View in EDS HTML Full Text PDF Full Text

Variables for Planning Hydrogen Refueling Infrastructure.

Saved in:
Bibliographic Details
Title: Variables for Planning Hydrogen Refueling Infrastructure.
Authors: Álvarez Coomonte, Agustín1 (AUTHOR), Grande Andrade, Zacarías2 (AUTHOR) zacarias.grande@upc.edu, Porras Soriano, Rocío3 (AUTHOR)
Source: Energies (19961073). May2026, Vol. 19 Issue 9, p2242. 26p.
Subject Terms: *Infrastructure (Economics), *Spatial arrangement, *Value chains, *Bayesian analysis, *Sustainable transportation, *Hydrogen as fuel, *Stochastic models
Abstract: Hydrogen-based zero-emission transport technologies have reached a level of technical maturity that enables their operational deployment; however, their large-scale uptake remains constrained by the limited availability of refuelling infrastructure. This gap between technological readiness and infrastructure provision represents one of the main bottlenecks for the transition towards hydrogen-powered mobility systems. In this context, stakeholders evaluate hydrogen deployment through a set of key quality objectives, primarily related to emissions, economic performance, and efficiency. The achievement of these objectives is inherently conditioned by the configuration of the hydrogen value chain and, in particular, by the spatial dimension of infrastructure deployment. Despite its relevance, the combined effect of value chain variables and location-specific factors on quality outcomes remains insufficiently characterised in the literature. To address this gap, this study proposes a probabilistic modelling framework based on Bayesian Networks to capture the relationships between value chain variables, location-dependent conditions, and resulting quality indicators. This approach enables the explicit representation and propagation of uncertainty across the system, providing a robust analytical basis for evaluating alternative infrastructure deployment strategies. By integrating technical, economic, and spatial dimensions within a unified modelling structure, the proposed framework supports informed decision-making in the planning and optimisation of hydrogen refuelling infrastructure. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 193716138
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Variables for Planning Hydrogen Refueling Infrastructure.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Álvarez+Coomonte%2C+Agustín%22">Álvarez Coomonte, Agustín</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Grande+Andrade%2C+Zacarías%22">Grande Andrade, Zacarías</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> zacarias.grande@upc.edu</i><br /><searchLink fieldCode="AR" term="%22Porras+Soriano%2C+Rocío%22">Porras Soriano, Rocío</searchLink><relatesTo>3</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 9, p2242. 26p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Infrastructure+%28Economics%29%22">Infrastructure (Economics)</searchLink><br />*<searchLink fieldCode="DE" term="%22Spatial+arrangement%22">Spatial arrangement</searchLink><br />*<searchLink fieldCode="DE" term="%22Value+chains%22">Value chains</searchLink><br />*<searchLink fieldCode="DE" term="%22Bayesian+analysis%22">Bayesian analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Sustainable+transportation%22">Sustainable transportation</searchLink><br />*<searchLink fieldCode="DE" term="%22Hydrogen+as+fuel%22">Hydrogen as fuel</searchLink><br />*<searchLink fieldCode="DE" term="%22Stochastic+models%22">Stochastic models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Hydrogen-based zero-emission transport technologies have reached a level of technical maturity that enables their operational deployment; however, their large-scale uptake remains constrained by the limited availability of refuelling infrastructure. This gap between technological readiness and infrastructure provision represents one of the main bottlenecks for the transition towards hydrogen-powered mobility systems. In this context, stakeholders evaluate hydrogen deployment through a set of key quality objectives, primarily related to emissions, economic performance, and efficiency. The achievement of these objectives is inherently conditioned by the configuration of the hydrogen value chain and, in particular, by the spatial dimension of infrastructure deployment. Despite its relevance, the combined effect of value chain variables and location-specific factors on quality outcomes remains insufficiently characterised in the literature. To address this gap, this study proposes a probabilistic modelling framework based on Bayesian Networks to capture the relationships between value chain variables, location-dependent conditions, and resulting quality indicators. This approach enables the explicit representation and propagation of uncertainty across the system, providing a robust analytical basis for evaluating alternative infrastructure deployment strategies. By integrating technical, economic, and spatial dimensions within a unified modelling structure, the proposed framework supports informed decision-making in the planning and optimisation of hydrogen refuelling infrastructure. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193716138
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/en19092242
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 26
        StartPage: 2242
    Subjects:
      – SubjectFull: Infrastructure (Economics)
        Type: general
      – SubjectFull: Spatial arrangement
        Type: general
      – SubjectFull: Value chains
        Type: general
      – SubjectFull: Bayesian analysis
        Type: general
      – SubjectFull: Sustainable transportation
        Type: general
      – SubjectFull: Hydrogen as fuel
        Type: general
      – SubjectFull: Stochastic models
        Type: general
    Titles:
      – TitleFull: Variables for Planning Hydrogen Refueling Infrastructure.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Álvarez Coomonte, Agustín
      – PersonEntity:
          Name:
            NameFull: Grande Andrade, Zacarías
      – PersonEntity:
          Name:
            NameFull: Porras Soriano, Rocío
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 19961073
          Numbering:
            – Type: volume
              Value: 19
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Energies (19961073)
              Type: main
ResultId 1