Abstract
Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods; 2) lighting control system using RTDM can save considerable energy by daylight harvesting.
Original language | English |
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Title of host publication | Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017 |
Publisher | Association for Computing Machinery |
Pages | 318-325 |
Number of pages | 8 |
Volume | Part F127852 |
ISBN (Electronic) | 9781450348096 |
DOIs | |
Publication status | Published - 2017 Feb 18 |
Event | 9th International Conference on Computer and Automation Engineering, ICCAE 2017 - Sydney, Australia Duration: 2017 Feb 18 → 2017 Feb 21 |
Other
Other | 9th International Conference on Computer and Automation Engineering, ICCAE 2017 |
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Country | Australia |
City | Sydney |
Period | 17/2/18 → 17/2/21 |
Keywords
- Daylight modeling
- Lighting control
- RBFNN
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software