| Download | - View accepted manuscript: Potential energy savings from high-resolution sensor controls for LED lighting (PDF, 1.2 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1016/j.enbuild.2017.09.048 |
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| Author | Search for: Dikel, Erhan E.1; Search for: Newsham, Guy R.1; Search for: Xue, Henry1; Search for: Valdés, Julio J.2 |
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| Name affiliation | - National Research Council of Canada. Construction
- National Research Council of Canada. Information and Communication Technologies
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| Format | Text, Article |
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| Subject | high-resolution sensors; light-emitting diodes (LEDs); energy efficiency; occupancy sensing; daylight harvesting |
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| Abstract | LED lighting systems paired with high-resolution sensor systems offer great potential for substantial energy savings via enhanced control options, and have other value-added features. We used modelling and demonstrations in a full-scale office test bed to illustrate this potential. First, we propose that such a system enables much shorter timeout periods for occupancy sensing: the higher density of sensors provides more reliable occupancy detection and LEDs are impervious to lifetime degradation from the consequent increased switching frequency. We used occupancy data measured in real office environments to estimate that a reduction in timeout period from the current code maximum of 20 minutes to 1 minute would yield 26% additional energy savings. Further, we installed 72 LED luminaires in an office test bed with windows; each luminaire featured a co-located motion sensor and light sensor. The localized light sensor enabled daylight harvesting at each fixture to be optimized to local spatial conditions, yielding an extra 35% energy savings compared to a single photosensor controlling all luminaires, and ensuring better delivery of target horizontal illuminance values across the space. Finally, we demonstrated a combination of local occupancy and daylight harvesting features that resulted in 79% energy savings compared to typical prevailing energy code provisions for open-plan offices. |
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| Publication date | 2017-09-19 |
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| Publisher | Elsevier |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 23002265 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 6729a7d5-ccc7-45e8-b6bf-34f5028c018f |
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| Record created | 2017-09-26 |
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| Record modified | 2021-10-14 |
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