Daylighting Strategies for Low-Rise Residential Buildings Through Analysis of Architectural Design Parameters
Abstract
1. Introduction
2. Materials and Methods
2.1. Qualitative Methods
2.2. Quantitative Methods
2.2.1. Experimental Method Using Illuminance Meter
2.2.2. Simulation Method Using DesignBuilder
3. Results
Correlation Analysis
4. Discussion
4.1. Limitations of the Study
- The study focuses solely on warm-humid climates, which limits how applicable their findings are. The best daylighting setups identified may not work in buildings located in temperate, cold, or hot-arid areas, where solar angles, cloud cover, and seasonal changes vary widely.
- Since this investigation focuses on a single case-study residence with its unique orientation constraints, urban obstructions, and window layout, the optimal configuration identified reflects the daylighting behavior of this specific building type. However, the core design principles can be adapted and applied to similar low-rise residential settings with comparable spatial and climatic conditions.
- Although climate-based daylight modeling was employed, the simulations depend on simplified assumptions that might not fully capture real-world conditions, such as furniture placement, shading adjustments, occupant details, or environmental shifts.
- The study assesses daylight quality using UDI, sDA, and ASE. Still, it does not consider other important factors, such as glare risk, thermal loads, or the interaction between daylighting and artificial lighting controls. As a result, the overall impact on energy use and visual comfort may be underestimated.
- Following LEED v4.1, this study assesses daylight performance using UDI, sDA, and ASE. However, metrics explicitly developed for residential settings—such as the RDS—are increasingly recommended for evaluating daylight sufficiency in dwellings, as they offer a more residential-specific perspective.
- Only one glazing transmittance value (VLT = 0.45) and a few skylight configurations were tested. Other glazing types, shading systems, or advanced daylighting devices (e.g., light shelves, diffusing skylights, dynamic glazing) were not examined, which limits the range of potential optimized solutions.
4.2. Recommendations
- Implement an SRR of 1:2 (equivalent to a 5% SRR) combined with a WWR of 22%. This setup offers the best balance of high UDI, adequate sDA, and low ASE, aligning with LEED v4.1 standards.
- Prioritize east-facing configurations with most windows on the north and south facades and few west-facing openings. When combined with appropriate shading and consideration of context, reflectance, and interior layout, this approach improves daylight performance while managing glare and heat gain.
- Use glazing with about 22% WWR and a VLT of 0.45 for low-rise buildings in warm and humid regions.
- Add effective shading devices to block direct sunlight and keep ASE at or below 10% to prevent visual discomfort.
- Prioritize placing most windows on the north and south facades to lower direct solar exposure and reduce low-angle glare.
- Reduce the size and number of windows on east and west facades, as these orientations allow low-angle morning and evening sun to increase ASE.
- If a south-facing orientation is needed, consider lowering the WWR to 15% along with the 5% SRR to maintain good daylighting while controlling glare. If using the 22% WWR for south, add strong glare-control measures such as advanced shading or selective glazing.
- Design to promote a positive relationship between sDA and UDI, ensuring that increased daylight autonomy comes with sufficient usable light.
- Manage the negative relationship between ASE and UDI actively to prevent too much sunlight from reducing effective daylighting.
- Use WWR and SRR as main controls for light intensity, focusing on how light is distributed and concentrated near windows.
- Shape the light environment through building orientation to maximize seasonal and diurnal light benefits.
- Implement an integrated design process that combines scatter plot trends (for visual analysis) and an objective function (for quantitative assessment) to support passive design decisions.
- While the optimal 22% WWR and 1:2 SRR configuration performed best for the studied residence, similar outcomes may differ in buildings with different layouts, obstruction patterns, or climate conditions. Therefore, refining façade proportions, shading details, and spatial layouts based on daylighting results to ensure consistent indoor lighting and reduce the need for artificial lighting can improve the clarity of tropical residential spaces.
5. Conclusions
- An SRR of 5% with a plan ratio of 1:2 met standards across all three daylight metrics (UDI, sDA, ASE), while other ratios performed well in sDA but exhibited glare issues based on scatter plot analysis.
- North-facing orientation with the same setup (22% WWR and 5% SRR) also performed well, providing high daylight autonomy with minimal glare, since windows face east and west, ideally for consistent, year-round indirect lighting with little discomfort.
