Window-to-wall Ratio Research Articles

Passive strategies for energy-efficient educational facilities: Insights from a mediterranean primary school

This study investigates the thermal and energetic dynamics of primary school classrooms in a Mediterranean climate in Khoualed Abdel Hakeem, Ain Temouchent County, Algeria. The research highlights significant optimizations by focusing on passive strategies such as external shading devices, Window-to-Wall Ratio (WWR), glazing types, and building envelope adjustments. Our simulations, validated rigorously, showcase a remarkable congruence with actual electricity consumption, affirming the reliability and efficacy of our simulation model as a valuable predictive tool. A Vertical Shading Angle (VSA) of 60° proves optimal, resulting in an impressive 11% reduction in Annual Energy Consumption (AEC). A recommended WWR of 30% demonstrates an 11% decrease in AEC and improves thermal and energy efficiency. Double Low Emissivity (Double-Low E) glazing is found to be superior, resulting in a significant 14% decrease in AEC. Achieving a WWR of 50% in shaded areas helps maintain a well-balanced thermal environment, resulting in a 12% reduction in heating and cooling requirements. The integration of passive strategies in the optimized model showcases a remarkable 44% overall reduction in energy consumption. The results highlight the efficacy of passive strategies, promoting energy-conscious and ecologically responsible practices, advocating for their incorporation in educational facilities, and offering valuable insights for sustainable school building design.

Multi-objective optimization of energy and daylight performance for school envelopes in desert, semi-arid, and mediterranean climates of Iran

Considering global warming as a critical challenge to human life, performance optimization of the building envelope can play a noticeable role to reduce a building's environmental footprint. Meanwhile, shading systems are considered as sustainable passive solutions to contribute to building energy efficiency, and daylight control in early-stage design. Nonetheless, a paucity of research has examined the various shading strategies in diverse climates, particularly arid desert and steppe regions, in conjunction with educational buildings. The present study aims to evaluate the role of fixed exterior shading systems (FESSs), and window-to-wall ratio (WWR) on building’ thermal and daylight performance in Iran with desert, semi-arid, and Mediterranean climates. Pareto Frontier and weighted-sum method for multi-objective optimization, and sensitivity analysis were used to study the optimum solutions, and the relationship between the design variables and the performance metrics. Three objective metrics including Spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE), and Energy Use Intensity (EUI), were defined as performance metrics. Shadings include vertical louver, horizontal louver, light shelf, overhang, and egg-crate. The results showed that EUI was reduced via FESS-integrated façade by 25.22%, 20.84%, 19.14%, 14.06%, and 13.47%, in Yazd, Bushehr, Kerman, Rasht, and Mashhad as selected studied cities, respectively. Based on ASE, the horizontal louver surpasses the other systems by 100% ASE value reduction in all climate zones except for Rasht. sDA level is reduced in all climate zones considering five studied FESSs excluding horizontal louver in Yazd and Rasht and overhang in Mashhad by 100% sDA level. Building energy performance simulation is validated by ASHRAE140-2020.

Wall-embedded micro heat pump for radiant heating in buildings: Evaluation of energy and thermal comfort performance

This paper presents a novel radiant heating system with a wall-embedded micro heat pump (WEMHP) for residential buildings. The interior surface temperature of the exterior wall-section empowered by the micro heat pump is independently controlled, enabling distributed thermal comfort delivery. The micro heat pump consists of a miniature compressor along with an aluminum roll-bond condenser and evaporator. In contrast to conventional hydronic radiant systems and heat pumps with separate indoor and outdoor units (i.e., split systems), the WEMHP is a “packaged” system that would not require on-site installation and charging of a secondary water loop and circulation pump or refrigerant piping. This could ultimately lead to reduced installation and maintenance costs. In this study, a detailed system model is presented and integrated with a single-zone building model to assess the energy performance of the WEMHP in heating mode. For a designed living room scenario with an external wall WEMHP-to-wall ratio (HPWR) of 0.6 and window-to-wall ratio (WWR) of 0.2, the simulation results show that up to 23 % energy savings compared with a baseline air-to-air heat pump are possible. The results also indicate the HPWR needs to be higher than 0.4 to achieve performance comparable to the baseline. Additionally, experiments were conducted in a laboratory environment in which surface temperatures were controlled to emulate different scenarios for integration of WEMHP technology and to evaluate thermal comfort conditions. The experimental results show that the median operative temperature differences in the indoor environment were within 0.5 °C for various locations while the largest radiant asymmetry was 2.2 °C for the designed room configuration. Moreover, simulations were conducted to evaluate thermal comfort conditions in applications having a smaller HPWR of 0.4 with various values of WWR. Overall, the combined simulation and experimental study shows that the WEMHP has potential to reduce energy use while maintaining thermal comfort at acceptable levels where the HPWR is higher than 0.4.

