Abstract:
The lighting retrofit method is adopted as one of the solutions to reduce lighting energy consumption
and improve lighting quality in existing buildings. Lighting controls and energy-efficient light sources
are used to achieve the goals of the lighting retrofit. Nowadays, Light-Emitting Diodes (LEDs) are
replacing traditional lighting technology owing to their high efficiency and longevity. One of the
advantages of LEDs is the controllability function, which allows users to set the light level according
to their preferences. This saves more energy and satisfies users’ lighting needs. However, over time,
the performance of lighting retrofit projects deteriorates subject to failure of the retrofitted lights.
Therefore, to maintain the performance of lighting retrofit projects, maintenance must be planned and
performed.
The impacts of the users’ lighting level requirements on LEDs’ life characteristics and lighting system
performance are investigated by using lighting controls. Light and occupancy sensors adjust artificial
light to the light level required by users and detect the presence of users in the zones, respectively.
Light sensors measure the average illuminance in the zones. The measured illuminance is compared to
the users’ set illuminance; if the measured illuminance is higher than the users’ set illuminance, lamps
are dimmed to meet users’ lighting preference, when the measured illuminance is less than the users’
set illuminance, lamps in the zone are replaced by new ones. The dimming level in each zone at each
sampling interval is used to estimate the operating junction temperature, thereafter the degradation
rate and luminous flux are calculated. Light levels at workspace are modelled using the lumen method.
This model helps to quantify energy savings and predict when lamps will fail to deliver the required
light levels. In existing studies, users’ lighting level requirements are neglected when investigating
the lifetime of the lighting system; however, users’ profile and driving schemes affect the operating
conditions of a lighting system. From the simulation results, it is noted that lumen output degradation
increases when the user’s set illuminance is above the illuminance required under normal operating
conditions and decreases when the user’s set illuminance is below the illuminance required under
normal operating conditions. Increased lumen output degradation shortens the lifetime of LEDs and
reduces energy savings, while decreased lumen output degradation extends the lifetime and increases
energy savings.
Generally, lighting retrofit projects contain a large lighting population; investigating when each lamp
will fail can be time-consuming and costly. In this research, a mathematical model is formulated to
model LEDs’ failure by analysing the statistical properties of the lumen degradation rates. Based on
the statistical properties of the degradation rates, the cumulative probability of failure distribution
and the survival function are modelled. The formulated survival function is incorporated into the
lighting maintenance optimization problem to balance energy savings and maintenance costs. A case
study carried out shows that, in 10 years, the optimal lighting maintenance plan would save up to
59% of lighting energy consumption with acceptable maintenance costs. It is found that the proposed
maintenance plan is more cost-effective than full maintenance. It is concluded that lumen degradation
failure should be considered when investigating the performance of lighting retrofit projects, as this
may not only affect energy savings but also reduce the level of illumination, which can cause visual
discomfort.
The initial investment costs of LEDs are still a barrier to the implementation of LED lighting systems
in residential buildings. Energy-efficiency projects often face hurdles to access capital investments
because decision-makers and funders do not have enough information about operational savings the
project can provide and specific financial requirements applied to efficiency investment. In this research,
an optimization model is formulated to give decision-makers and funders detailed information about
the performance and operational savings that a LED lighting retrofit project can offer and its economic
viability. The lumen degradation failure model developed is used to monitor and estimate the energy
savings, and the optimal maintenance plan is scheduled to replace failed lamps. In the existing studies,
the economic analysis of the lighting retrofit projects is assessed based on lighting population decay
due to burnout failure while in this research economic analysis is assessed by considering the lumen
degradation failure. The case study results show that the substitution of halogen light bulbs with
LED light bulbs could save up to 291.4 GWh of energy consumption, and reduce 273:92 103 tons
of CO2 emissions over 10-year period. The optimization model formulated is effective to help the
decision-makers and funders to quantify the savings and assess the economic viability of the LED
lighting retroïnˇA˛t project. This optimization model can help the decision-makers and funders to make
an informed decision.