Superstructure-based optimization framework to assess defossilization pathways in petrochemical clusters
M.D. Tan (TU Delft - Energy and Industry)
I. Nikolic (TU Delft - System Engineering, TU Delft - Multi Actor Systems)
Andrea Ramirez (TU Delft - ChemE/Chemical Engineering)
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Abstract
The petrochemical industry must transition its material and energy sources from fossil-based sources to more sustainable alternatives. While decarbonizing the energy source is challenging, defossilization of the material feedstock is significantly more difficult. In this work, we present a superstructure-based, multi-period, multi-objective optimization framework to address this problem. This framework focuses on minimizing the use of fossil carbon and modifications to petrochemical clusters while explicitly controlling the order of appearance of new processes. The combination of process options becoming available to the solution space over time and the cluster being locked in a path-dependent transition allows the framework to capture realistic transformation pathways. We demonstrate the framework with a small-scale case study of 10 fossil-based and 6 alternative processes. The results demonstrate the ability of the framework to select optimal defossillization pathways while simultaneously considering the impacts on mass and energy flows across the cluster.
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