Hydrothermal liquefaction (HTL) of microalgae is a promising pathway to biocrude oil, but its high energy demand remains a key challenge. This study addresses this issue by developing and optimizing an enhanced heat integration strategy using Aspen Plus® and a genetic algorithm. The strategy integrates an evaporation step and additional heat exchangers to concentrate the algae slurry and recover thermal energy from the reactor effluent. A genetic algorithm was employed to optimize key process variables, including pump pressures and heat exchanger temperatures, with the goal of maximizing energy efficiency and minimizing CO2e emissions. The optimized process achieved notable improvements compared with the baseline, increasing energy efficiency from 54% to 56%, reducing the net energy ratio by 40% (from 0.1 to 0.06 MJ input per MJ oil), and lowering CO2e emissions by 20% (from 0.54 to 0.43 kg CO2 per kg oil). Sensitivity analyses revealed that biocrude yield and feedstock concentration were the most influential parameters affecting overall performance. This work demonstrates a viable, low-carbon pathway for microalgae-based biofuel production and provides a roadmap for future research and industrial-scale implementation.
