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Multi-objective optimization and exergoeconomic analysis of waste heat recovery from Tehran's waste-to-energy plant integrated with an ORC unit

机译:德黑兰废热电厂与ORC装置集成后的余热回收的多目标优化和能效经济分析

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摘要

Recovery of waste heat in large industrial plants is nowadays an important topic of thermal optimization. In the present study, energy, exergy, and exergoeconomic analysis of an integrated system, Tehran's waste-to-energy power plant coupled with an organic Rankine cycle (ORC), is analyzed. Parametric study of essential parameters (moisture content, pinch point temperature differences of the HROG, steam generator's superheat temperature difference, and steam turbine inlet pressure) is performed thermodynamically. The best system performance achieved using R123 as the working fluid of ORC. After implementation of the waste-heat-recovery system into the WtE plant, with R123 the energy and exergy efficiencies increase from 17.27% to 19.51% and 14.49%-16.36%, respectively. Exergy analysis reveals that the gasifier and steam generator are the main source of exergy destruction in the overall system. Additionally, the results of single-objective optimization based on maximum exergy efficiency and minimum total product unit cost were calculated. Furthermore, multi-objective optimization based on genetic algorithm using MATLAB software is implemented to find the optimum point with respect to exergy efficiency and total product unit cost as the objective functions. The exergy efficiency and total product unit cost at the optimum point, considering multi-objective optimization, are 19.61% and 24.65 $/GJ, respectively. (C) 2018 Elsevier Ltd. All rights reserved.
机译:如今,大型工业工厂中的废热回收是热力优化的重要课题。在本研究中,分析了一个综合系统(德黑兰的垃圾发电厂和有机朗肯循环(ORC))的能源,火用和能源经济分析。通过热力学对基本参数(湿度,HROG的夹点温度差,蒸汽发生器的过热温度差和蒸汽轮机入口压力)进行参数研究。使用R123作为ORC的工作流体可获得最佳的系统性能。在WtE工厂中实施废热回收系统后,R123的能源效率和火用效率分别从17.27%提高到19.51%和14.49%-16.36%。火用分析表明,气化炉和蒸汽发生器是整个系统中火用破坏的主要来源。此外,还计算了基于最大火用效率和最小总产品单位成本的单目标优化结果。此外,基于MATLAB软件的遗传算法实现了多目标优化,以火用效率和总产品单位成本为目标函数,找到了最佳点。考虑多目标优化,在最佳点的火用效率和总产品单位成本分别为19.61%和24.65 $ / GJ。 (C)2018 Elsevier Ltd.保留所有权利。

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