Daylight adaptive optimal lighting system control strategies for energy savings and visual comfort in commercial buildings
Artificial lighting of commercial buildings in Malaysia consumes 21% of the total electrical energy. Therefore, reducing the energy is required to achieve sustainable buildings (i.e., higher energy efficiency and visual comfort), by implementing optimal light sensor placement method and optimi...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English English English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4124/1/24p%20KHAIRUL%20RIJAL%20WAGIMAN.pdf http://eprints.uthm.edu.my/4124/2/KHAIRUL%20RIJAL%20WAGIMAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/4124/3/KHAIRUL%20RIJAL%20WAGIMAN%20WATERMARK.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Artificial lighting of commercial buildings in Malaysia consumes 21% of the total
electrical energy. Therefore, reducing the energy is required to achieve sustainable
buildings (i.e., higher energy efficiency and visual comfort), by implementing optimal
light sensor placement method and optimisation-based control strategy. However, in
recent works related to light sensor placement, energy performance and illuminance
uniformity (Uo) are not considered, and the results did not provide the optimal number
of sensors to be employed. To optimise power consumption (PC) and visual comfort
simultaneously through the optimisation-based control strategy, the previous work
developed a visual comfort model to represent Uo. However, the model did not
consider daylight and the results of Uo need further improvement. This research
proposes: (1) a new optimal light sensor placement method (OLSPM) by using
combined particle swarm optimisation (PSO) and fuzzy logic controller (FLC) denoted
as OLSPM-PSOFLC, and (2) a new visual comfort metric called illuminance
uniformity deviation index (IUDI) and incorporated with multi-objective PSO
(MOPSO) for solving energy consumption and visual comfort problem. The OLSPM�PSOFLC is developed to determine the optimal number and position of light sensors
by considering PC while satisfying average illuminance level (Eav) and Uo. To ensure
both PC and Uo in the room are always at the optimum levels, the IUDI with MOPSO
is developed. Before the proposed methods are implemented, retrofitting lighting
system is implemented first to determine the best lamp technology to be installed in
terms of technical and economic metrics. An actual office room is considered for
carrying out the proposed methods. The comparative results showed that the OLSPM�PSOFLC significantly reduced the number of sensors, energy consumption, carbon
dioxide emission, payback period, and life cycle cost were 66%, 23%, 23%, and 30%,
respectively, compared to the multi-sensor. Meanwhile, based on the comparative
study of the IUDI and CVRMSE, the IUDI showed superior performance with 6% and
27% improvement of Uo and energy savings, respectively. Based on their superiority,
the newly developed methods can be potentially implemented for all types of rooms
and are very useful methodologies towards sustainable commercial buildings. |
|---|