- South-facing orientation showed promising results, especially with 15% WWR and 5% SRR, maintaining strong daylighting levels. However, glare mitigation strategies such as shading devices or selective glazing are recommended if choosing a 22% WWR in this orientation. Most windows on the north and south faces are preferred over those on the east and west to reduce glare, which is why east-facing windows are often paired with those on the north and south.
- Optimal window designs feature glazing with a 22% WWR and a VLT of 0.45, combined with effective shading devices to block glare and achieve an ASE of no more than 10%. While ASE does not directly measure glare perception, it is used here to assess potential visual discomfort from excessive illuminance.
- The east-facing orientation demonstrated the strongest performance, providing ample daylight with minimal glare, especially when most windows were on the south and north facades and fewer on the west.
- UDI was the primary metric for evaluating year-round daylight conditions, while ASE and sDA offered additional assessments aligned with LEED v4.1 standards.
- A positive correlation between sDA and UDI further suggests that higher daylight autonomy leads to better usable daylight levels, while the negative correlation between ASE and UDI highlights that too much sunlight can decrease effective daylight utilization.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| ASE | Annual sunlight exposure |
| DF | Daylight factor |
| DGP | Daylight glare probability |
| DR | Dining room |
| OF | Objective function |
| LEED | Leadership in energy and environmental design |
| LR | Living room |
| NBCI | National Building Code of India |
| sDA | Spatial daylight autonomy |
| SHGC | Solar heat gain coefficient |
| SRR | Skylight-to-roof ratio |
| U | Overall heat transfer coefficient |
| UDI | Useful daylight illuminance |
| VLT | Visible light transmittance |
| WWR | Window-to-wall ratio |
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| Room Typology | Size of the Room (m2) | Window-Vertical Dimensions (m) | Sill Height (m) | Wall Surface Area (m2) | Total Area of the Window (m2) | WWR (%) | Orientation of the Openings |
|---|---|---|---|---|---|---|---|
| Bedroom | 20.5 | 1.3 | 0.9 | 60.31 | 3.45 | 6.231 | north, west |
| Dining room (DR) | 14.12 | 1.3 | 0.9 | 45.62 | 1.22 | 3.331 | east |
| Kitchen | 10 | 0.7 | 0.9 | 33.28 | 0.61 | 2.565 | east |
| Living room (LR) | 30.16 | 1.3 | 0.9 | 62.16 | 2.34 | 4.401 | north and west |
| Room Typology | Average Indoor Illuminance | Outdoor Illuminance | Daylight Factor | Recommended Daylight Factor |
|---|---|---|---|---|
| 9 AM | ||||
| Bedroom | 35.275 | 4750 | 0.7447 | 1.5 |
| DR | 60.55 | 13,620 | 0.445 | 2 |
| Kitchen | 18 | 11,420 | 0.157 | 2.5 |
| LR | 9.874 | 7620 | 0.129 | 0.625 |
| 12 PM | ||||
| Bedroom | 52.676 | 5670 | 0.929 | 1.5 |
| DR | 111.95 | 8200 | 1.365 | 2 |
| Kitchen | 13.875 | 7450 | 0.186 | 2.5 |
| LR | 17.2 | 9450 | 0.182 | 0.625 |
| 3 PM | ||||
| Bedroom | 91.002 | 9910 | 0.918 | 1.5 |
| DR | 68.61 | 12,650 | 0.542 | 2 |
| Kitchen | 5.5 | 7290 | 0.075 | 2.5 |
| LR | 21.316 | 8230 | 0.259 | 0.625 |
| Metrics | Values |
|---|---|
| UDI | An acceptable illuminance range of 300–3000 lux for 90% of the space occupied hours (Spatial percentage) [56] |
| ASE | The percentage of floor area containing 10% or preferably ASE (LEED) v4.1 (>1000 lux for 250 h annually) [57] |
| sDA | 300 lux for 50% of the time the space is in use throughout the year [58,59] |
| Ambient bounces | 5 |
| Ambient accuracy | 0.22 |
| Ambient resolution | 512 |
| Sky patches | 3-1297-34 |
| Optimized Skylight-to-Roof-Plan Ratio | SRR Optimized | Orientation | WWR | WWR Modified Simulation |
|---|---|---|---|---|
| 1:1 | 4% | north, south, east, west | existing 3% | 15%, 22% |
| 1:2 | 5% | north, south, east, west | existing 3% | 15%, 22% |
| 1:1.5 | 8% | north, south, east, west | existing 3% | 15%, 22% |