Multi-objective optimization of daylight illuminance indicators and energy usage intensity for office space in Tehran by genetic algorithm

One of the important categories in office spaces is the control of daylight and energy consumption. By controlling natural light, it is possible to provide uniform light in the entire space, sufficient daylight, and visual comfort for office workers. In many cases, this important issue can be resolved by choosing the right shading. In this study, the aim is to investigate the significance of some important parameters such as DoS (Depth of Shading), FO (Facade Offset), FSoS (Flip Start of Shading), LoS (Location of Shading), WWR (Window to Wall Ratio), CoS (Count of Shading), AoS (Angle of Shading), and HoW (Height of Window) in the optimal design of shading for an office environment in Tehran. For this purpose, eight variables have been designed and the aim is to improve the indicators of Energy Usage Intensity (EUI), Spatial Daylight Autonomy(sDA), Daylight Glare Probability (DGP), and Tc (Thermal comfort) in the office space. For optimization in the grasshopper environment, Wallacei’s algorithm was used. Then, the algorithm provides a set of optimal points. Then a point was selected as optimal by the WSM (Weighted Sum Method) method. According to the input variables that are DoS, FO, FSoS, LoS, WWR, CoS, AoS, and HoW its optimal point values are 0.4, 0, Up, Horizontal, 80, 5, 30, 0.5, respectively. The results show that the values of sDA, DGP, EUI, and Tc were improved by 43.6%, 52.77%, 13.9, and 3.696%, respectively, before and after shading optimization. Also, the annual glare and the hottest and coldest day of the year were checked where there were around 500(cd/m2) and 200(cd/m2) reduction of glare value in winter and summer seasons, respectively. Finally, the value of Useful Daylight Illuminance (UDI)before and after the installation of the optimal shading was 25.8 and 68.4, respectively.

Heat Loss Optimization of a Building with Different Window to Wall Area Ratios

Abstract The types of glass and exterior walls and the window-to-wall ratio (WWR) on building façades play a major role in heat losses that occur in every type of building, residential or commercial. The opaque and transparent surfaces of buildings have an important role in terms of both energy losses and energy gains. Windows are the parts of the building envelope where heat losses mostly occur. As the WWR increases on the façades of a building, heat losses increase, but heat gains from solar energy also increase, which assists in free heating of the building. In this study, a detached residential building located in Antalya, Turkey, a province with hot–humid climatic conditions, has been examined. A series of simulations were carried out to detect the effects of WWRs and different glass, frame, and exterior wall types on heat losses of the building. The heat loss values obtained from these simulations were processed by using a special mechanical installation calculation software. Simulations were performed for apartment rooms with levels of WWR ranging from 30 to 60 % of the wall areas facing the façade. In order to minimize heat loss, double-pane glass (or double-glazed glass) was used instead of single-pane glass. The aim of this study was to find the optimum value in terms of applicability and economy. The optimum value was calculated by minimization according to both the linear graphical method and the dual simplex optimization method. The values found in both methods were compared and interpreted. It is believed that the optimized glass, frame, joinery, and exterior wall parameters, which are influential to the energy performance of the building, will make a positive contribution to the architectural design phase in addition to improving the energy efficiency of existing buildings.

