The global transition toward renewable energy demands strategies to replace fossil-derived feedstocks. Soybean straw, generated at a ratio of 1.2–1.5 tons per ton of grain, is an abundant, underutilized lignocellulosic residue with significant potential for renewable fuel production. Brazil produced approximately 148 million tons of soybeans in 2024, making soybean straw a strategic feedstock for large-scale biorefineries. This work proposes a conceptual biorefinery that integrates thermochemical and biological routes to produce renewable methanol as a drop-in substitute for fossil-derived methanol in biodiesel transesterification, with the aim of achieving an energy-autonomous system. Three kinetic models were developed: (i) a multi-component pyrolysis model based on cellulose, hemicellulose, lignin, and extractives decomposition; (ii) an ADM1-R3 anaerobic digestion model; and (iii) a bi-reforming model integrating steam reforming, dry reforming, and water-gas shift reactions of the biogas. To achieve thermal self-sufficiency, the biochar fraction is combusted and coupled to a Brayton cycle. The models were developed and integrated in Python. The pyrolysis model yielded 32.7 wt% biochar, 50.8 wt% bio-oil, and 16.5 wt% pyro-gas at 750°C. The anaerobic digestion model produced 0.35 m³ of biogas per kg of volatile solids, with a methane content of 56%. The bi-reforming model achieved an H₂/CO ratio of 2.2 and a syngas output of 313 kmol/h at a biomass feed rate of 8,000 kg/h, corresponding to approximately 50 ton/day of renewable methanol. The CO₂ in the biogas is consumed as a reactant in dry reforming, thereby reducing direct atmospheric emissions. The Brayton cycle generates 2.5 MW of net electrical power and 6 MW of recoverable heat from exhaust gases at 645°C, supplying the thermal demand of the pyrolysis and reforming stages and effectively closing the energy loop. The integrated biorefinery demonstrates that soybean straw can sustain renewable methanol production while achieving energy autonomy through biochar-driven cogeneration. Bio-oil is recovered as a high-value co-product, and digestate is used as an organic fertilizer, strengthening economic competitiveness. The developed Python-based platform integrates detailed kinetic, thermodynamic, and energy balance models, providing a basis for subsequent techno-economic evaluation of the proposed agro-industrial biorefinery and advancing circular bioeconomy principles across the soybean supply chain.