Multiperiod Stochastic Optimization Model for Carbon Capture and Storage Infrastructure under Uncertainty in CO2 Emissions, Product Prices, and Operating Costs

Abstract

A multiperiod stochastic programming model is developed for planning a carbon capture and storage (CCS) infrastructure including CO2 utilization and disposal in an uncertain environment and with a time-varying investment environment. An inexact two-stage stochastic programming approach is used to analyze the effect of possible uncertainties in product prices, operating costs, and CO2 emissions. The proposed model determines where and how much CO2 to capture, store, transport, utilize, or sequester for the purpose of maximizing the total profit of handling the uncertainty while meeting the CO2 mitigation target during each time period of a given planning interval. The capability of the proposed model to provide correct decisions despite a changing uncertain environment is tested by applying it to designing and operating the future CCS infrastructure on the eastern coast of Korea over a 20-year planning interval (2011-2030).