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Exergoeconomic optimization of a combined cycle power plant's bottoming cycle using organic working fluids

机译:使用有机工质对联合循环发电厂的底部循环进行能效经济优化

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One of the measures to reduce carbon dioxide emissions and increase energy efficiency in a combined cycle power plant is the improving of its thermodynamic efficiency by optimizing the heat utilization s study, a mathematical model of the bottoming cycle of a combined cycle power plant was developed in Matlab. The heat recovery steam generator, which is a crucial element of the bottoming cycle, is modeled as a heat exchanger network. It consists of multiple pressure levels and a reheater that uses organic working fluids in the lower pressure levels. The mathematical model provides the possibility that the heat exchangers in each pressure level could be in parallel and serial arrangements. An exergoeconomic optimization was conducted, where the optimization variables comprised the heat exchanger layout and the operating parameters of the working fluid in each pressure level. The objective of the optimization was to minimize the sum of the cost of exergy destruction in the bottoming cycle and investment costs. The genetic algorithm and gradient optimization methods were used as optimization tools. The results show that lower cost of exergy destruction can be achieved by optimizing the heat exchanger layout and using organic fluids in the lower pressure levels of a heat recovery steam generator. This research work addresses a gap in the literature by taking into account the heat exchanger layout, optimization parameters, and organic fluids while optimizing a bottoming cycle, which is of essential importance.
机译:联合循环电厂减少二氧化碳排放和提高能源效率的措施之一是通过优化热利用来提高其热力学效率,并在此基础上开发了联合循环电厂底部循环的数学模型。 Matlab。作为底部循环的关键要素的热回收蒸汽发生器被建模为热交换器网络。它由多个压力等级和一个在较低压力等级使用有机工作流体的再热器组成。数学模型提供了在每个压力水平下热交换器可以并联和串联布置的可能性。进行了能效经济优化,其中优化变量包括热交换器布局和每个压力水平下工作流体的运行参数。优化的目的是最小化自下而上周期的火用破坏成本和投资成本之和。遗传算法和梯度优化方法被用作优化工具。结果表明,通过优化热交换器布局并在热回收蒸汽发生器的较低压力水平下使用有机流体,可以实现较低的火用破坏成本。这项研究工作通过考虑换热器布局,优化参数和有机流体,同时优化了底部循环,解决了文献中的空白,这至关重要。

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