The potential role of carbon capture and storage technology in sustainable electric-power systems under multiple uncertainties

One of the problems facing researchers in managing carbon capture and storage (CCS) technology is that complex energy systems accommodate the relevant social, economic, environmental, and political factors. Many system behaviors, factors, and parameters are associated with uncertainties. Effective management of such a complex system involves balancing tradeoffs among these key influencing factors under multiple uncertainties. In this study, an interval-fuzzy stochastic programming (IFSP) method is developed to deal with multiple uncertainties expressed as fuzzy sets, intervals and probability distributions. An IFSP-CCS model is formulated to plan CCS technology of power system in Bayingolin Mongol Autonomous Prefecture (Bazhou). Policy scenarios are introduced to investigate the potential role of CCS technology and sensitivity analyses are performed to assess the influence of various economic factors on system cost. Results indicate various uncertainties existed in CCS development and the related factors can affect the modeling outputs. Results also reveal that CO2-mitigation constraint can induce the development of renewable energy and CCS, and CCS technology can make a great contribution to CO2 emission reductions from a long-term planning perspective. The findings can provide support for CCS investment in fossil-fuel-dominated electric-power system and offer useful information for policy investigation under multiple uncertainties.