Optimal design and operation of refinery hydrogen systems under multi-scale uncertainties

Robust design of hydrogen systems for large-scale refineries under multi-scale uncertainties has great potential for energy saving and cost reduction. The operation of hydrogen network is greatly affected by the rapidly changing market, deteriorating crude feedstock and varying operating conditions. In this paper, we propose a two-stage stochastic programming with flexibility constraints modeling framework that accounts for multi-scale uncertainties in an integrated strategy, aiming to achieve a good trade-off between the economic performance and the robustness of operation. A tailored-made global optimization algorithm based on multiparametric disaggregation technique is developed to tackle the computational challenge of the resulting MINLP problem with numerous bilinear terms. To illustrate the applicability of the proposed modeling framework and solution algorithm, studies on the optimal design of an industrial hydrogen system are presented. Multi-scenario operation strategy increases the operational flexibility and greatly reduces the total annualized cost in terms of the value of stochastic solution.