Abstract
Occupancy-based lighting control can be applied at
several resolution levels. To aid lighting designers in choosing the
appropriate solution for a specific open-plan office case, this paper
presents a simulation tool which enables calculating the lighting
energy use for the different control strategies. By using a stochastic
modelling approach and input parameters as users’ function type,
the office’s policy and special absences, the model could reflect the
actual occupancy behaviour in the office at hand. The results of
the model were validated with occupancy data from several studies
and found to be similar enough to conclude that the model can be
trusted and applied. A convergence analysis showed that 1000
iterations are required to produce these reliable results. This
paper discusses the development of the tool, its performance as
well as the deviations found between its output and measurements
on the average occupancy of the different occupancy types.
Further research on occupancy patterns of different job function
types would improve the model as well as extend its applicability.
several resolution levels. To aid lighting designers in choosing the
appropriate solution for a specific open-plan office case, this paper
presents a simulation tool which enables calculating the lighting
energy use for the different control strategies. By using a stochastic
modelling approach and input parameters as users’ function type,
the office’s policy and special absences, the model could reflect the
actual occupancy behaviour in the office at hand. The results of
the model were validated with occupancy data from several studies
and found to be similar enough to conclude that the model can be
trusted and applied. A convergence analysis showed that 1000
iterations are required to produce these reliable results. This
paper discusses the development of the tool, its performance as
well as the deviations found between its output and measurements
on the average occupancy of the different occupancy types.
Further research on occupancy patterns of different job function
types would improve the model as well as extend its applicability.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017 |
| Editors | Antonio Guerrieri, Giancarlo Fortino, Athanasios V. Vasilakos, MengChu Zhou, Zofia Lukszo, Carlos Palau, Antonio Liotta, Andrea Vinci, Francesco Basile, Maria Pia Fanti |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 476-481 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-5090-4429-0 |
| ISBN (Print) | 978-1-5090-4430-6 |
| DOIs | |
| Publication status | Published - 16 May 2017 |
| Event | 14th IEEE International Conference on Networking, Sensing and Control (ICNSC 2017) - Calabria, Italy Duration: 16 May 2017 → 18 May 2017 Conference number: 14 http://icnsc2017.dimes.unical.it |
Conference
| Conference | 14th IEEE International Conference on Networking, Sensing and Control (ICNSC 2017) |
|---|---|
| Abbreviated title | ICNSC 2017 |
| Country/Territory | Italy |
| City | Calabria |
| Period | 16/05/17 → 18/05/17 |
| Internet address |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Convergence analysis
- Energy consumption
- Occupancy patterns
- Occupancy spread
- Stochastic modelling
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