1. Introduction
In today’s world, one of the main challenges in buildings is the challenge of energy consumption. In this regard, artificial lighting is known as one of the major factors in energy consumption. Studies show that buildings are significantly dependent on artificial lighting, and due to this dependence, it constitutes almost 40% of the global annual electricity consumption [
1]. Educational buildings, classified as non-residential structures, represent 17% of total energy consumption [
2]. Of this amount, across various components of educational buildings, classrooms account for approximately 50% of total energy consumption [
3]. Studies have shown that energy consumption in schools varies widely and can range from 86 to 272 kWh per square meter. These differences are due to the design, construction, and operation of the buildings [
4]. Additionally, it is reported that 93% of energy consumption in schools comes from electricity, while only 7% is from fossil fuels, including gas. This data highlights the need for strategies to optimize energy consumption and reduce dependence on fossil resources [
5]. Research has shown that by using different lighting control methods, significant energy savings can be realized. Estimates suggest that these savings can reach 50% or more. This not only reduces energy costs but also advances environmental sustainability by conserving natural resources and cutting greenhouse gas emissions—potentially by 40% in educational buildings with optimized designs [
6]. While lighting design encompasses both natural and artificial sources, this study focuses specifically on artificial lighting optimization due to prevalent daylight obstructions in urban educational settings, such as those in dense cities like Taipei, where surrounding structures limit natural light availability. Although daylighting through windows or clerestories could enhance energy efficiency, its practical integration is constrained in this context, prompting a targeted investigation into artificial solutions. This work serves as a foundational step toward holistic classroom design, with plans to incorporate broader environmental factors like daylight, ventilation, and acoustics in future research, building on the artificial lighting framework established here.
In building design, in addition to considering energy issues, one of the key principles is to create a sense of comfort and security for the occupants. To achieve sustainable design, approaches must optimize energy consumption while ensuring occupant comfort and well-being. Visual comfort, as an essential element of indoor environmental quality, plays a critical role in reducing fatigue, improving health, alertness, and attention, and increasing satisfaction with indoor environments [
7]. Among key parameters affecting visual comfort, glare control is especially important [
8]. Glare—categorized into discomfort glare and disability glare—can reduce concentration, efficiency, and visibility, leading to long-term health issues. Accurate measurement of discomfort glare remains challenging due to its subjective nature, necessitating tools like the Unified Glare Rating (UGR) and Visual Comfort Probability (VCP) for assessment [
9].
Given the dual priorities of energy efficiency and visual comfort, this study investigates two main parameters: height and surface reflectance, which are critical variables in classroom lighting design. The primary contributions include developing an integrated approach to balance energy use, glare, and light uniformity, offering actionable design guidelines for urban classrooms where artificial lighting dominates—a gap underexplored in prior work. The primary objective is to integrate these variables to achieve optimal lighting solutions that enhance visual comfort while reducing electrical energy demand.
Literature Review and Research Gap
In the context of visual comfort and energy efficiency, due to the importance of lighting on electrical energy consumption and user health, many studies have been conducted by researchers in this field.
Studies show that factors such as ceiling height, surface reflectance, and lamp configurations are influential on both topics.
Prior research has extensively explored energy-saving strategies in lighting systems. Studies highlight that the choice of lighting technologies can significantly impact the management and optimization of energy consumption. Replacing traditional light sources with energy-efficient lighting technologies, such as light-emitting diodes (LEDs), is considered a strategy to enhance energy savings in spaces and improve visual comfort [
10,
11,
12]. Studies also show that automated lighting controls [
13,
14,
15,
16] and lighting retrofits can reduce energy use by 29–38% in educational buildings [
17]. For instance, Hassouneh et al. [
18] demonstrated that dimmers could save 10–60% of energy depending on space type and usage patterns. Recent studies reinforce these findings. In 2023, Alfaoyzan and Almasri [
19] reported a 44% reduction in university building energy use with LED and sensor upgrades, while in 2024 Miranda et al. [
20] achieved 35% savings in classrooms by integrating LEDs with daylight controls, though their focus included unobstructed settings, unlike the urban constraints in this study.
Height is also a key parameter in lighting design, directly affecting the number of lamps, light uniformity, and energy consumption. Studies show that as ceiling height increases, the distance between the light source and the work surface increases, necessitating the use of more or higher-powered lamps to compensate for reduced illuminance. For example, in a study where ceiling height varied from 2.5 to 4.5 m, it was found that every 0.5 m increase in height requires 8–10% more lamps to maintain the desired level of illumination [
21].
