Multi-component optimisation for refinery hydrogen networks

Heavier crude oil, tighter environmental regulations and increased heavy-end upgrading in the petroleum industry are leading to the increased demand for hydrogen in oil refineries. Hence, hydrotreating and hydrocracking processes now play increasingly important roles in modern refineries. Refinery hydrogen networks are becoming more and more complicated as well. Therefore, optimisation of overall hydrogen networks is required to improve the hydrogen utilisation in oil refineries. Previous work over hydrogen management has developed methodologies for H2 network optimisation, with a very simplistic assumption that all H2 rich streams consist of H2 and CH4 only, which leads to a serious doubt of solution’s feasibility. To overcome the drawbacks in previous work, an improved modelling and optimisation approach has been developed. Light hydrocarbon production and integrated flash calculation are incorporated into a hydrogen consumer model. An optimisation framework is developed to solve the resulting NLP problem. A case study is carried out to demonstrate the effectiveness of the developed approach.

► Improved detailed multi-component hydrogen consumer model.
► Integrated flash calculation using constant K-values.
► Rigorous multi-component hydrogen network modelling.
► Systematic NLP optimisation methodology for refinery hydrogen network design.