4E analysis and multi-objective optimization of an integrated MCFC (molten carbonate fuel cell) and ORC (organic Rankine cycle) system

• Published in: Energy (Oxford) 2015-03, Vol.82, p.650-663
• Main Authors: Haghighat Mamaghani, Alireza, Najafi, Behzad, Shirazi, Alec, Rinaldi, Fabio
• Format: Article
• Language: English
• Subjects: Computational efficiency; Computing time; Cost engineering; Economic; Economic analysis; Exergy; Gas turbine; Mathematical models; Molten carbonate fuel cell; Multi-objective optimization; Optimization; Organic Rankine cycle; Rankine cycle
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2015.01.074

This article proposes a novel hybrid system, integrating high temperature MCFC-GT (molten carbonate fuel cell-gas turbine) and ORC (organic Rankine cycle), which provides the possibility to achieve high electrical and exergetic efficiencies owing to the subsequent electrical power output in the bottoming cycle. After developing a mathematical model, comprehensive energetic, exergetic, economic and environmental evaluations (4E analysis) are performed and a multi-objective optimization method is utilized to find optimal solutions while considering the exergetic and economic objectives simultaneously. Two conflicting objectives including total exergetic efficiency and total cost rate of the system in multi-objective optimization are taken into account to build a set of Pareto optimal solutions. This optimum solution results in the exergetic efficiencies of 35.6%, 44.3%, and 54.9% for the fuel cell system, ORC cycle and the whole hybrid system respectively, while the total cost of the plant is 0.294 M€ per year. The study reveals that introducing the ORC bottoming cycle leads to about 5% improvement in the exergetic efficiency of the proposed plant. Furthermore, a sensitivity analysis is conducted to investigate the effect of variation in economic parameters, the fuel unit cost and interest rate, on the Pareto optimal solutions. •An exergetic-economic-environmental analysis on an MCFC-GT-ORC system was conducted.•Exergetic efficiency and total cost rate were selected as two conflicting objectives.•Multi-objective optimization was employed to obtain a set of Pareto front solutions.•A sensitivity of Pareto front solutions was investigated to economic parameters.