(507b) Low-Dimensional Techno-Economic Cost Model for Expedited Hydrothermal Liquefaction Process Evaluation

Hydrothermal liquefaction (HTL) is rapidly emerging as a method to convert abundant organic wastes into renewable fuels. Deployment of this promising technology would benefit greatly from generalized methods of predicting costs, since current methods for estimating HTL costs requires a time and resource intensive process design and techno-economic analysis (TEA) for each specific case. To enable more efficient allocation of resources, there is a need for a simple and universal tool that can predict the economic viability of HTL processes. In this study, we have developed a model that utilizes three key variables - feedstock cost, biocrude yield, and process scale - to predict the minimum selling price of fuel (MFSP) produced by an HTL process. Our model is based on empirical observations from a wide range of feedstock costs, biocrude yields, and process scales obtained through detailed TEA. By fitting adjustable parameters to this model, we were able to predict independently published values of MFSP (N = 25) with an accuracy of ±20.4%, as shown in Figure 1. Model predictions are within 40% of the published value 95% of the time and in the worst case the discrepancy is 45.9%, meaning that the accuracy of the universal model is sufficient for screening purposes.

Figure 1: Parity performance of model-predicted minimum fuel selling price (MFSP) against literature values of MFSP.

The resulting model is capable of predicting MFSP using readily available data inputs, including feedstock cost, process scale, and experimental results for biocrude yield, enabling order-of-magnitude estimates for HTL ventures while foregoing the resource-intensive process of performing a traditional economic analysis.