Thermal energy integration and optimization in a biomass-fueled multi-generation system for power, hydrogen, and freshwater production
Li Sun, Ali Basem, Saleh Alhumaid, Mohamed Ayadi, Mahidzal Dahari, Talal Saad Alharbi, Yasmin Khairy, Abdulrahman M. Alansari, Samah G. Babiker, Ibrahim Mahariq
Abstract
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 m 3 /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 m 3 /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 %.