Similarly, in a study by Ciampi et al. [
22], the performance of lighting in a historic building was investigated, and low-cost solutions for saving energy were proposed. The results of the study show that as the height is reduced, the number of lamps required for lighting also decreases, resulting in a reduction in the number of lamps by between 19.5 and 23.5%.
In another study, it was shown that increasing the height from 2.5 to 3 m leads to an 8 to 10 percent increase in lamps required to achieve the necessary 500 lux, and the author also replaced semi-direct LED lamps with asymmetric lenses instead of fluorescent lamps, resulting in a 20% reduction in electrical energy consumption while meeting the UGR standard limit of less than 19 [
23]. Alshibani [
24] further validated this, reporting an 8–10% increase in lamp demand with a 0.5 m height increase in school buildings, emphasizing height’s role in energy trade-offs.
In another study using virtual reality simulations, it was shown that classrooms with a ceiling height of 4.8 m require 17.3% more lamps to achieve similar performance scores compared to a ceiling height of 3 m. This increased need for lamps is due to reduced light uniformity in taller ceilings [
25].
Another study emphasizes increased learning performance in classrooms below 3.5 m due to reduced light scattering [
26].
Visual comfort has also been a focal point, with glare control emerging as a critical factor. Architectural features such as window design, surface reflectivity, and material choices significantly influence light distribution and glare.
A study by Jafarian et al. [
27] has shown that the choice of wood for interior surface finishes can influence the uniformity of light and overall lighting quality in a space. Additionally, a study by Michael et al. [
28] suggests using light-colored and reflective materials for furniture to enhance the distribution of light indoors. Furthermore, research by Makaremi et al. [
29] shows that the reflective properties of interior surfaces, particularly walls, play a significant role in enhancing light uniformity.
Other studies indicate that adjusting the reflectivity of interior surfaces (ρ) and the transmittance coefficient of windows (τ) significantly impacts energy consumption and light quality [
30].
In this regard, another study reported a 32.6% reduction in artificial lighting energy consumption using glass with a transmittance coefficient of 0.8 and horizontal shading devices [
31].
In another study, titled “Efficient Daylighting: The Importance of Glazing Transmittance and Room Surface Reflectance”, the author focused on vertical illuminance and wall reflectance (70–80%) for circadian rhythms. To maintain 300 lux in a room, it is suggested that for rooms with a height of 3 m or more, adaptive glazing that allows 80% of sunlight to pass through (τ = 0.8) be used to ensure comfort for users and keep glare below 19.
In this study, the combination of increasing the wall reflectance coefficient (ρ = 80%) with optimized lamp density resulted in a 32% reduction in energy consumption [
32].
In another study titled “
Effect of Surface Reflectance on Lighting Efficiency in Interiors”, it was shown that a 10% increase in ceiling reflectance (from 70 to 80) results in a 15 to 18% reduction in lighting power density (LPD). Additionally, increasing floor reflectance (ρ = 40–50%) leads to a balance between energy consumption and visual comfort by reducing glare [
33]. Baglivo et al. [
34] extended this, demonstrating that a 90% ceiling and 80% wall reflectance in schools reduced LPD by 32%, highlighting the synergy of reflectance and artificial lighting in obstructed environments. Beyond artificial lighting, daylighting’s potential in unobstructed classrooms has been explored; for instance, in 2023, Papadakis, N. and Katsaprakakis, D. A. [
35] showed that reflective surfaces and shading reduced energy use by 62–77% in Mediterranean schools, suggesting a need for comparative studies across classroom types—an aspect deferred here to focus on urban constraints.
Despite the undeniable effects of surface reflectance and height on light quality and their impact on energy consumption, and despite the advancements made in previous research, the following limitations exist in the literature:
- -
Unidimensional focus on parameters: Most studies have only examined separate factors such as lamp configurations, surface reflectivity, or ceiling height, ignoring the combined effects of these parameters on multi-objective criteria (such as light uniformity, glare control, and energy consumption).
- -
Focus on natural light: Although the impact of architectural features (such as surface reflectivity) on natural light has been widely examined, the role of these parameters under artificial lighting conditions is still not fully recognized. Recent work, such as that of Awang, Mariah et al. [
36], achieved 40% savings with smart controls but overlooked height and reflectance interactions, reinforcing this gap.
