achieve this goal, a new objective function is defined for the system optimization including social cost of air pollution for the power generation systems. The objective function is based on the first law efficiency, energy cost and the external social cost of air pollution for an operational system. It is concluded that using inlet air cooling system for the CCPP system and its optimization results in an increase in the average output power, first and second law efficiencies by 17.24%, 3.6% and 3.5%, respectively, for three warm months of year. Crown Copyright (C) 2014 Published by Elsevier Ltd. All rights reserved.
机译:本文首先对联合循环发电厂进行了全面的热力学建模,并研究了燃气轮机进气雾化系统对联合循环发电厂的第一定律和第二定律效率以及净功率输出的影响。本研究考虑的联合循环发电厂(CCPP)由双压热回收蒸汽发生器(HRSG)组成,它利用离开燃气轮机的废气能量产生过热蒸汽,从而在兰金循环中发电。为了加深对这项研究的了解并提出植物的最佳性能评估,正在使用遗传算法进行全面优化。为了实现这一目标,为系统优化定义了一个新的目标函数,包括发电系统空气污染的社会成本。目标函数基于第一定律效率,能源成本和运营系统空气污染的外部社会成本。结论是,对于CCPP系统,使用进气冷却系统及其优化可在一年的三个温暖月份中平均输出功率,第一定律和第二定律效率分别提高17.24%,3.6%和3.5%。官方版权(C)2014,由Elsevier Ltd.发行。保留所有权利。

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