(243d) Dynamic Performance of Fischer-Tropsch Liquid Fuel Production from Solar-Assisted Supercritical Water Gasification of Algae

The coupling of solar supercritical water gasification (SCWG) of algae with downstream Fischer–Tropsch (FT) synthesis is a promising approach for renewable biofuel production. The accurate prediction of the economic performance highly depends on the transient behaviour of the system. However, the integration of solar-driven SCWG with the conventional FT slurry bubble column reactors, which take days or weeks to achieve steady-state operation, is quite challenging, due to the transient nature of the solar resource. Microtubular reactors, on the other hand, can achieve steady-state much faster than the conventional FT reactors.

This paper focuses on the effect of solar variability and evaluates the techno-economic feasibility of an integrated solar-SCWG and microtubular-FT process. For this purpose, the steady-state SCWG and FT processes are modelled in ASPEN Plus software. A fixed-size 50 MW_th con- centrated solar-thermal (CST) input is used to drive the endothermic reactions in the SCWG system. The output gases from the gasifier mainly contain CO2, CH4 and H2. Three alternative reforming technologies are evaluated in this research including Steam Methane Reforming (SMR), Autothermal Reforming (ATR), and Partial Oxidation/Dry Reforming (PO/DR) to convert CH4 to syngas. After the reforming process, the H2 to CO ratio is less than the optimal ratio (2.1) for downstream FT and some make-up hydrogen is provided from low-temperature photovoltaic water-splitting (PV-electrolysis). Syngas storage acts as the buffer between the SCWG and FT units.

The main dynamic parameters considered here are the ramp times for the FT reactor, the size of syngas storage and the solar multiple for the FT system. The off-design production rates of syngas and liquid products are determined from the steady-state ASPEN models as a function of DNI. The polynomials obtained from these variables are imported into a system model in OpenModelica. The case study developed here is based on one year of hourly weather data for Geraldton, Australia. The total capital investment of the integrated units is estimated using the nth plant scenario with a 30-year plant lifetime. The levelised cost of fuel (LCOF) is calculated as a function of the FT size, assuming a fixed size for CST. The sensitivity analysis suggests that the operating cost of algal and H2 (from PV-electrolysis) feedstocks are the dominant components of the LCOF. A single-objective optimization is performed to find the configuration with the lowest LCOF. This carbon-neutral fuel produced from algal biomass can be blended with fossil fuels to decrease the life-cycle greenhouse gas emissions. Further reduction in the LCOF is expected from technological improvements and cost reductions in PV-H2 technology, and using cheaper feedstocks.