Integrating hydroprocessors in refinery hydrogen network optimisation

Recent developments on sulphur specifications in middle distillate fuels are exerting a higher demand on refinery hydrogen systems. Previous methodologies on hydrogen network optimisation have been developed mainly based on the assumption of fixed hydroprocessing performance with constant hydrogen consumption and light hydrocarbon yields in hydrogen consumer models, in order to reduce the complexity of the problem. As a result, interactions among process operating conditions, product quality and yields, and hydrogen consumption are usually neglected. esent work is an integrated approach for refinery process and hydrogen network design. Empirical correlations for sulphur prediction in liquid products are modified and adopted to predict hydrogen consumption in hydrotreaters. The model is validated with different feedstock properties and shows good agreement with experimental data. Light hydrocarbon yields in hydrodesulphurisation reactions are also predicted and integrated in the network model. Modelling and optimisation of the overall network is performed and the effects of process and operational variables on performance indicators and hydrogen production requirements are investigated. As a Nonlinear programming model, the overall network model is optimised with the CONOPT solver in General Algebraic Modelling System (GAMS). As demonstrated in a case study, by integrating hydrotreating models into multicomponent hydrogen networks, the focus of refinery hydrogen management can now be shifted from minimising hydrogen consumption to optimising hydrogen utilisation to improve refining profitability.