Multi-objective optimization of a biomass-fired supercritical CO2 Brayton–electrolysis system for high‑efficiency hydrogen, power, and cogenerative thermal services

Abstract

A hybrid biomass-fired polygeneration plant integrating a gas turbine, a supercritical CO₂ Brayton loop, and an alkaline electrolyzer was developed to co-produce hydrogen, oxygen, electricity, and process heat. Rice Husk (RH) and Corn Stover (CS) feedstocks were assessed under identical thermodynamic boundaries to examine energy efficiency and carbon performance. The model, formulated in MATLAB, combined detailed mass- and energy-balance equations with an extended heat-recovery network. Multi-objective optimization using NSGA-II aimed to maximize hydrogen generation, limit CO₂ emissions, and raise overall efficiency. Parametric analysis revealed that higher turbine pressure ratios strengthen electrical output and diminish carbon intensity, whereas elevated turbine‑inlet temperatures promote thermal energy recovery but slightly lower global efficiency. Pareto‑optimal configurations displayed clear trade-offs between feedstocks: the RH case (PR = 18, Tg = 950 K) yielded 2.45 kg h⁻¹ of H₂, 37 kg h⁻¹ of CO₂, and 42.2 % efficiency; the CS counterpart produced 3.05 kg h⁻¹ of H₂ and 45 kg h⁻¹ of CO₂ at 40.5 % efficiency. The cascade turbine coupling and electrolysis pre-heating loop ensure full use of available thermal exergy and confirm strong thermodynamic synergy across both fuels. Sensitivity testing on PR, Tg, and BFR demonstrated model stability with deviations below 3 %. Overall, the findings establish a reproducible and feedstock-adaptive framework for high-efficiency, low-carbon, multi-output biomass energy systems suited to decentralized power and hydrogen production.