Multi-objective optimization of a dual energy-driven solid oxide fuel cell-based power plant

Regarding the ability of solid oxide fuel cell-based energy conversion systems and modifying their design structure, the current study comprehensively investigates the potential of empowering a novel integrated solid oxide fuel cell-based power plant via liquefied natural gas together with geothermal energy, addressing this matter. Likewise, the newly designed system embraces an efficient design through multi-heat recovery based on two energy sources. In this regard, the sensitivity analysis and optimization (using a genetic algorithm) methods are utilized to assess the proposed system, taking into account the energy, exergy, exergo-economic, and environmental perspectives. The results indicate that as the current density of the cell increases, the net output power and energy efficiency of the system enhance. Among considered decision variables, geothermal water temperature and turbine pressure have the severest impacts on the output power and the corresponding unit cost. Moreover, optimization results reveal that the air heat exchanger and turbine have the highest exergy destruction costs with values of 4800 $/year and 4500 $/year, respectively. Furthermore, it is found that the emissions' cost (0.000154 $/s) would be around 2% lower when the system is optimized by minimizing unit product cost rather than maximizing the energy or exergy efficiency of the system.