Thermal energy integration and optimization in a biomass-fueled multi-generation system for power, hydrogen, and freshwater production

This work investigates a biomass-driven multi-generation system designed for simultaneous power, freshwater, and hydrogen production, addressing the interlinked energy-water-environment nexus. The configuration integrates Brayton, supercritical carbon dioxide (SCO2), organic Rankine cycle (ORC), and thermoelectric generator (TEG) subsystems to maximize utilization of biomass-derived syngas. The recovered energy drives a reverse osmosis (RO) desalination unit for freshwater production and an alkaline electrolyzer for hydrogen generation, followed by two-stage compression for storage. Under baseline conditions, the system generates 1.99 MW of electricity, 9.38 kg/h of hydrogen, and 88.6 m3/h of freshwater, with an overall exergetic efficiency of 20.25 %, emissions intensity of 0.85 kg/kWh, and a payback period of 5.87 years. The Brayton cycle accounts for 49.3 % of the total cost rate, while the gasifier exhibits the highest exergy destruction at 46 %. Sensitivity analyses show that varying biomass moisture content (10–30 %) and operating temperatures (700–900 °C) significantly influence system performance. Using a data-driven optimization framework that combines artificial neural networks (ANN) and a genetic algorithm (GA), the system's exergetic efficiency improves to 21.76 %, freshwater output rises to 90.96 m3/h, and emissions intensity decreases to 0.877 kg/kWh. Additionally, optimization reduces the total cost rate by 2.71 %, leading to a payback period of 5.4 years, and enhances the system's overall performance by 12.64 %.