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With the increasing demand for hydrogen resulting from fierce market competition and stringent environmental legislation, the hydrogen system has become an important component of a refinery. It is vital for the hydrogen system to be operated economically and safely under varying operating conditions. This calls for a systematic approach to the design and optimization of flexible hydrogen systems, which is the aim of this article. The hydrogen distribution network is designed at the minimum total annual cost subject to constraints on the flow rates and pressures of both existing and new equipment during the payback period. Varying hydrogen demands, different pipeline levels, and the possibility of hydrogen units being shut down are considered as operating conditions in the design optimization task, leading to the formulation and solution of a mixed-integer nonlinear programming (MINLP) problem. Using a linearization method, the MINLP formulation is approximated by a mixed-integer linear programming (MILP) problem, resulting in an acceptable quality and high efficiency. An industrial hydrogen system is taken as a case study. As shown in the case study, the proposed approach can handle high-dimensional and complex hydrogen system problems and gain significant economic improvements in comparison to an existing design.

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In a refinery, hydrogen, as a valuable resource, is also a byproduct and a significant raw material source of the petroleum refining and petrochemical hydrogenation process. To reduce costs and save energy for the petrochemical industry, the hydrogen system in a refinery should be operated under the optimal scheme to meet the varying hydrogen demands of hydrogen consumers. Optimal scheduling of the hydrogen system can help a refinery to achieve cost reduction and cleaner production. In this paper, a discrete-time mixed-integer nonlinear programming (MINLP) model that considers the penalties for abnormal situations in the hydrogen pipe network (HPN), compressors start–stop, and changes in hydrogen sources for hydrogen consumers is proposed for the optimal scheduling of the hydrogen system under multiperiod operation. The solution of the scheduling problem is obtained based on an iterative method between that of a mixed-integer linear programming (MILP) problem and that of a nonlinear programming (NLP) problem, avoiding the solution of the MINLP problem directly and the occurrence of composition discrepancy. A case study based on the data from a real refinery is presented to illustrate the effectiveness and feasibility of the proposed methodology.