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Ensuring Reliable District Heating Systems: Identifying Critical Components under Independent and Cascading Failure Scenarios

aut.relation.articlenumber107118
aut.relation.endpage107118
aut.relation.journalSustainable Cities and Society
aut.relation.startpage107118
dc.contributor.authorMao, Ding
dc.contributor.authorXu, Sai
dc.contributor.authorWang, Jay
dc.contributor.authorShen, Linhua
dc.contributor.authorHe, Wei
dc.date.accessioned2026-01-07T01:59:35Z
dc.date.available2026-01-07T01:59:35Z
dc.date.issued2026-01-05
dc.description.abstractUrban district heating systems are vital infrastructures of sustainable cities, providing efficient and centralized thermal energy to residential and industrial users. However, these systems consist of numerous interdependent components that are prone to faults, which can disrupt heat supply and compromise service reliability. Identifying critical components to maintain system stability is crucial for enhancing the resilience and sustainability of urban energy infrastructure. Critical components are generally determined by evaluating the consequences of failures, which involves simulating all possible fault scenarios, a process that is computationally expensive and time-consuming. To address this challenge, we propose a comprehensive component importance identification framework. This framework incorporates two methods: the Importance Calculation Method (ICM), which operates under normal system conditions, and the Failure-Simulation-Based Method (FSM), which simulates failure consequences. These methods evaluate component criticality under both independent and cascading failure scenarios, incorporating topological and functional perspectives. To validate the proposed framework, gridded heating system models of varying scales, comprising 4-, 9-, 16-, and 25-node configurations, were developed. Applying the framework to these models revealed a strong correlation between ICM and FSM results: the topological importance index in ICM showed a high correlation with FSM’s functional consequence indices (ρ > 0.75), while the functional importance indices achieved even higher correlations (ρ = 0.94–0.97). Finally, the framework was applied to a real-world district heating system in China, where it successfully identified critical pipes and demonstrated the effectiveness and practical value of the proposed ICM through comparison with traditional fault-simulation-based methods.
dc.identifier.citationSustainable Cities and Society, ISSN: 2210-6707 (Print), Elsevier BV, 107118-107118. doi: 10.1016/j.scs.2026.107118
dc.identifier.doi10.1016/j.scs.2026.107118
dc.identifier.issn2210-6707
dc.identifier.urihttp://hdl.handle.net/10292/20449
dc.languageen
dc.publisherElsevier BV
dc.relation.urihttps://www.sciencedirect.com/science/article/abs/pii/S2210670726000053?via%3Dihub
dc.rightsThis is the Author's Accepted Manuscript of an article published in Sustainable Cities and Society. The Version of Record is available at DOI: 10.1016/j.scs.2026.107118
dc.rights.accessrightsOpenAccess
dc.subject0502 Environmental Science and Management
dc.subject1205 Urban and Regional Planning
dc.subject3302 Building
dc.subject3304 Urban and regional planning
dc.subject4406 Human geography
dc.titleEnsuring Reliable District Heating Systems: Identifying Critical Components under Independent and Cascading Failure Scenarios
dc.typeJournal Article
pubs.elements-id749811

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