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

被引:157
作者
Behzadi, Amirmohammad [1 ]
Gholamian, Ehsan [1 ]
Houshfar, Ehsan [1 ]
Habibollahzade, Ali [1 ]
机构
[1] Univ Tehran, Sch Mech Engn, Coll Engn, POB 11155-4563, Tehran, Iran
关键词
WtE power plant; ORC; Multi-objective optimization; Exergoeconomic; Gasification; ORGANIC RANKINE-CYCLE; LOW-GRADE HEAT; MULTI OBJECTIVE OPTIMIZATION; PARAMETRIC OPTIMIZATION; BIOMASS GASIFICATION; PERFORMANCE ANALYSIS; EXERGETIC ANALYSIS; STRAW COMBUSTION; KALINA CYCLE; POWER-PLANT;
D O I
10.1016/j.energy.2018.07.074
中图分类号
O414.1 [热力学];
学科分类号
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.
引用
收藏
页码:1055 / 1068
页数:14
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