Recently, Dr. Xia Chong from the College of Energy and Power Engineering at Zhengzhou University of Light Industry (ZZULI) published a high-quality academic paper entitled "5E analysis and multi-objective optimization of a novel PGR/AB-AD-SOFC-GT-ORC hybrid system using machine learning and NSGA-II" in Energy Conversion and Management (CAS Q1 TOP journal, IF = 10.9), an internationally renowned academic journal in the energy sector. Dr. Xia Chong serves as the first author, and ZZULI is the first affiliated institution.

The technology of producing hydrogen from municipal solid waste (MSW) via gasification and subsequent coupling with solid oxide fuel cell (SOFC) for power generation represents a promising technical route for waste valorization and clean energy supply. Within gasification technologies, although air gasification enables autothermal operation, it suffers from a low hydrogen yield; steam gasification can increase hydrogen concentration, but it requires external heat supply; and conventional electric heating and partial oxidation exhibit obvious drawbacks. This study develops a novel PGR/AB-AD-SOFC-GT-ORC hybrid system that supplies the heat released from SOFC anode off-gas combustion to the pyrolysis-gasification reactor (PGR), in which the PGR and afterburner (AB) are designed as an integrated structure. In addition, this study conducts a comprehensive 5E analysis of the hybrid system across five dimensions: energy, exergy, exergoeconomics, environment, and efficiency. On this basis, this study introduces a machine learning model and the NSGA-II multi-objective optimization algorithm to optimize the maximum power generation efficiency and the minimum levelized cost of energy (LCOE), subject to the constraint that the system's carbon dioxide (CO₂) emissions remain below those of conventional petroleum fuel-based systems (0.236 t/GJ). The results reveal that, under the best compromise solution, the system achieves an exergy efficiency of 43.60%, a power generation efficiency of 44.03%, CO₂ emissions of 0.229 t/GJ, and an LCOE of 0.03959 $/kWh. The hybrid system significantly improves energy efficiency while reducing emissions and costs, thus providing a viable solution for hydrogen production from MSW.

This research has been supported by programs such as the Key Research and Development Program of Henan Province, the Young Backbone Teachers of Henan Province, and the Henan Province Science and Technology Program for Tackling Key Problems.

Journal article link: https://doi.org/10.1016/j.enconman.2026.121375