Synthesis of Optimal Processing Pathway for Microalgae-based Biorefinery under Uncertainty

The research in the field of microalgae-based biofuels and chemicals is in early phase of the development, and therefore a wide range of uncertainties exist due to inconsistencies among and shortage of technical information. In order to handle and address these uncertainties to ensure robust decision making, we propose a systematic framework for the synthesis and optimal design of microalgae-based processing network under uncertainty.

By incorporating major uncertainties into the biorefinery superstructure model we developed previously, a stochastic mixed integer nonlinear programming (sMINLP) problem is formulated for determining the optimal biorefinery structure under given parameter uncertainties modelled as sampled scenarios.

The solution to the sMINLP problem determines the optimal decisions with respect to processing technologies, material flows, and product portfolio in the presence of uncertain parameters. The developed framework is implemented and tested on a specific case study, to identify the promising processing pathway for the production of biofuels from microalgae while accounting for modelled uncertainties.