Resilient Design and Operations of Chemical Process Systems

Abstract Resilience in response to disruption events is critical to the economic performance of process systems, but this concept has received limited attention in the literature. We propose a general framework for resilience optimization to incorporate an improved quantitative measure of resilience and a comprehensive set of resilience enhancement strategies for process design and operations. The proposed framework identifies a set of disruptive events for a given system, and then formulates a multiobjective two-stage adaptive robust mixed-integer fractional programming model to optimize the resilience and economic objectives simultaneously. The model accounts for network configuration, equipment capacities, and capital costs in the first stage, and the number of available processes and operating levels in each time period in the second stage. A tailored solution algorithm is developed to tackle the computational challenge of the resulting multi-level optimization problem. We demonstrate the applicability of the proposed framework through applications on a shale gas processing system.