Multi-objective optimization for the deployment of carbon capture utilization and storage supply chain considering economic and environmental performance

Abstract

Carbon capture utilization and storage (CCUS) is widely recognized as a promising mitigation technology that would significantly reduce carbon dioxide (CO2) emission. This study develops an optimization-based framework for the deployment of CCUS supply chain with economic and environmental concerns. The overall supply chain is optimized based on superstructure method over a 20 years’ time horizon to provide the location and scale of capture and sequestration sites as well as the most efficient CO2 transport routes capable of meeting the reduction target. The resulting problem is a multi-objective mixed integer linear programming (MILP) problem, whose objectives include minimizing total annual cost and environmental impact. The environmental impact is measured by Global Warming Potential (GWP) imposed by the supply chain operation and quantified according to the principles of Life cycle assessment (LCA). ε-Constraint method is implemented to solve the resultant multi-objective model. A realistic case study that addresses the optimal design of the CCUS supply chain needed to meet the reduction target in Northeast China is studied to demonstrate the application of the proposed model. Results obtained provides valuable insights into the addressed problem and guides the decision-maker to adopt more sustainable alternatives in the deployment of CCUS.