- -
Lack of integrated frameworks: The simultaneous impact of ceiling height, surface reflectivity, and lamp density on energy consumption and visual comfort has rarely been analyzed. Moreover, broader classroom design considerations—such as acoustics or unobstructed layouts—are seldom integrated with lighting studies, limiting applicability to diverse educational settings.
This research introduces a novel, holistic approach by investigating the combined influence of height, surface reflectance coefficients, and the number of lamps on classroom lighting performance. Key contributions include (1) quantifying the synergistic effects of height and reflectance on energy and glare control in artificial lighting contexts, (2) providing optimized design parameters for urban classrooms with limited daylight, and (3) laying a foundation for future multi-parameter studies incorporating daylight and acoustics.
To this end, a mixed simulation-statistical methodology was employed to answer three key questions:
- (1)
How does the combination of surface reflectance coefficients (ceiling, wall, floor) and room height affect the performance of the lighting system?
- (2)
What combination of surface reflectance coefficients within the specified range of the EN 12464-1 standard [
37] has the best impact on the design case being investigated (classroom), and what has been the impact of each surface?
- (3)
How can a balance be created among the conflicting criteria of illumination, glare, and energy consumption?
In this regard, simulations were initially conducted using Dialux software for two different heights (2.5 and 3 m) and various combinations of reflectance coefficients. Then, using extensive simulations (100 scenarios) with correlation analysis and multiple regression analysis in Excel, the correlation and contribution of each parameter to changes in performance criteria were quantified.
The results showed that high-reflectance surfaces (e.g., ceilings: 90%, walls: 80%) can reduce lighting power density (LPD) while maintaining illuminance uniformity. This led to the interaction of height parameters with the demand for lamp quantity and uniformity.
The results indicated that at a height of 2.5 m and a combination of ceiling reflectance at 90%, wall reflectance at 80%, and floor reflectance at 40%, along with 12 semi-direct lamps, not only does it provide uniform lighting of 500 lux, but it also limits glare to below the threshold of 19 UGR. This research also demonstrated that intelligent design and establishing interactions among various parameters not only lead to over 40% energy savings and cost reductions but also have a significant impact on reducing carbon emissions (e.g., 300.67 kg CO2/year per classroom) while ensuring visual comfort through effective glare control (UGR < 19), as validated through 100 detailed simulations and advanced statistical analyses.
Furthermore, the findings highlight the critical interplay between design parameters and provide specific guidelines on multi-objective criteria (glare control, light uniformity, energy consumption) that can serve as a useful guide for lighting designers and engineers to design more efficient and sustainable lighting systems by considering all influencing factors.
2. Materials and Methods
This research is based on a classroom at the National Taipei University of Technology as a sample to evaluate the parameters under investigation, including glare and energy consumption. To achieve this goal, Dialux evo 12.1 software (DIAL GmbH, Lüdenscheid, Germany) was used.
Although this study is based on a typical classroom environment found in many educational institutions, the classroom examined in this research is located in the Sixth Academic Building. The position of the building is shown in
Figure 1.
The selected classroom has dimensions of 8 m × 7 m (56 m
2) with ceiling heights of 2.5 m and 3 m, chosen because these reflect typical urban university classroom sizes in Taiwan, aligning with NTUT architectural standards and common educational building layouts [
38]. These dimensions accommodate 24 students, consistent with average class sizes in higher education, and the height range (2.5–3 m) represents standard ceiling heights in modern and renovated school buildings, allowing us to test height’s impact on lighting design [
21]. Classrooms in this building face serious limitations in utilizing natural light, even during daylight hours and peak usage times, due to its proximity to the tall Hong-Yue Technology Research Building, which is directly in front of its windows. To address daylight potential and its limitations an initial daylight assessment was conducted for this classroom using Dialux. Simulations evaluated daylight availability at noon (12 p.m.) under two conditions: with obstruction (adjacent Hong-Yue building) and without. Per EN 12464-1 standards [
37], a classroom for adult education requires 500 lux. Without obstruction, daylight provided an average of 239 lux ranging from 31.4 to 1853 lux as shown in
Figure 2, where the color scale represents illuminance levels (in lux), with blue indicating lower values and orange indicating higher values, falling short of the standard due to Taiwan’s predominantly cloudy and rainy climate, where overcast conditions prevail approximately 60% of the year [
5]. This variability, combined with the site’s latitude (25° N), limits daylight reliability, though it reduces artificial lamp demand during daytime compared to obstructed conditions. With obstruction, daylight contribution dropped to an average of 1.66 lux ranging from 0.19 to 0.66 lux, as shown in
Figure 3, where the color scale represents illuminance levels (in lux), with dark blue indicating lower values (around 0.19 lux) and lighter shades indicating higher values, a reduction of over 99% in illuminance. This near-total loss renders the classroom dark during the day, necessitating full reliance on artificial lighting,
Figure 4 and
Figure 5 show light distribution renderings in both positions. These findings reflect a broader urban challenge in Taiwan, where narrow streets, dense building layouts, and close proximities—often less than 5 m apart—obstruct daylight in many structures, as observed in Taipei’s compact urban fabric [
40]. Consequently, this study prioritizes artificial lighting strategies to ensure visual comfort and energy efficiency, addressing real-world constraints in such urban educational environments.
