Modeling and optimization of refinery hydrogen management system considering hydroprocessing mechanisms and constraints

•The coupling sink-source model expresses hydroprocessing mechanisms.•The coupling sink-source model expands optimization dimension for HNS.•The interactions between HNS and hydroprocessing unit operations are revealed.•The linear representation-based optimization framework achieves global optimizat...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Chemical engineering science Jg. 321; S. 122861
Hauptverfasser: Zhou, Yingqian, Yang, Minbo, Wang, Yufei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.02.2026
Schlagworte:
Coupling sink-source model
Hydrogen network synthesis
Hydroprocessing mechanisms
Machine learning
Mixed-integer nonlinear programming
Mixed-integer nonlinear programming
Coupling sink-source model
Hydrogen network synthesis
Hydroprocessing mechanisms
Machine learning
ISSN:0009-2509
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•The coupling sink-source model expresses hydroprocessing mechanisms.•The coupling sink-source model expands optimization dimension for HNS.•The interactions between HNS and hydroprocessing unit operations are revealed.•The linear representation-based optimization framework achieves global optimization. Hydrogen network synthesis (HNS) in refineries serves as an effective approach to enhance hydrogen utilization efficiency, optimize network topology, and reduce operating costs. Conventional methods typically rely on the fixed hydrogen source and sink parameters, which deviates from the refinery reality. To address this problem, this work develops a data-driven optimization framework that hybrids rigorous simulation and machine learning to establish a coupling hydrogen sink-source model with hydroprocessing mechanisms and product specifications. The proposed framework comprehensively incorporates reaction-separation-compression systems in HNS. A mixed-integer nonlinear programming model is formulated for optimal synthesis of hydrogen networks. The results of systematic case studies reveal that implementing the coupling sink-source model expands the optimization dimensions, thereby reducing the pure hydrogen consumption in hydroprocessing units and decreasing the total annualized cost (TAC) by 9.35 %∼10.00 %. The consideration of compressor sharing contributes to a slight TAC reduction due to its low-cost proportion, but it enables additional cost savings through topology reconfiguration. The synergistic optimization of hydrogen networks and hydroprocessing units is achieved in this work.
ISSN:0009-2509
DOI:10.1016/j.ces.2025.122861