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

Abstract

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.