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Linking Building Energy-Load Variations with Occupants' Energy-Use Behaviors in Commercial Buildings: Non-Intrusive Occupant Load Monitoring (NIOLM)
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rafsanjani, Hamed Nabizadeh | - |
dc.contributor.author | Ahn, Changbum | - |
dc.date.accessioned | 2024-05-17T08:04:16Z | - |
dc.date.available | 2024-05-17T08:04:16Z | - |
dc.date.created | 2024-05-16 | - |
dc.date.created | 2024-05-16 | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Procedia Engineering, Vol.145, pp.532-539 | - |
dc.identifier.issn | 1877-7058 | - |
dc.identifier.uri | https://hdl.handle.net/10371/203284 | - |
dc.description.abstract | Studies indicate that occupancy-related energy-use behaviors have a significant influence on overall energy consumption in commercial buildings. In this context, understanding and improving occupants' energy-consuming behaviors shows promise as a cost-effective approach to decreasing commercial buildings' energy demands. Current behavior-modification pursuits rely on the data availability of occupant-specific energy consumption, but it is still quite challenging to track occupant-specific energy-consuming behaviors in commercial buildings. On the other hand, individual occupants have unique energy-consumption patterns at their entry and departure events and will typically follow such patterns consistently over time. Thus, analyzing occupants' energy-use patterns at the time of their entry and departure events plays a critical role in understanding individual occupants' energy-use behaviors. To this end, this paper aims to develop a non-intrusive occupant load monitoring (NIOLM) approach that profiles individual occupants' energy-use behaviors at their entry and departure events. The NIOLM approach correlates occupancy-sensing data captured from existing Wi-Fi networks with aggregated building energy-monitoring data in order to disaggregate building energy loads to the level of individual occupants. Results from a 3-month long period of tracking individual occupants validate the feasibility of the NIOLM approach by comparing the framework's outcomes with the individual metering data captured from plug-load sensors. By utilizing existing devices and Wi-Fi network infrastructure, NIOLM provides a new opportunity for current industry and research efforts to track individual occupants' energy-use behaviors at a minimal cost. | - |
dc.language | 영어 | - |
dc.publisher | Procedia Engineering | - |
dc.title | Linking Building Energy-Load Variations with Occupants' Energy-Use Behaviors in Commercial Buildings: Non-Intrusive Occupant Load Monitoring (NIOLM) | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.proeng.2016.04.041 | - |
dc.citation.journaltitle | Procedia Engineering | - |
dc.identifier.wosid | 000387531600069 | - |
dc.identifier.scopusid | 2-s2.0-84999791292 | - |
dc.citation.endpage | 539 | - |
dc.citation.startpage | 532 | - |
dc.citation.volume | 145 | - |
dc.description.isOpenAccess | Y | - |
dc.contributor.affiliatedAuthor | Ahn, Changbum | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordAuthor | Commercial buildings | - |
dc.subject.keywordAuthor | Energy consumption | - |
dc.subject.keywordAuthor | Non-intrusive approach | - |
dc.subject.keywordAuthor | Occupant energy-use behavior | - |
dc.subject.keywordAuthor | Profiling energy-use behavior | - |
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- College of Engineering
- Department of Architecture & Architectural Engineering
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