Predictive Modeling and Optimization of Biogas Reforming and Proton-Conducting SOFCs Integrated System

Abstract

In this study, the power generation performance of a proton-conducting solid oxide fuel cell (H-SOFC) integrated with biogas steam reforming is investigated to determine the optimal operating conditions. The system design and process simulation are carried out using Aspen Plus. The effects of three key operating parameters — reformer temperature, steam-to-biogas (S/C) molar ratio, and SOFC operating temperature— on electrical performance and CO₂ emissions are examined. Predictive modeling is developed using a Regression Tree to capture the relationship between input parameters and performance indicators. Subsequently, a Genetic Algorithm (GA) is employed to identify the optimal operating conditions that maximize power output and SOFC efficiency while minimizing CO₂ emissions. The results indicate that the optimal reformer temperature is 1024.26 K with an S/C ratio of 1.5, and the H-SOFC should operate at 1024.53 K, yielding a power output of 427.60 kW, an SOFC efficiency of 43.53%, and CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> emissions of 226.62 g/kWh. This demonstrates that the integrated system provides a highly efficient and low-carbon power generation solution.