Novel hybrid two-stage alkali metal thermoelectric converter and thermally regenerative electrochemical cycle to exploit waste heat of solid oxide fuel cell: Performance assessment and optimization

An innovative combination of a two-stage alkali metal thermoelectric converter (TAMTEC), and thermally regenerative electrical cycle (TREC) is employed to utilize the high-quality heat dissipated from solid oxide fuel cell (SOFC) for further electricity production. The superiority and effectiveness of the SOFC-TAMTEC-TREC system are verified compared to existing SOFC-based hybrid systems and sole SOFC. The performance of the system based on energy, exergy, and economic indicators is evaluated by varying the main design parameters. Parametric assessment demonstrates that the SOFC-TAMTEC-TREC system can reach the maximum power density of 12126 W m −2 with energy and exergy efficiencies of 47.13% and 50.46% as TAMTEC proportional constant increases to 10 7.5 m 2 and rising SOFC pore and gain diameters to 3.77 × 10 −6 m and 2.5 × 10 −6 m, respectively reduce the cost rate density of system by 3.55 $ h −1 m −2 . Furthermore, to achieve the maximum power density and exergy efficiency, and minimum cost rate density, NSGA-III multi-criteria optimization, and decision-making techniques are conducted. Outcomes indicate that Shannon entropy leads to the maximum power density of 8597.2 W m −2 with a 35.94% enhancement relative to a single SOFC and 1 $ h −1 m −2 increment in cost rate density of the hybrid system, while LINMAP and TOPSIS ascertain the minimum increase in the cost rate density by 0.6 $ h −1 m −2 with 31.04% improvement in power density relative to single SOFC. • A TAMTEC-TREC hybrid system is integrated with an SOFC for extra power production. • Thermodynamic and exergoeconomic indicators of the hybrid system are analyzed. • Effects of design parameters on the performance of the hybrid system are revealed. • The hybrid system is a promising option for highly efficient power production. • NSGA-III multi-criteria optimization is applied to identify the optimum performance.