Façade feature extraction for urban performance assessments: Evaluating algorithm applicability across diverse building morphologies

Urban feature extraction methods have presented multiple opportunities in the field of environmental building performance studies, and urban assessments. With reference to façade features, window size and position are key parameters that influence occupant perception and environmental performance of indoor spaces. A myriad of methods have been proposed to automatically detect façade window layouts from street view images yet it is still unclear how to assess the strengths and limitations of these methods or how they can be combined for higher detection performance. This paper aims to add clarity for those aiming to use computer vision techniques for façade layout extraction for urban level sustainability assessments. An automated pipeline to enable the extraction and detection of WWRs (Window to Wall ratios) is introduced that is based on two fundamentally different computational approaches; a grammar-based edge detection framework (Method 1) and a learning-based method (Method 2) that utilizes CNNs (Convolutional Neural Networks). The paper then compares the detection efficacy of both methods, focusing on WWR accuracy, in New York and Lisbon, including their ability to extract more detailed façade properties such as floor-to-floor heights. The study finds that the learning-based method shows lower error scores across the two cities. In Lisbon, 69 % of conditions were detected within the 10 % error range and 91 % were within the 20 % range under Method 1. Under Method 2, 82.5 % of conditions were within the 10 % error range and 95 % were within the 20 % range. In New York, 66 % of conditions were within the 10 % error range and 90 % were within the 20 % range under Method 1 while 77.5 % of conditions were within the 10 % error range and 93 % were within the 20 % range under Method 2. Finally, a hybrid method is proposed to leverage the strengths of the two models, and higher accuracies are obtained in both the New York and Lisbon dataset. In New York, 96.5 % are now detected within the 20 % error range and 81.5 % within the 10 % error range. In Lisbon, 96 % are now detected within the 20 % error range and 83.5 % within the 10 % error range. With reference to the total building height extraction formulated under Method 2, the results show a relative error of 3.5 % in height estimation in the sample set.

Optimizing energy efficiency and thermal comfort of green envelope applications in hot arid climate

Climate change and unresolved environmental challenges in arid environments negatively affect urban development. Previous literature tackled the significance of ecological approaches and building envelope optimization as main pillars in reducing energy consumption and enhancing energy efficiency and thermal comfort in buildings. This study aims to tackle an environmental simulation of implementing green roofs and green walls as an ecological strategy applied to the building envelope with considerations of the window-to-wall ratio (WWR) in contribution to enhancing the built environment’s energy efficiency and thermal comfort. The main study aimed to define the optimum solutions for applying ecological approaches on a medium office building envelope to investigate the enhancement of thermal comfort and total site energy. Hot arid climatic data was selected for its recent environmental challenges, and building envelope design, relying on experimental simulation research, a model was simulated using Design-builder software using discomfort hours and total site energy as the main objectives. Heating and cooling were added as outputs in the optimization to monitor their effect on the indoors. The two main output parameters were the WWR and envelope construction. Then a percentage decrease in the running cost was addressed. The multi-objective optimization showed an effective positive impact of green roof application on the building in hot arid climate than that of the green wall, which highlights the significance of green wall implementation to environmental and economic sustainable developments in arid environments.

Optimizing the View Percentage, Daylight Autonomy, Sunlight Exposure, and Energy Use: Data-Driven-Based Approach for Maximum Space Utilization in Residential Building Stock in Hot Climates

This paper introduces a comprehensive methodology for creating diverse layout generation configurations, aiming to address limitations in existing building optimization studies that rely on simplistic hypothetical buildings. This study’s objective was to achieve an optimal balance between minimizing the energy use intensity (EUI) in kWh/m2, maximizing the views percentages to the outdoor (VPO), achieving spatial daylight autonomy (sDA), and minimizing annual sunlight exposure (ASE). To ensure the accuracy and reliability of the simulation, the research included calibration and validation processes using the Ladybug and Honeybee plugins, integrated into the Grasshopper platform. These processes involved comparing the model’s performance against an existing real-world case. Through more than 1500 iterations, the study extracted three multi-regression equations that enabled the calculation of EUI in kWh/m2. These equations demonstrated the significant influence of the window-to-wall ratio (WWR) and space proportions (SP) on the EUI. By utilizing these multi-regression equations, we were able to fine-tune the design process, pinpoint the optimal configurations, and make informed decisions to minimize energy consumption and enhance the sustainability of residential buildings in hot arid climates. The findings indicated that 61% of the variability in energy consumption can be attributed to changes in the WWR, as highlighted in the first equation. Meanwhile, the second equation suggested that around 27% of the variability in energy consumption can be explained by alterations in space proportions, indicating a moderate correlation. Lastly, the third equation indicated that approximately 89% of the variability in energy consumption was associated with changes in the SP and WWR, pointing to a strong correlation between SP, WWR, and energy consumption. The proposed method is flexible to include new objectives and variables in future applications.

