Multi-period Optimization of Hydrogen Networks with Sulfur Content Variation

Abstract

Abstract Crude oil is becoming heavier and lower-quality worldwide, especially the increase of sulfur content, which significantly influence on hydrogen consumption and products quality. At present, mathematical programming for hydrogen network integration can effectively conserve hydrogen resource. However, existing model hardly consider sulfur variation of crude oil. In this paper, a mixed integer nonlinear programming (MINLP) model is established to address hydrogen networks with feed oil sulfur content variation in multi-period. Hydroprocessing units are classified as upstream and downstream ones and new connections are added to perform integration. Fresh hydrogen minimization are employed as objective to optimize the hydrogen networks. Case study indicates that the novel model can achieve optimal strategy for sulfur content variation.