Enhanced methodology for disaggregating space heating and domestic hot water heat loads of buildings in district heating networks

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dc.contributor.authorBorgato, Nicola
dc.contributor.authorBordignon, Sara
dc.contributor.authorPrataviera, Enrico
dc.contributor.authorGaray Martínez, Roberto
dc.contributor.authorZarrella, Angelo
dc.date.accessioned2025-02-14T08:49:27Z
dc.date.available2025-02-14T08:49:27Z
dc.date.issued2025-03
dc.date.updated2025-02-14T08:49:27Z
dc.description.abstractThis paper presents an innovative approach to disaggregate a building's global heat consumption into space heating and domestic hot water heat load components using Energy Signature Curve models. The study addresses the challenges associated with these models, which often fail to represent daily trends accurately and do not account for dynamic changes in building usage. Four approaches based on linear regression models are compared to determine the most accurate method for space heating and domestic hot water disaggregation. The state-of-the-art Energy Signature Curve is compared with three improved alternatives. A new algorithm for automatic season threshold identification is proposed. The comparison with consumption data indicates that the proposed methodology significantly improves the accuracy in heat load disaggregation, with the superior performance provided by the model based on a 24-hour energy threshold. This advancement can potentially optimize district heating network management and support retrofit interventions by providing detailed consumption profiles.en
dc.identifier.citationBorgato, N., Bordignon, S., Prataviera, E., Garay-Martinez, R., & Zarrella, A. (2025). Enhanced methodology for disaggregating space heating and domestic hot water heat loads of buildings in district heating networks. Applied Thermal Engineering, 263. https://doi.org/10.1016/J.APPLTHERMALENG.2024.125296
dc.identifier.doi10.1016/J.APPLTHERMALENG.2024.125296
dc.identifier.issn1359-4311
dc.identifier.urihttp://hdl.handle.net/20.500.14454/2305
dc.language.isoeng
dc.publisherElsevier Ltd
dc.rights© 2024 The Author(s)
dc.subject.otherEnergy signature curve
dc.subject.otherHeat load clusterization
dc.subject.otherHeat load disaggregation
dc.subject.otherLinear regression models
dc.subject.otherSeason threshold identification
dc.titleEnhanced methodology for disaggregating space heating and domestic hot water heat loads of buildings in district heating networksen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.titleApplied Thermal Engineering
oaire.citation.volume263
oaire.licenseConditionhttps://creativecommons.org/licenses/by-nc-nd/4.0/
oaire.versionVoR
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