Techno-economic uncertainty analysis of wet waste-to-biocrude via hydrothermal liquefaction

Abstract

Wet waste hydrothermal liquefaction (HTL) has the potential to make economically competitive and environmentally sustainable biocrude. However, there are few studies available on the continuous-flow wet waste HTL process. Therefore, stochastic techno-economic analysis (TEA) is needed to evaluate the economic feasibility and risks of the wet waste HTL process. This work leveraged our previous uncertainty quantification work on algae HTL and in-house wet waste HTL continuous system testing data. A “component additivity” model was developed to predict HTL product yields and qualities from different wet waste compositions. With the established HTL yield model, a process reduced-order model (ROM) coupled with an economic model was built in Microsoft Excel® to replace the rigorous but computationally intensive Aspen Plus® model for uncertainty analysis. The proposed stochastic TEA approach using the ROM reduces the computational time for the analysis by 2000 times, compared to the full Aspen-based model. Monte Carlo simulation was conducted to quantify the uncertainties from feedstock composition, HTL yield model, aqueous-phase product treatment, utility consumption, and equipment sizing and costing. The stochastic TEA indicates that the MBSP for wet waste HTL ranges from $2.65/gge ($0.75/L) to $4.93/gge ($1.41/L) (10th and 90th percentiles) with a median of $3.55/gge ($1.01/L). Feed moisture, HTL reactor model, and capital investment are the main contributors to the economic uncertainty of the wet waste HTL process. Uncertainty in the MBSP could be reduced by roughly 50% if uncertainties in the feed moisture and HTL reaction yield model can be effectively controlled or decreased.