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Carbon capture, utilization, and storage (CCUS) are widely regarded as a crucial technological option for industrial large-scale carbon dioxide (CO2) emissions reduction. However, high-cost and uncertainties hinder the widespread application of CCUS technology. In this study, an interval-chance-constrained programming-based optimization model was proposed to address random probability distributions, interval values, complex interactions, and the dynamics of capacity expansion issues. The model was applied to a CCUS project in China. A se
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