Modelling hydrothermal liquefaction process

Abstract

Renewable, drop-in fuels are necessary for transportation sectors that are challenging to electrify in order to mitigate climate change and achieve the European Green Deal's goal of being climate neutral by 2050. Hydrothermal liquefaction (HTL) is a promising thermochemical process. It converts wet biomass directly to an energy-dense biocrude, avoiding the need for drying. It also generally produces biocrude with lower oxygen content and improved higher heating value than fast pyrolysis. In this thesis, development and validation of the Aspen Plus simulation model for the full bark-to-biofuel conversion is investigated. The simulation of HTL of forest residue, specifically bark, followed by hydrodeoxygenation (HDO) and product stabilisation is performed using a model components (black box) approach. Experimental feedstock and product data for white pine bark were used to adjust individual component yields in the HTL yield reactor until the carbon, hydrogen, and oxygen balances closed (<0.001% atom error). The model reproduces the biocrude’s elemental composition to within ±2.3 wt% (C, H, O) and predicts an HHV of 29.9 MJ/kg, 3.8 MJ/kg above the experimental value. HTL is simulated as mildly exothermic (-11 kW), yet the overall process still demands 6.6 kW of external heat, highlighting the value of heat recovery. HDO of the modelled biocrude reduces oxygen to 0.43 wt%, raises the HHV to 46.2 MJ/kg (47.6 MJ/kg after stabilisation), consumes 0.06 kg H₂/kg biocrude and releases 41 kW of reaction heat that can offset the HTL duty. The upgraded fuel is rich in C5-C6 paraffins and contains C7-C18 cyclic and linear hydrocarbons, making it suitable for sustainable gasoline, aviation, and diesel blends. Model validity across feedstocks was evaluated with mulberry bark experimental data. It maintained atom balance closure and predicted 35.5 MJ/kg HHV (32.5 MJ/kg in experimental data), without altering the model component list, suggesting its potential application to other feedstock modelling. The validated model offers a strong basis for future studies on heat integration, techno-economic analysis and optimisation of biomass-to-biofuel processes.