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Multi-objective performance optimization of irreversible molten carbonate fuel cell-Stirling heat engine-reverse osmosis and thermodynamic assessment with ecological objective approach
Mohammad H. Ahmadi, 1 Mohammad Sameti, 2 Seyed M. Pourkiaei, 3 Tingzhen Ming, 4 Fathollah Pourfayaz, 3 Ali J. Chamkha, 5 Hakan F. Oztop 6 , Mohammad Ali Jokar 3
1  Faculty of Mechanical Engineering; Shahrood University of Technology; Shahrood Iran
2  Faculty of Engineering and Computer Sciences (ENCS); Concordia University; Montreal Quebec Canada
3  Department of Renewable Energy and Environmental Engineering; University of Tehran; Tehran Iran
4  School of Civil Engineering and Architecture; Wuhan University of Technology; Wuhan China
5  Mechanical Engineering Department; Prince Sultan Endowment for Energy and Environment; Prince Mohammad Bin Fahd University; Al-Khobar Saudi Arabia
6  Department of Mechanical Engineering, Technology Faculty; Fırat University; Elazig Turkey

Published: 12 November 2018 by Wiley in Energy Science & Engineering
Wiley, Volume 6; 10.1002/ese3.252
Abstract: This paper aims to investigate a hybrid cycle consisting of a molten carbonate fuel cell (FC) and a Stirling engine which, by connecting to a seawater reverse osmosis desalination unit, provides fresh water. First, a parametric evaluation is performed to study the effect of some key parameters, including the current density and the working temperature of the FC and the thermal conductance between the working substance and the heat reservoirs in the Stirling engine, on the objective functions. The objective functions include the energy efficiency, the exergy destruction rate density, the fresh water production rate, and the ecological function density. After investigating each double combination of these objective functions, two scenarios are defined in quest to concurrently optimize three functions together. The first scenario aims to optimize the energy efficiency, the exergy destruction rate density, and the fresh water production rate; and the second scenario attempts to optimize the energy efficiency, the fresh water production rate, and the ecological function density. A multi‐objective evolutionary algorithm joined with the nondominated sorting genetic algorithm (NSGA‐II) approach is employed to obtain Pareto fronts in each case scenario. In order to ascertain final solutions between Pareto fronts, three fast and robust decision‐making methods are employed including TOPSIS, LINMAP, and Fuzzy. Finally, a sensitivity analysis is conducted to critically analyze the performance of the system.
Keywords: Stirling engine, molten carbonate fuel cell, Reverse Osmosis Desalination, Multi‐Objective Optimization, multi‐disciplinary approach
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