2.1. Lighting Standards
To design indoor lighting for various applications, specific standards must be followed. EN 12464-1 [
37] specifies that for different applications in educational buildings, the required illuminance varies from 300 lux to 750 lux, depending on the type of usage, as shown in
Table 1 [
20]. This study focuses on the lighting design for a university classroom intended for adults, including evening classes.
2.2. Research Methodology Framework
This study employs an integrated three-phase methodology combining lighting simulation, statistical analysis, and energy performance calculation:
Phase 1: Lighting Simulation in Dialux
- -
Collected all case study parameters (room dimensions, surface reflectance, luminaire specifications).
- -
Conducted validation tests comparing simulated vs. measured data.
- -
Performed main simulations under two ceiling heights (2.5 m/3 m) with varying reflectance coefficients.
Phase 2: Statistical Analysis
- -
Applied multiple linear regression in Excel to quantify parameter impacts.
- -
Conducted ANOVA to verify model significance.
Phase 3: Energy Performance Calculation (IPMVP Option A)
Energy savings were quantified following the International Performance Measurement and Verification Protocol (IPMVP) using a three-step approach:
- -
N = Number of luminaires
- -
P = Power per luminaire
- -
= Daily operational hours
- -
= Monthly working days
- 2.
Operational Savings Calculation
where
is consumption in optimized scenarios
- 3.
Carbon Emission Reduction
where
= 0.5 kg/kWh
2.3. Unified Glare Rating (UGR)
The UGR (Unified Glare Rating) is one of the most important goals of lighting design, aiming to create an environment with the least amount of glare. The UGR serves as a standard index for quantitatively assessing glare in indoor environments. Since glare can lead to decreased concentration, eye fatigue, and consequently reduced productivity, designers can create a more efficient and comfortable environment for occupants by controlling UGR. Many factors can influence the UGR value, including the type of light source (size and shape), the reflectivity of surfaces, and the observer’s position. The UGR calculation formula is based on the GUT model and is calculated as follows:
= background luminance (cd/m2), excluding the contribution of the glare sources.
= luminance of the luminaire (cd/m2).
3 = solid angle subtended at the observer’s eye by the luminaire (steradians).
p = Guth position index.
The UGR values can range from 10 to 30, each carrying different meanings regarding glare assessment, as shown in
Figure 6.
The UGR lower 16 is considered good, and up to 19 is acceptable, although it indicates higher glare levels. However, 19 is the threshold; values above this lead to increasing discomfort due to glare, reaching the “annoying” and “uncomfortable” levels, thus becoming unacceptable for suitable design. While 10 to 16 is good and up to 19 is acceptable, lower UGR values are preferable, indicating less glare. Therefore, various standards, such as CIE 117 [
41], provide specific definitions for different UGR values [
20], as presented in
Table 2.
There are also software tools available that allow designers to evaluate lighting quality before the actual project implementation. These software tools measure the UGR, including AGI32, Revit, and Dialux. Among these, Dialux, which specializes in lighting design, is one of the most reputable software for evaluating lighting and the UGR, allowing for optimized lighting design through simulation [
15,
42].
2.4. Lighting Setup
As mentioned, this research involved simulations performed using Dialux software (version 12.1). The research design was experimental–analytical. The independent variables in this research included room height and reflectance coefficients of the ceiling, walls, and floor. The steps were carried out as follows:
2.4.1. Project Information Collection
As stated earlier, this study simulated a real classroom at the National Taipei University of Technology in Taipei. The room’s dimensions are detailed in
Figure 7. A rectangular room with dimensions of 8 by 7 m has an area of 56 square meters. It can accommodate 24 students, and the room is designated for adult education at the university, with classes held in the afternoons as well. The height of the room varied across two scenarios: one scenario with a height of 2.5 m and another scenario with a height of 3 m. The calculations focused solely on artificial lighting conditions, excluding natural light.
