Optimizing liquid hydrogen transport and trade through a hub-and-spoke model

Optimizing liquid hydrogen transport and trade through a hub-and-spoke model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimizing liquid hydrogen transport and trade through a hub-and-spoke model Kamini Singh, S Viswanathan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6694850/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This work explores the potential of transforming a port into a hydrogen hub within a regional trade network using a cost optimization model. With the global push toward clean energy, ports can play a key role in hydrogen distribution across countries. We propose a “hub and spoke” logistics model where liquid hydrogen (LH₂) is imported from a producer nation and redistributed to neighbouring countries. The presented model is built using mixed integer linear programming (MILP) and tested through a real-world case study: Australia as the hydrogen exporter, Singapore as the central hub, and Malaysia and Indonesia as regional importers. To ensure broad applicability, the model evaluates four ship capacities—70,000 m³, 140,000 m³, 280,000 m³, and 420,000 m³—reflecting different cost and scale scenarios. A total of 1,539 demand combinations are analysed to reflect varying future market conditions. Results indicate that Singapore holds strong potential to serve as a hydrogen trade hub, with possible cost savings of up to 55% and an average reduction of 24% across scenarios. These findings highlight the strategic importance of maritime infrastructure and regional planning in the hydrogen economy, positioning key ports like Singapore at the centre of future energy logistics. Environmental Economics Hub & spoke network mixed integer linear programming economies of scale optimization LH2 shipping and trading Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6694850","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":458417161,"identity":"688ac5c5-7d24-460e-8ebe-11000d3f8b48","order_by":0,"name":"Kamini Singh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYBACCSA+wGDAwMAGQh8gggbEa2GcAVFNWAsMsDHzEKNFsv104uGCAgZ7Pun2a49td/xJbGBv3ibB8KcWpxZpntwNh2cYMCS2yZwpN849Y5DYwHOsTIKx7ThOLXIMQC08BgwJbBI5adK5bUAtEjlmEowNx3Br4X8L1mIP1mIJ0iL/xgzoMNxapCUgtjC2SaQfk2YE28ID1MJWg9v7M8C2SCS2SeSwSfa2GRu38aQVWyS2HcCpReJ87ubPPH9s7OVnpD+T+NkmJ9vPfnjjjQ9/6nBqgekEYh5IdLCBiASGw4S0gAD7A2QeQVtGwSgYBaNg5AAA4mNMfiGd+HcAAAAASUVORK5CYII=","orcid":"","institution":"NTU","correspondingAuthor":true,"prefix":"","firstName":"Kamini","middleName":"","lastName":"Singh","suffix":""},{"id":458417162,"identity":"e425175c-ceff-4a4b-bf38-849bc4b9ba06","order_by":1,"name":"S Viswanathan","email":"","orcid":"","institution":"NTU","correspondingAuthor":false,"prefix":"","firstName":"S","middleName":"","lastName":"Viswanathan","suffix":""}],"badges":[],"createdAt":"2025-05-19 04:18:20","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6694850/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6694850/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83123748,"identity":"4a5f74db-c376-4a19-be91-80ec5f6f2a4e","added_by":"auto","created_at":"2025-05-20 09:26:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1086698,"visible":true,"origin":"","legend":"","description":"","filename":"Projrct2EoSforHSmanuscript3.33SubmissionJCP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6694850/v1_covered_5c53eca9-0688-4e54-ab37-584c6798c919.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eOptimizing liquid hydrogen transport and trade through a hub-and-spoke model\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Nanyang Technological University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hub \u0026 spoke network, mixed integer linear programming, economies of scale, optimization, LH2 shipping and trading","lastPublishedDoi":"10.21203/rs.3.rs-6694850/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6694850/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis work explores the potential of transforming a port into a hydrogen hub within a regional trade network using a cost optimization model. With the global push toward clean energy, ports can play a key role in hydrogen distribution across countries. We propose a \u0026ldquo;hub and spoke\u0026rdquo; logistics model where liquid hydrogen (LH₂) is imported from a producer nation and redistributed to neighbouring countries. The presented model is built using mixed integer linear programming (MILP) and tested through a real-world case study: Australia as the hydrogen exporter, Singapore as the central hub, and Malaysia and Indonesia as regional importers. To ensure broad applicability, the model evaluates four ship capacities\u0026mdash;70,000 m\u0026sup3;, 140,000 m\u0026sup3;, 280,000 m\u0026sup3;, and 420,000 m\u0026sup3;\u0026mdash;reflecting different cost and scale scenarios. A total of 1,539 demand combinations are analysed to reflect varying future market conditions. Results indicate that Singapore holds strong potential to serve as a hydrogen trade hub, with possible cost savings of up to 55% and an average reduction of 24% across scenarios. 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