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.