Different surfaces have varying degrees of light reflectance, which impacts how light is distributed and, consequently, the overall appearance of the space. Reflectance coefficients significantly affect glare and brightness in a location. The European standard EN 12464 [
37] specifies appropriate reflectance ranges for ceilings, floors, and walls, as shown in
Table 3 [
43]. In this research, each scenario was initially set with the lowest standard limit and then evaluated at the highest standard limit.
2.4.2. Lamp Selection
Dialux software provides a comprehensive library of various lamps and their specifications for different applications, facilitating the selection of the appropriate option. The lamp selected for this study is an Indirect/Direct LED lamp with a power rating of 29.0 W, chosen after comparing it with alternatives like 36W fluorescent lamps (80–100 lm/W) and higher-wattage LEDs (e.g., 40 W, 110 lm/W). The 29W LED, manufactured by Current, offers superior luminous efficacy (124.1 lm/W) compared to fluorescents (20–30% less efficient), reducing energy use, and its indirect/direct design minimizes glare (UGR < 19) more effectively than direct-only lighting. It also provides a Color Rendering Index (CRI) of 80, ensuring accurate color perception critical for educational settings, and a Correlated Color Temperature (CCT) of 3500K, offering a warm yet neutral tone that balances comfort and alertness per EN 12464-1 standards [
37]. Higher-wattage LEDs (e.g., 40 W) were avoided as they exceeded the required 500 lux, wasting energy without improving comfort, while lower-wattage options (e.g., 20 W) risked insufficient uniformity. Its availability in Dialux’s library ensured accurate simulation. The light distribution curves are illustrated in
Figure 8. The lamp configuration was manually arranged in a grid pattern to ensure uniform illuminance of 500 lux across the 56 m
2 classroom area, meeting EN 12464-1 standards [
37]. This manual approach optimized lamp numbers (9–15) based on height and reflectance variations, ensuring even light distribution and glare control tailored to desk layouts, unlike automated placement, which might not account for specific classroom needs. According to the given standards, light can be positioned in the space either manually or automatically in Dialux. For this research, manual positioning was utilized. The classroom standards were entered into Dialux based on
Table 1, and manual methods were employed for light distribution.
2.4.3. Glare Assessment
To evaluate glare within the classroom using Dialux, two methods exist: the Surface Calculation method and the Point Calculation method. The Point Calculation method is primarily used for assessing glare on a specific object and point. Since this study aims to calculate the overall glare in the classroom, the Surface Calculation method was employed. The Concluding Surface method in Dialux 11 was utilized, which involved the following:
- -
Drawing a rectangle covering all desks.
- -
Considering a step width of 15 degrees for seated students, allowing for eye movement without head lifting.
- -
Viewing angles ranged from 0 to 180 degrees, representing a full-frontal view.
Glare calculation points were established at 9 points on the x-axis and 8 points on the y-axis, which were automatically suggested by Dialux. However, the number of points can also be manually adjusted, typically based on the number of rows and objects present. Alternatively, the automatic suggestions from Dialux, which usually propose more points, can be accepted. UGR measurements were taken at an eye level of 1.2 m, corresponding to seated students (
Figure 9).
4. Discussion
The aim of this research was to achieve optimal indoor lighting for a classroom, focusing on a design that balances visual comfort and energy efficiency. While previous studies have primarily focused on the single-factor impact of parameters such as height or surface reflectance [
11,
29,
44], this study addressed the complex interaction of three factors—height, surface reflectance, and the number of lamps—to achieve optimal design in a classroom. Previous studies have highlighted the importance of research in providing well-lit indoor environments, especially in settings such as educational and office spaces where individuals spend considerable time and require adequate concentration.