Trade-Off Judgement for Daylighting and Energy Consumption in the High and Large Space of the University Gymnasium in Beijing

Taking the high and large space of the University of Science and Technology Beijing Gymnasium as this research object, this paper analyzes the influence of different window positions, window-to-wall ratio (WWR), solar heat gain coefficient (SHGC), heat transfer coefficient (K), and visible light transmittance (VT) on the total indoor energy consumption in winter and summer and obtains the relationship between the daylight factor and VT formed when the window is opened per unit area. Through energy consumption simulation, the variation law and calculation formula for indoor total energy consumption are obtained. The results show that the SHGC and K of the exterior window have a significant influence on the total energy consumption. By using the energy consumption simulation of different types of exterior windows, it is concluded that the SHGC of the south-facing window is negatively correlated with the variation of air conditioning energy consumption per unit area Δe1,w, while the others are positively correlated. Moreover, the SHGC and K of the skylight have the most significant influence on the Δe1,w. The total energy consumption decreases and then increases with the increase in the window area, and there is a lowest point, so the right side of the lowest point is less than or equal to 105% of the lowest total energy consumption as a reasonable window area zone. Finally, a progressive optimization method for weighing daylighting and energy consumption in university gymnasiums in Beijing is proposed.

Assessment of window renovation potential in an apartment with an energy performance approach

Abstract Windows are of great importance in improving the energy efficiency of buildings. It is possible to achieve this with the help of the regeneration of window design. The amount of energy used, the expense of heating and cooling, and the emissions of greenhouse gases that contribute to climate change can all be significantly reduced by improving the energy efficiency of windows. For this, computer modeling and BIM-based simulation programs provide significant timesaving in simultaneously evaluating design variations’ visual and thermal results. This study selected a four-story residential building to analyze the energy load and thermal comfort of the windows redesign and examine the energy-saving potential for residential buildings. To analyze the renewed window design strategies, a four-story apartment building is selected as a case study in Izmir/Turkey (38° 4′, 27° 2′). This apartment is built on a 90 m2 gross floor area. The existing indoor environmental conditions of the flat are generally observed as cool and low illuminated by the occupants, so the window design options must be compared and renewed. As the first option, current conditions are simulated. The second option is to simulate different patterns for window-to-wall ratio (WWR). Moreover, the third option is to simulate different types of glass in each window. Currently, the WWR of the selected flat in the north, east and south directions is around 10%. But more is needed to provide daylight to the apartment. This article used Autodesk Revit and Green Building Studio simulations to investigate WWR and glass types and evaluate energy use intensity’s (EUI) impact. As a result, this study shows that a 10% WWR on all building facades leads to an EUI of 993.9 MJ/m2/year. In contrast, increasing the WWR to 95% significantly increased EUI, reaching 2121 MJ/m2/year. In addition, it has been shown that the use of low U-value glasses, such as translucent wall panels and super-insulated three-pane clear Low-E, can provide energy savings of up to 5% per year, and especially the super-insulated three-pane Low-E glass type provides the highest efficiency on all facades.

Examining the role of passive design indicators in energy burden reduction: Insights from a machine learning and deep learning approach

Passive design characteristics (PDC) play a pivotal role in reducing the energy burden on households without imposing additional financial constraints on project stakeholders. However, the scarcity of PDC data has posed a challenge in previous studies when assessing their energy-saving impact. To tackle this issue, this research introduces an innovative approach that combines deep learning-powered computer vision with machine learning techniques to examine the relationship between PDC and energy burden in residential buildings. In this study, we employ a convolutional neural network computer vision model to identify and measure key indicators, including window-to-wall ratio (WWR), external shading, and operable window types, using Google Street View images within the Chicago metropolitan area as our case study. Subsequently, we utilize the derived passive design features in conjunction with demographic characteristics to train and compare various machine learning methods. These methods encompass Decision Tree Regression, Random Forest Regression, and Support Vector Regression, culminating in the development of a comprehensive model for energy burden prediction. Our framework achieves a 74.2 % accuracy in forecasting the average energy burden. These results yield invaluable insights for policymakers and urban planners, paving the way toward the realization of smart and sustainable cities.

