Data-driven multi-criteria optimization for sustainable biogas-to-hydrogen systems: A comprehensive framework for sustainability-indexed design and analysis

This study presents a comprehensive, data-driven optimization-based multi-criteria decision-making framework (Opti − MCDM) for the optimal design and analysis of sustainable biogas-to-hydrogen (B2H2) systems. Five methane (CH₄) reforming technologies were evaluated under varying biogas qualities (55–75 % CH₄) with four objectives: hydrogen production rate, unit cost, CO₂ emissions, and energy efficiency. A general process model simulated reforming, syngas adjustment, and separation, generating over 130,000 data sets. The Opti − MCDM framework identified optimal configurations and operating conditions, providing both objective-oriented and sustainability-indexed solutions that balance trade-offs among conflicting goals. Notably, the most sustainable solution achieved a well-balanced performance, with an annual hydrogen production of 34.34 kt/y, a unit cost of 1.84 USD/kg of H₂, CO₂ emissions of 1.54 kg of CO_2eq/kg of H₂, and an energy efficiency of 46.64 % under biogas containing 75 % CH₄. These results represent the lowest trade-offs relative to the optimal values, with deviations of 24.82 %, 9.95 %, 31.14 %, and 17.14 % for product yield, economic, environmental, and energy efficiency indicators, respectively. The proposed framework offers practical guidelines for process designers and decision-makers seeking technically feasible and sustainability-aligned B2H2 configurations. This work advances the integration of data-driven optimization and multi-criteria analysis in renewable hydrogen production, supporting the transition to low-carbon energy systems.