Bio-oil and heavy oil are co-processed in an existing
fluid catalytic
cracker of a refinery to reduce the biofuel cost and add biocarbon
into cracked products. The supply chain design is one of the fundamental
methods to further reduce the production cost of the co-processing
system. In this work, a two-stage stochastic programming integrating
the fluctuations of straw supply and price, algae growth rate, algae
nutrients price, crude oil price, and bio-oil yield is built to design
the supply chain of co-processing the system including biomass and
crude oil. The sample average approximation method is adopted to solve
the proposed two-stage stochastic programming. A fluid catalytic cracker
with 1.2 Mt/y is used as an example to illustrate the model. The results
show that optimal capacities of the algae cultivation process, fast
pyrolysis and depot, integration of crude oil supply and biomass supply,
and minimized total annual cost under multiperiod and uncertainties
can be obtained. A comparison of the stochastic programming and the
deterministic programming is also conducted and the result shows that
the total annual cost decreases if uncertainties are considered. The
uncertainties in the co-processing system should be considered when
designing the supply chain to increase the model’s feasibility.