Simplified model for the short-term forecasting of heat loads in buildings

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dc.contributor.authorEguizabal, Markel
dc.contributor.authorGaray Martínez, Roberto
dc.contributor.authorFlores-Abascal, Iván
dc.date.accessioned2025-07-22T11:21:08Z
dc.date.available2025-07-22T11:21:08Z
dc.date.issued2022-10-25
dc.date.updated2025-07-22T11:21:08Z
dc.description.abstractA data-driven model is used to predict one-hour ahead heat loads based on present and recent history of weather and heat loads. A computationally inexpensive method is built to deliver load forecasting based on existing data quality and resolution from smart meters. Optimal model formulation is discussed and optimized at 4-hour historical values. The model is trained and tested against synthetic data from a building energy simulation, resulting in absolute error <4% and R2 values in the range of 0.92 to 0.94.en
dc.identifier.citationEguizabal, M., Garay-Martinez, R., & Flores-Abascal, I. (2022). Simplified model for the short-term forecasting of heat loads in buildings. Energy Reports, 8, 79-85. https://doi.org/10.1016/J.EGYR.2022.10.224
dc.identifier.doi10.1016/J.EGYR.2022.10.224
dc.identifier.eissn2352-4847
dc.identifier.urihttps://hdl.handle.net/20.500.14454/3267
dc.language.isoeng
dc.publisherElsevier Ltd
dc.rights© 2022 The Author(s)
dc.subject.otherBuilding
dc.subject.otherHeating demand
dc.subject.otherLagged value
dc.subject.otherRegression model
dc.titleSimplified model for the short-term forecasting of heat loads in buildingsen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.endPage85
oaire.citation.startPage79
oaire.citation.titleEnergy Reports
oaire.citation.volume8
oaire.licenseConditionhttps://creativecommons.org/licenses/by-nc-nd/4.0/
oaire.versionVoR
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