Optimizing hybrid ventilation and daylight-linked dimming control for carbon reduction and thermal comfort in a subtropical high-rise office building

The dominant contributors to electricity consumption in existing buildings are air-conditioning and lighting systems. This study aims to optimize hybrid ventilation and daylight-linked dimming control in a subtropical high-rise office building. The objective is to reduce carbon emissions while ensuring thermal and visual comfort. These two strategies can be retrofitted in a typical curtain wall system with vertical windows without encountering any technical limitations. EnergyPlus is used to analyze the impact of these strategies on enhancing thermal comfort and illuminance while achieving electricity savings in the high-rise office building. Based on the typical meteorological year of Hong Kong, using natural ventilation in perimeter zones can reduce the energy use intensity (EUI) by 2.6 to 3.41 % for 30.09 to 34.97 % of total operating hours, depending on window-to-wall ratios (WWRs). Furthermore, daylight-linked dimming control in perimeter zones can reduce EUI by 18.91 % to 21.9 % in the HVAC portion and 8.09 % to 12.25 % in the lighting portion during 91.39 % to 98.28 % of total operating hours. Using daylighting with a high WWR helps reduce 6.31 to 9.21 % in total greenhouse gas emissions. The study also develops a logistic regression model using three climatic variables to predict the natural ventilation status. Overall, the use of daylighting greatly improves the percentage of acceptable predicted mean vote (PMV), with the greatest improvements observed in perimeter zones facing east and west on the middle floors. However, the combined application of both strategies results in a tempered improvement. The novelty of this study lies in providing guidance on suitable WWRs for implementing both strategies to achieve carbon reduction. Moreover, the significance lies in providing a quantitative assessment of how enhanced ventilation and lighting controls contribute to lower carbon emissions while improving thermal comfort.

A spatial mapping of thermal comfort and air quality (SMTC-AQ) framework for the built environment using computational fluid dynamics approach

Indoor environmental quality (IEQ), driven by thermal comfort and indoor air quality (IAQ), is a major factor that impacts occupant's well-being and productivity since people spend 80–90 % of their time indoors. The current approaches for assessing and quantifying IEQ presume fixed values and ranges in naturally ventilated (NV) spaces within the simulation environment. However, such an approach cannot capture point-to-point changes that occur in the built environment due to localized variations of environmental variables such as air velocity and temperature. This study proposes a sensing and simulation-based framework, Spatial Mapping of Thermal Comfort and Air Quality (SMTC-AQ) in a computational fluid dynamics (CFD) environment to address this. Salient characteristics of SMTC-AQ include the modification of predicted mean vote (PMV) for NV spaces, specifically for the Indian context, and the implementation of the under-explored concept of domain-decoupling utilizing the ISHRAE weather file. Using SMTC-AQ, the study determines the optimal window-to-wall ratio (WWR) and opening-to-wall ratio (OWR) for a case study room in an Indian academic building, considering both IAQ and thermal comfort. In the study, indoor air velocity and temperature are first validated with field data, followed by a scenario analysis to assess the impact of opening characteristics on IEQ. The findings show that for building spaces in tropical climates with moderate outdoor temperatures and lower relative humidity, thermal comfort, and IAQ can be improved by implementing higher WWR and OWR. Moreover, WWR is a more relevant criterion for improving thermal comfort and a better OWR design is crucial for enhancing IAQ in NV spaces.

