Geological carbon dioxide (CO_(2)) 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 CO_(2) u...Geological carbon dioxide (CO_(2)) 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 CO_(2) utilization and storage. However, CO_(2) emissions gas collection exhibits a stochastic probability distribution, and CO_(2) 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 CO_(2) 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 CO_(2) 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 CO_(2) distribution and facilities capacity expansion schemes to maximum system benefits and the highest feasibility. Besides, a set of two-stage CO_(2) 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 CO_(2) utilization and storage distribution research content under multiple uncertainties.展开更多
基金This study was supported by the National Natural Science Foundation of China of China(51761125013,51778319).
文摘Geological carbon dioxide (CO_(2)) 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 CO_(2) utilization and storage. However, CO_(2) emissions gas collection exhibits a stochastic probability distribution, and CO_(2) 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 CO_(2) 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 CO_(2) 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 CO_(2) distribution and facilities capacity expansion schemes to maximum system benefits and the highest feasibility. Besides, a set of two-stage CO_(2) 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 CO_(2) utilization and storage distribution research content under multiple uncertainties.