Studies indicate that in today’s world, 20% of individuals spend most of their time indoors under low or inappropriate lighting with minimal physical activity, leading to irregular and short sleep patterns. These factors can disrupt chronobiology, potentially resulting in fatigue, mood disorders, and reduced cognitive function. Research also suggests that prolonged chronodisruption may indirectly increase the risk of cardiovascular diseases through stress and metabolic changes [
45,
46], though direct evidence linking lighting alone to such outcomes remains limited. Furthermore, chronodisruption can negatively affect melatonin and cortisol levels, with cortisol being a regulator of stress-related functions. Proper lighting conditions are a crucial factor in achieving an optimal indoor environment [
45,
47]. Studies on the impact of lighting on students have shown that adequate lighting in educational environments not only positively affects students’ learning and performance but also contributes to improving their psychological and physiological well-being [
48,
49,
50]. Conversely, inadequate lighting can lead to temporary physiological issues such as headaches and concentration problems [
40,
51,
52], as well as psychological issues that negatively affect mood and motivation. In severe cases, it can even lead to permanent problems such as damage to the visual system [
40,
53]. Visual comfort indices examine the relationship between human needs and lighting conditions by considering four main factors: glare, uniformity, quantity, and quality of light. Controlling glare is a key parameter for achieving visual comfort [
54,
55,
56].
The present study demonstrated that optimizing the three factors—height, surface reflectance, and the number of lamps—can lead to up to 40% energy savings while maintaining glare control (UGR < 19). Our results revealed that ceiling reflectance contributes 50.9% to illuminance variance, while walls account for 32% and floors 17%, aligning with Makaremi et al. [
29] and Singh et al. [
33] on multi-surface reflectance effects. However, contrary to Montoya et al. [
11] and Ciampi et al. [
22] focusing solely on height reduction, we demonstrate that optimal lighting requires balanced reflectance ratios (ceiling:90%, walls: 80%, floor: 40%) combined with height adjustments to simultaneously control UGR (<19) and energy use.
In this research, in addition to complying with EN standards in terms of quantitative and visual parameters to achieve a standard design, the selection of lamps was also examined based on qualitative parameters CRI and CCT.
According to the specifications of the selected lamps, a CRI above 80 and a CCT of approximately 3700 Kelvin were recorded, indicating compliance with qualitative standards.
Furthermore, the selected lamps were of the semi-direct type, and in terms of glare—considered a visual parameter—even in the worst-case scenario between the two main scenarios, the glare level did not exceed the standard limit of 19.
This indicates the correct selection of lamp type and its compatibility with lighting design standards, as also shown in previous studies, which demonstrate that indirect lamps inherently provide better light dispersion in a space compared to direct lamps and produce less glare [
29].
Research indicates a correlation between uniformity and glare: higher uniformity reduces glare, while lower uniformity—when light dispersion in the room is insufficient—increases glare.
As observed in
Figure 32, a decrease in uniformity from 68 to 59 leads to a 35.7% increase in UGR (from 13 to 19). This finding aligns with studies [
44,
53] that report an inverse relationship between uniformity and glare. However, the innovation of this research lies in discovering the moderating role of surface reflectance. Increasing the reflectance of ceiling, wall, and floor surfaces can improve uniformity up to 67 and reduce UGR to 14, even at a lower height (2.5 m).
Studies also show that simple measures, such as reducing height, can decrease the number of lamps [
11], which aligns with the current study. If we compare the first case of the first scenario with the first case of the second scenario, both under the same conditions—namely, low reflection factors of ceiling, wall, and floor surfaces—only the height differs. In the first case of the first scenario, 15 lamps were installed at a height of 3 m, which even fell short of the required lux for the room. However, in the first case of the second scenario, 12 lamps were installed, which provided the necessary lux for the room. This means that the number of lamps was reduced by 20% due to the change in height.
However, it is noteworthy that when the height is greater, more lamps are needed to achieve the required lux in the room, despite having better uniformity. Conversely, when the height is lower, fewer lamps are required, but uniformity decreases, leading to an increase in glare.
As mentioned, changing the height resulted in a 20% reduction in the number of lamps. However, in terms of visual comfort, in the first case of the first scenario with a height of 3 m, we had better uniformity at 64 and glare at 16. In the first case of the second scenario with a height of 2.5 m, the uniformity was 59, which is slightly below the standard minimum of 60, and the glare was 19, which is at the threshold of the standard, meaning it is only acceptable. This indicates that at a height of 3 m compared to a height of 2.5 m, under equal testing conditions, the change in height had an impact of approximately 7.81% on uniformity and resulted in an 18.75% increase in glare, changing from 16 to 19.
To address the performance conflict between the number of lamps and visual comfort at height, the reflectance of surfaces is recognized as a key parameter in this research. Increasing the reflectance of ceiling, wall, and floor surfaces can effectively enhance light uniformity.
In both scenarios, as the reflectance of these surfaces increases, uniformity improves, leading to a reduction in glare. We observe an increase in uniformity from the first case to the second, and consequently, glare decreases.