The effect of window design factors on the cooling load in hospitals wards

PurposeThis paper investigates the optimization of window design factors (WDFs) in hospital buildings, particularly in government hospitals within the arid climate of the Qassim region, with the aim of achieving a better cooling load reduction. Continuous monitoring of the hospital ward section is crucial due to patients' needs, requiring optimal indoor air quality and cooling load.Design/methodology/approachThe study identifies the optimal conditions for WDF design to mitigate cooling load, including window-to-wall ratio (WWR), window orientation (WO), room size and U-value (thermal properties), effectively reduce energy consumption in terms of sensible cooling load (MWh/m2) and comply with local codes. Data collection involved a smart weather station, while the Integrated Environmental Solution Virtual Environment (IESVE) software facilitated the simulation process.FindingsKey findings reveal that larger patient rooms were about 40% more energy-efficient than smaller rooms. The northern orientation showed lower energy consumption, and specific WWRs and glazing U-values significantly affected energy loads. In an analysis of U-value changes in energy performance based on the Saudi Building Code (SBC), the presented values did not meet the minimum energy consumption standards. For a valid 40% WWR with a thermal permeability of 2.89, 0.181 MWh/m2 was consumed, while for an invalid 100% WWR with the same permeability but facing the north, 0.156 MWh/m2 was consumed, which is considered an invalid practice. It is vital to follow prescribed standards to ensure energy efficiency and avoid unnecessary costs.Originality/valueFocus lies in emphasizing the significance of adhering to prescribed standards, such as SBC, to guarantee energy efficiency and prevent unwarranted expenses. Additionally, the authors highlight the crucial role of optimizing glazing properties and allocating the WWR appropriately to achieve energy-efficient building design, accounting for diverse orientations and climatic conditions.

Implementation of light shelves and WWR to improve daylight performance in university classroom

Daylight plays important role in achieving good Indoor Environment Quality (IEQ) because it contributes to human health and optimal working performance. The Engineering Center (EC) building, which is part of Universitas Indonesia in Depok, Indonesia has great daylight potential with an existing design Window-to-Wall Ratio (WWR) of 100%. However, this potential has yet to be maximized due to use of artificial lighting during the day. Moreover, the uneven distribution of sunlight entering the room creates some issues (i.e., glares, dazzled, heat and low uniformity level). This research tries to improve this condition by intervening in Window to Wall Ratio (WWR) and adding Light Shelves (LS) in class 101 (facing south) and 102 (facing north). 56 variations of WWR and LS were simulated using Rhinoceros (RH) and Grasshopper (GH) software with plug-ins (Ladybug and Honeybee). The simulation results show three design configurations WWR 60% - LS straight; WWR 78% - LS straight; and WWR 60% - LS curve in room number 102 facing north produce illuminance close to the maximum and minimum threshold for good lighting in the classroom (350 - 500 lx). This study will provide reference strategies for improving daylight performance in university classrooms with tropical climates.

Impact of Passive Design Strategies on Environment, Cooling and Lighting Energy Demand. A Weighted Least Squares-Based Approach

Abstract The energy transition requires optimal knowledge of the thermal behaviour of different passive strategies. This paper explores the impact of 28 variables representing 4 shading devices, 5 external wall compositions (U w), 3 window types (U w), 4 window-to-wall ratios (WWR), 4 types of climates represented by 4 cities, and 8 orientations. Applying the Latin hypercube sampling method, a campaign of 300 dynamic thermal simulations is performed to assess the impact of the variables selected using the weighted generalised linear regression method for the energy demand for air conditioning, the energy demand for lighting, and the environmental impact expressed in kg of CO2. The model of energy demand for cooling (R² = 0.951) shows that the weather data is the variable that most explains energy demand, followed by the glazing ratio, the thermal characteristics of external walls, and shading devices. The model explaining the energy demand for lighting (R² = 0.945) shows that the WWR and shading devices, the weather data, and the orientation, influence the energy demand for lighting. Finally, the model explaining the embodied carbon footprint (kg of CO2) (R² = 0.989) shows that external walls and window type are the main influencing factors. Finally, the best combination for balancing the cooling-lighting-embodied carbon balance equation is discussed.

Robust multi-objective building design optimization approach using NSGA-II algorithm considering weather and occupant uncertainties

