Optimal strategies for carbon capture, utilization and storage based on an inexact mλ-measure fuzzy chance-constrained programming

Abstract

In this study, IMP (interval mathematical programming), mλ-measure, and fuzzy chance-constrained programming are incorporated into a general optimization framework, leading to an IMFCP (interval-parameter mλ-measure based fuzzy chance-constrained programming) method. The IMFCP method can be used to deal with not only interval uncertainties in the objective function, variables and left-hand side parameters, but also fuzzy uncertainties in the right-hand side. mλ-measure, which has the advantage of self-dual and can reflect the aspiration preference of decision makers, is used to describe the failure risk of fuzzy chance constrains. As a more generalized approach compared with credibility constrained programming, IMFCP can reflect the balance between optimism and pessimism. The developed method is applied to the long-term planning of CCUS (carbon capture, utilization and storage) management system. The results of IMFCP method can generate a series of CCUS management patterns under different risk levels, gain in-depth insights into the effects of uncertainties, and consider a proper balance between system costs and risks of constraint violation.