By combining height reduction and increased reflectance, the third case of the second scenario is identified as the most optimal case in terms of energy and cost savings.
Table 16.
As shown in
Table 16, implementing the optimal scenario (2-3) not only reduces the initial cost by 40% but also achieves a saving of USD 781 over 10 years. This figure, scaled to a school with 20 classrooms, reaches USD 15,632, demonstrating the high economic viability of this design.
Increasing surface reflectance and reducing height not only reduces the demand for lamps and saves energy and costs but can also directly have a significant impact on reducing carbon emissions.
In the case studied in this research, conducted in Taiwan, the carbon intensity is considered to be 0.5 kg CO
2 per kilowatt-hour on average [
57].
To calculate the reduction in carbon emissions resulting from energy savings, we employed the following formula: (2)
- -
CER = Carbon Emission Reduction
- -
ES = Energy Savings
- -
CI = Carbon Intensity
As shown in
Table 6, energy savings of 300.67 kWh/year were achieved from scenario 1-1 to 1-3 and from 2-1 to 2-3 in each scenario. From 1-1 to 2-3 (combining increased surface reflectance and reduced height), energy savings reached 601.34 kWh/year. Based on the values obtained,
Table 17 shows the reduction in carbon emissions.
The results indicate that increasing reflectance alone (scenario 1-1 to 1-3) or reducing height alone (scenario 2-1 to 2-3) each leads to a reduction of 150.34 kg CO2 per year. The combination of reducing height and increasing reflectance (from scenario 1-1 to 2-3) results in a reduction of 300.67 kg CO2 per year, demonstrating a two-fold impact on carbon emission reduction.
These impacts are significant at larger scales; when scaled to 100 classrooms, this strategy could save 30.07 tons of CO
2/year, which is approximately equivalent to removing 6.5 gasoline-powered vehicles from the road annually. (Based on an average emission of 4.6 tons CO
2 per vehicle per year, [EPA]) [
46].
These findings highlight the importance of lighting design strategies with sustainability goals in educational buildings.
Although the third case of the second scenario is the most optimal in terms of energy, it has a UGR of 18 in terms of visual comfort, which, despite passing the standard, is very close to the undesirable threshold of 19. While this case can also be considered acceptable because it meets visual comfort standards, the second case of the third scenario, with a UGR of 14, is better within the standard. It only consumes 300 kWh more than the third case. If user visual comfort is the priority, this case is recommended. However, this case still achieved energy reduction compared to the initial state.
Present Study Limitations and Future Work
Simulation vs. Real World: The study used a simulation (Dialux) rather than a real classroom. Simulations, while useful, have limitations. For example, to assess the impact of human factors such as student interaction and behavior, further research in real classrooms is necessary to examine the effects of various strategies on users.
Artificial Light Focus: This research focused solely on artificial light due to the obstructed daylight in the selected classroom, caused by the adjacent Hong-Yue Technology Research Building. While daylighting via windows or clerestories could potentially double energy savings to 80% in unobstructed settings [
31], its exclusion isolates the role of artificial lighting in constrained urban environments. Future research should integrate these findings with daylighting strategies—such as optimizing window placement or adding clerestories—to maximize energy efficiency and enhance student well-being.
Limited Scale: This study was conducted on a single 8 m × 7 m classroom with obstructed daylight due to adjacent buildings. Generalizing the results to classrooms with different dimensions or unobstructed daylight access—such as those with larger windows or no nearby obstructions—requires further research. Future studies should include such classrooms for comparative analysis, evaluating artificial lighting against hybrid designs to broaden the applicability of these findings.
5. Conclusions
By examining the interaction of three crucial variables—height, surface reflectance coefficients, and number of lamps—this study aimed to optimize classroom lighting by balancing visual comfort and energy efficiency. Two main simulations were conducted with different ceiling heights (2.5 m and 3 m) and varying surface reflectance coefficients. Additionally, correlation and regression analysis of 100 scenarios were performed.
The results show that optimizing these factors can lead to significant improvements in both energy savings and visual comfort, with a potential 40% reduction in energy use while maintaining acceptable glare levels (UGR < 19).
