An interval-parameter two-stage optimization model for CO2 collection, distribution, transportation, utilization, and storage planning

Geological carbon dioxide (CO2) utilization and storage have been widely recognized as one of the important options to deliver greenhouse gas emissions reduction. Reasonable planning is critical to promote CO2 utilization and storage. However, CO2 emissions gas collection exhibits a stochastic probability distribution, and CO2 utilization and storage features fluctuation demands, which have gone beyond current determine planning techniques. To fulfill the current research gap, this study develops an interval-parameter two-stage programming-based CO2 collection, distribution, transportation, utilization, and storage optimization model, integrating interval parameter planning and two-stage planning into a general framework. Therefore, the model can address uncertainties expressed as random probabilistic distributions and discrete intervals, tackle dynamic facilities capacity expansion issues, develop optimal predefined CO2 distribution policy, and generate recourse schemes to address gas shortage or gas surplus issues. The model is examined by a typical hypnotical case study in China. The results revealed that the model could generate a set of first-stage reasonable CO2 distribution and facilities capacity expansion schemes to maximum system benefits and the highest feasibility. Besides, a set of two-stage CO2 outsourcing purchases and facilities capacity expansion in reserve storage regions solutions were also generated to address the gas oversupplies and shortage issues. The modeling approach enriches the current CO2 utilization and storage distribution research content under multiple uncertainties.