Citation Export
DC Field | Value | Language |
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dc.contributor.author | Oh, Ji Hyun | - |
dc.contributor.author | Kim, Hye Gi | - |
dc.contributor.author | Kim, Sun Sook | - |
dc.date.issued | 2023-01-01 | - |
dc.identifier.uri | https://aurora.ajou.ac.kr/handle/2018.oak/36919 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85180158510&origin=inward | - |
dc.description.abstract | To achieve carbon neutrality at the national or city level, the energy performance and conservation measures of large buildings should be evaluated. However, the assessment of the energy performance of existing building stock is often based on annual energy use intensity calculated from energy bill data due to data acquisition limitations. This approach has limitations in analyzing seasonal effects and establishing effective energy conservation strategies. In this paper, we propose a novel energy performance assessment method for existing office building stock. Our method classifies monthly electricity, gas, and heat energy use patterns using clustering algorithms without requiring additional database construction beyond the National Building Energy Database in Korea. We discuss the clustering results and provide an application method to assist policymakers through a case study. | - |
dc.description.sponsorship | This study was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT & Future Planning (grant number NRF2020R1A2C1103033). | - |
dc.language.iso | eng | - |
dc.publisher | Institute of Physics | - |
dc.subject.mesh | Building stocks | - |
dc.subject.mesh | Carbon neutralities | - |
dc.subject.mesh | Conservation measures | - |
dc.subject.mesh | Energy bills | - |
dc.subject.mesh | Energy performance | - |
dc.subject.mesh | Energy performance assessments | - |
dc.subject.mesh | Energy-use intensities | - |
dc.subject.mesh | Large buildings | - |
dc.subject.mesh | Performance measure | - |
dc.subject.mesh | Seasonal effects | - |
dc.title | Cluster analysis-based energy performance assessment for office building stock | - |
dc.type | Conference | - |
dc.citation.conferenceDate | 2023.9.13. ~ 2023.9.15. | - |
dc.citation.conferenceName | 2023 International Conference on the Built Environment in Transition, CISBAT 2023 | - |
dc.citation.number | 8 | - |
dc.citation.title | Journal of Physics: Conference Series | - |
dc.citation.volume | 2600 | - |
dc.identifier.bibliographicCitation | Journal of Physics: Conference Series, Vol.2600 No.8 | - |
dc.identifier.doi | 10.1088/1742-6596/2600/8/082025 | - |
dc.identifier.scopusid | 2-s2.0-85180158510 | - |
dc.identifier.url | http://iopscience.iop.org/journal/1742-6596 | - |
dc.type.other | Conference Paper | - |
dc.description.isoa | true | - |
dc.subject.subarea | Physics and Astronomy (all) | - |
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