Flexibility analysis using boundary functions for considering dependencies in uncertain parameters

In this work, we present a novel approach for considering dependencies (often called correlations) in the uncertain parameters when performing (deterministic) flexibility analysis. Our proposed utilizes (linear) boundary functions to approximate observed or expected distribution of operating points (i.e. uncertainty space), and can easily be integrated index test problem. contrast hyperbox sets commonly used deterministic analysis, based on allow subsets which limit metric but no operation is expected, excluded. We derive generic mixed-integer formulation defined by functions, suggest an algorithm identify set with high accuracy. The tested compared several examples including industrial case study.