Identification of optimal transitions towards climate footprint reduction targets using a linear multi-period carbon integration approach

Multi-period carbon integration identified CO₂ reduction schemes over a time horizon towards a specified target. Previously proposed multi-period approaches involving mixed integer non-linear formulations are difficult to solve. This paper introduces a two-step optimization approach to evaluate CO₂ reduction policies using a mixed integer linear program (MILP) through decomposition. The first step includes an exhaustive search of optimal low cost source-sink connections to process non-linear information involving pipeline, multistage compressor sizing and costing into linear/piece-wise linear optimal costs. The second step applies these models in the linear multi-period optimization model to design cost optimal CO₂ reduction networks. An example is solved where the method robustly and quickly found cost optimal solutions for CO₂ capture, utilization and storage (CCUS) networks coupled with Renewable Energy (RE) schemes. It shows how the method can be applied to assess prescribed CO₂ emissions reduction policies and identify improved policies resulting in reduced mitigation costs.