| 1:1-double-high | 4% | north, south, east, west | existing 3% | 15%, 22% |
| Simulation Images Using DesignBuilder—WWR 15% | Simulation Images Using DesignBuilder—WWR 22% | ||
|---|---|---|---|
| 1:2 Ratio-5% | |||
| East | North | ||
![]() | ![]() | ![]() | ![]() |
| 91.00% | 91.10% | 90.29% | 91.00% |
| West | South | ||
![]() | ![]() | ![]() | ![]() |
| 91.20% | 91.8% | 90.87% | 90.70% |
Annual hours ![]() | |||
| Ref. | Tools/Methods Used | Metrics Evaluated | Major Findings |
|---|---|---|---|
| Sultana & Joarder [67] | Parametric modeling; Grasshopper; Octopus (MOO); Radiance; EnergyPlus | WWR; Lightwell geometry; Overhang depth; sDA; ASE; Mean illuminance | Uniform lightwell greatly improves daylight (36 → 377 lux), sDA (0.95% → 44.29%), and achieves an acceptable ASE; This introduces a framework for daylight–energy optimization in deep-plan tropical apartments. |
| Tao et al. [68] | Random Forest (RF); SHAP; Agent-Based Modeling (ABM) | WWR; Roof insulation; Wall insulation; Temperature rise rate | Roof insulation (28.3%), WWR (25.9%), and wall insulation (24.7%) are the most influential; high WWR and single glazing increase discomfort. |
| Kamalabadi et al. [69] | Bio-inspired adaptive façade modeling; Electrochromic glazing; Climate-based daylighting | SDA; UDI; Exceeded UDI; Adaptive façade parameters | A multi-layer kinetic and electrochromic façade achieves UDI 86–93%, and SDA > 55%. The bio-inspired and smart glazing outperforms individual adaptive systems. |
| Ukpong et al. [70] | Daylighting simulations; Static + climate-based metrics | Orientation; Shading; UDI; ASE | North–south orientation performs best; Optimal WFR ≈ 19%; Strong inverse ASE–UDI relationship; Climate-responsive daylighting guidelines are needed. |
| Atthaillah et al. [71] | Ladybug Tools; Radiance; Sensitivity analysis; Regression model | WWR; Horizontal shading depth; Shading elevation; Distance to adjacent building; Annual visual comfort | Top variables: shading depth, shading elevation, and east-side WWR. Optimal values are 2.6 m for shading depth, 2.7 m for elevation, and 10% for WWR. An adjacent building offset of ≥0.5 m improves daylighting. |
| The present study | On-site illuminance measurements DesignBuilder EnergyPlus | WWR (15%, 22%) SRR = 5% Orientation (E, N, S, W combinations) UDI, SDA, ASE | Optimal configuration: 5% SRR, 22% WWR, VLT 0.45, east-facing orientation → maximizes UDI and SDA while keeping ASE low. South orientation is viable with 15% WWR or shading if using 22% WWR. Window design with 22% WWR + VLT 0.45 maintains ASE ≤ 10%. Confirms evidence-based thresholds for warm-humid passive design; workflow supports code integration and future glare-focused improvements. |
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Kalaimathy, K.; Gopalakrishnan, S.; Shanthi Priya, R.; Selvam, C.; Senthil, R. Daylighting Strategies for Low-Rise Residential Buildings Through Analysis of Architectural Design Parameters. Architecture 2025, 5, 125. https://doi.org/10.3390/architecture5040125
Kalaimathy K, Gopalakrishnan S, Shanthi Priya R, Selvam C, Senthil R. Daylighting Strategies for Low-Rise Residential Buildings Through Analysis of Architectural Design Parameters. Architecture. 2025; 5(4):125. https://doi.org/10.3390/architecture5040125
Chicago/Turabian StyleKalaimathy, Kamaraj, Sudha Gopalakrishnan, Radhakrishnan Shanthi Priya, Chandrasekaran Selvam, and Ramalingam Senthil. 2025. "Daylighting Strategies for Low-Rise Residential Buildings Through Analysis of Architectural Design Parameters" Architecture 5, no. 4: 125. https://doi.org/10.3390/architecture5040125
APA StyleKalaimathy, K., Gopalakrishnan, S., Shanthi Priya, R., Selvam, C., & Senthil, R. (2025). Daylighting Strategies for Low-Rise Residential Buildings Through Analysis of Architectural Design Parameters. Architecture, 5(4), 125. https://doi.org/10.3390/architecture5040125