Key Findings:
Impact of Surface Reflectance: The model’s good predictive power was indicated by the regression analysis’s R square of 0.969662. It was found that light intensity increases by 4.11 units for every unit increase in ceiling reflectance and by 2.5792 units for every unit increase in wall reflectance. Furthermore, light intensity rises by 1.375 units for every unit increase in floor reflectance. Light uniformity and glare were greatly enhanced by raising the reflectance coefficients of the floor, walls, and ceiling. the largest influence was caused by the ceiling reflectance (50.9%), which was followed by the walls (32.0%) and the floor (17.0%). It was discovered that the best surfaces for improving light distribution and lowering glare were those with high reflectivity (ceiling ≥ 85%, walls ≥ 80%, and floor ≥ 40%). Furthermore, the correlation analysis indicated that wall and ceiling reflectance coefficients do not correlate with one another, but they do have the strongest correlation with light intensity. This discovery gives designers greater creative freedom. Furthermore, in each case (from scenario 1-1 to 1-3 and from scenario 2-1 to 2-3), merely increasing the reflectivity of surfaces resulted in a 20% decrease in energy usage. These findings demonstrate important role of surface reflectance for both visual comfort and energy efficiency.
Effect of Height: By reducing the height from 3 m to 2.5 m, 20–25% fewer bulbs were needed, which resulted in a 20% energy decrease from scenario 1-1 to scenario 2-1. However, the necessity to balance height with reflectance and lamp placement is highlighted by the fact that this height reduction also slightly reduced uniformity and increased glare by 18.75%.
Energy Savings: This study achieved a 40% reduction in energy consumption by combining a higher surface reflectivity with a lower height. Only nine bulbs were utilized in the most energy-efficient scenario (scenario 2, case 3), which saved 601.34 kWh annually and reduced carbon emissions by 300.67 kg CO2.
When scaled to 100 classrooms this strategy could save 30.07 tons of CO2 a year, which is the same as taking 6.5 gasoline-powered vehicles off the road.
Economic Benefits: Compared to the baseline scenario, the optimized design (scenario 2, case 3) saved USD 781.60 over a ten-year period and reduced initial costs by 40%. Over ten years, this amounts to a USD 15,632 savings for a school with 20 classrooms.
Visual Comfort: Scenario 1, case 2 provided the best visual comfort, with a UGR of 13, high reflectance coefficients, and 15 bulbs. Scenario 2, case 2, with 12 lamps and a UGR of 14, is displayed to be the most balanced option, providing both energy efficiency and excellent visual comfort.
Recommendations for Design:
Prioritize Ceiling: To optimize light distribution and minimize glare, ceiling reflectance, as the top priority (with a 50.9% contribution to lighting), should be increased as much as possible to ≥85%.
Optimize Height:
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For glare-sensitive areas (such as children’s classrooms), use a height of 3 m while keeping surface reflectivity high, as this reduces the need for a greater number of lamps.
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Height of 2.5 m: The optimal option for reducing energy consumption by 20% to 25%, provided that high-reflectance surfaces are used. The combination of both reduced costs by up to 40% and provided a desirable UGR of 14.
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Lamp Placement: To obtain the required illumination and uniformity, use accurate simulations to determine the number of lights after determining the height and surface reflectance.
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Combined Strategies: To achieve the optimal balance between energy savings and visual comfort, use a mixture of lower height and higher surface reflectance (reflectance coefficients: ceiling 90, walls 80, floor 40), as recommended in this study.
Additionally, avoid high reflectance coefficients for the floor (30,40) while the reflectance coefficients for the ceiling and walls are below 80.
It should be noted that there is no single design that yields the best results in terms of energy and visual comfort. However, through the interaction of various parameters, optimal designs can be achieved, allowing for the best decisions based on the needs of the space and priorities. In this context, surface reflectance coefficients play a key role in creating interaction between the contradictions of height, the number of lamps, glare, and energy consumption, effectively acting as a controller. This allows glare issues to be managed at lower heights while controlling lamp demand at higher heights.
Concluding Remarks:
This research highlights the importance of a holistic approach to artificial lighting design, where energy efficiency and visual comfort are optimized simultaneously. By optimizing ceiling height, surface reflectance, and lamp placement significant energy savings and improved lighting quality can be achieved, contributing to both economic and environmental sustainability. These efforts reduce carbon footprints by 30.07 tons of CO2 annually across 100 classrooms, aligning with broader environmental goals. This study lays the groundwork for integrated design optimization, with future work planned to address additional factors such as daylight integration, acoustics, and thermal comfort, enhancing the overall classroom environment. These findings provide valuable guidelines for designing energy-efficient and visually comfortable educational spaces, with potential applications in other indoor environments as well.