A novel methodology is presented to evaluate how real-world operational uncertainties impact multi-objective building design optimization process. NSGA-II algorithm is applied across nine distinct operational scenarios, considering diverse weather datasets and energy usage patterns to optimize energy efficiency and thermal comfort in a residential building within India's hot and dry climate. The analysis considers 382,400 possible design options for each scenario. Using (10.5–12.5) % of model evaluations, NSGA-II significantly reduces Annual Cooling Energy Demand (ACED; 46.7%–58.7%) and Cooling Set-point Unmet Hours (CSUH; 70.92%–86.93%) to identify nine Pareto–Optimal solution sets. The final robust optimal design is confirmed by selecting the most repeated parameter settings, representing the highest robustness. Low thermal transmittance walls, double-glazed windows with a 10% window-to-wall ratio (WWR), deep overhangs, and a low solar heat gain coefficient are recognized as robust optimal building components. However, Air Conditioner (AC) sizing lacks robustness in minimizing energy demand across scenarios, requiring case-specific evaluation due to its sensitivity to weather and operational variations. Further, PAWN sensitivity analysis highlighted the substantial impact of WWR (KSWWR ∼ (0.46–0.66)) and wall type (KSWall ∼ (0.31–0.46)) on ACED and CSUH in chosen climate. AC operation is more important for predicting CSUH (KSAC ∼ 0.35) than ACED (KSAC ∼ 0.10).

Daylighting and energy performance of the window with transparent insulation slats in the humid subtropical climate zone

The window with transparent insulation slats (WTIS) is a promising glazing system to balance building energy efficiency with adequate indoor illumination. It was investigated in several studies before, but the strengths and weaknesses of WTIS have yet to be unveiled compared with other commonly used windows regarding natural lighting and energy-saving potential. Without this information, it is hard for an architect or engineer to design and choose the optimal window type for an improved visually comfortable indoor environment and energy-efficient buildings. To address this research gap and exploit WTIS’s potentialities more comprehensively, this study used a cellular office room in Changsha as a case study to evaluate the annual daylighting and energy performance of WTIS and three commonly representative windows (double-glazing, double-glazing with interior aluminum blinds, and the Low-E window) in the humid subtropical climate zone. The analysis considered the impact of window-to-wall ratios (WWRs) and window orientations. A comprehensive approach was presented in this study, and the experiment data verified the thermal and optical models of WTIS in the simulation. The results indicate that the WTIS (Frosted slats) has better daylighting performance than other windows when WWR is larger than 40% in south orientation, which can increase the proportion of the indoor daylight illumination (100–3000 lx) to more than 86%. Considering both daylighting and energy performance, the WTIS (Smooth slats) is suitable for small WWRs, especially for north-facing windows.

Identifying Façade Orientations with Closely Similar Thermal Performance for Unifying Façade Design Features in Hot Arid Climate

Large-scale residential projects require architects to balance energy efficiency, thermal comfort, and cost-effectiveness in designing building units distributed in different orientations. Applying a single design to all orientations may not result in comfort conditions and energy efficiency; meanwhile, creating a unique design solution for each orientation can be time-consuming and costly to implement. Despite numerous studies recommending design alternatives for particular orientations, the ranges where orientation changes do not demand a change in the façade design still need to be determined. This research aims to identify ranges for which changes in building orientation do not necessitate changes in the façade design. It involves conducting parametric energy and thermal comfort simulations in a test room and testing the findings using real-life datasets from a large-scale residential project. Glass type, window-to-wall ratio (WWR), and utilization of shading devices were among the design parameters investigated. Results show that for all-year-round occupancy projects, a common solution can be applied for orientation changes between 0° to 10° from the north, −10° from the south, and ±5° from east and west for WWR of less than 50% in hot arid climates. These ranges can increase for small WWRs and when reflective glazing or shading devices are applied. This helps streamline design and construction processes, lower costs, and save energy in large-scale residential projects.

Dynamic Simulation Analysis of Influencing Factors of Energy Consumption of Public Building Envelope in Central China

It difficult for buildings in cold regions to reasonably meet ultra-low energy consumption requirements. To explore the influencing factors of building energy consumption in this type of climatic region, this paper takes a typical public building in Zhengzhou, China as a case study to dynamically simulate an entire building. The influence of the window glass, window-to-wall ratio (WWR), thermal insulation material thickness and other factors on building energy consumption is considered. The sensitivity of envelope design factors to energy consumption is analyzed by the orthogonal test. The results indicate that the effect of changing the technical parameters of the external envelope structure on building energy efficiency is significant. Moreover, range analysis is used to determine the primary and secondary factors with regard to their influence on the energy consumption of the building. The WWR, the type of external window glass and the thickness of the external wall insulation layer should be considered first in energy-saving design; the energy-saving potential of the roof insulation thickness is not as significant as these factors. The results of the study can provide a reference for the energy-saving design of public buildings in Central China.