Multi-objective optimization and decision analysis of a system based on biomass fueled SOFC using couple method of entropy/VIKOR

A power generation system including solid oxide fuel cell (SOFC), gasifier, and high-temperature sodium heat pipes was modeled using the Lagrange method of undetermined multipliers. The model validation was performed in comparison with the data available in the literature. The results showed that the presented model had a high validity. The parametric analysis showed that there was an optimum value for current density to achieve the highest net power but the exergy efficiency was reduced gradually with the current density. Response surface methodology (RSM) was utilized for multi-objective optimization purpose. The analysis of variance (ANOVA) was performed and different regression models with high validity were presented for power (R-2 = 93.40%) and exergy efficiency (R-2 = 96.22%). The one-objective optimization was performed using the interaction effect of parameters derived by ANOVA. The multi-objective optimization results indicated that the optimum power was achieved at relatively low exergy efficiencies and the optimum exergy efficiency was accompanied by low powers. A stepwise multi-objective optimization procedure was conducted and an optimum region was recognized. The performance of the system was assessed from energy, exergy, and environmental viewpoints for different biomasses including pine sawdust, groundnut shell, rice straw, rice husk, eucalyptus, sunflower shell, and sugarcane bagasse. Multi-criteria decision making (MCDM) analysis was implemented in order to select the biomass with the best performance. The cold gas efficiency, energy efficiency, exergy destruction rate, CO2 emission, and fuel flow rate were selected as different criteria. The MCDM results revealed that eucalyptus had the best performance.