You are currently viewing a new version of our website. To view the old version click .
MDPIMDPI
Search all articles
Urban Science
Download PDF
  • Article
  • Open Access

13 October 2025

Net-Zero Energy Retrofitting in Perth’s Residential Sector: Key Features and Strategies for Sustainable Building Transformation

,
and
1
Department of Architecture, Stamford University Bangladesh, Dhaka 1217, Bangladesh
2
School of Design and the Built Environment, Curtin University, Perth 6102, Australia
*
Authors to whom correspondence should be addressed.
Urban Sci.2025, 9(10), 421;https://doi.org/10.3390/urbansci9100421 
(registering DOI)
Version Notes
Order Reprints

Abstract

The study aims to identify optimum retrofitting strategies that mitigate climate change and support Australia’s net-zero emissions target by 2050. Current heating and cooling demands, as well as the energy performance of three stand-alone houses built before 2003, were evaluated to determine optimal retrofitting measures. Based on a comprehensive literature review and physical building surveys and energy simulations using FirstRate5 of three selected case studies of stand-alone houses in Australia’s climate zone 5, the study identifies and proposes effective retrofitting opportunities in Western Australia. Additionally, the outcomes from FirstRate5 illustrate that improving ceiling and exterior wall insulation in living and dining areas, sealing air leaks, reducing overshading, and replacing single-glazed windows with double-glazed units while enlarging north-facing windows, following the recommended wall–window ratio significantly improve the energy rating of the selected houses. The average energy rating performance of the three selected stand-alone houses increases from an average below 3.5 stars (211.5 MJ/m2) to above 7.5 stars (46.7 MJ/m2), representing around 76.6% improvement in energy efficiency. Just to contextualise the scale up, such retrofitting of all old stand-alone houses built before 2003 would potentially reduce emissions by 12.73 Mt CO2-e/year, representing a 3.16% contribution toward Australia’s national emission reduction target by 2035. Additionally, installing solar energy systems could reduce an extra 4.5 Mt CO2-e/year. The study’s findings demand robust retrofitting strategies for Australia to achieve its 2050 net-zero emissions targets.

1. Introduction

The building sector accounts for almost 34% of the world’s energy consumption [] and 37% of carbon emissions []. According to the Paris Agreement, countries must limit global warming to 1.5 °C to reduce climate risk and impacts, by reaching global net-zero CO2 emissions by 2050 []. Australia and all signatory countries of the Paris Agreement have committed to the global goal of holding the increase in global temperature to well below 2 °C above pre-industrial levels, and to pursuing effort to limit the temperature increase to 1.5 °C. The Australian Government’s Net Zero Plan articulated six sectors (Electricity and energy, Transportation, Industry, Agriculture and land, Resources, and Built environment) that capture the full breadth of the economy []. In Australia, buildings account for about one-fifth of national emissions (operational plus part of embodied), with residential buildings contributing a significant share []. To tackle climate change and achieve net zero by 2050, the Australian building sector plays a crucial role by incorporating various energy-efficient parameters and a building rating system into its national construction code (NCC) for constructing new buildings.
Meanwhile, globally, approximately 98% of the building stock consists of existing structures [], and less than 2% of buildings in Australia are replaced each year []. With energy efficiency being a key consideration in design, achieving net zero by 2050 is a significant challenge without considering the existing building stock. This sector will consume 50% of Australia’s carbon budget by 2050 if the heating and cooling of buildings continue at the present rate. Regarding the carbon budget, 40% is mainly allocated to residential buildings, which is almost 90% of the Australian building stock and is responsible for 10% of national emissions []. Most existing residential buildings were constructed before the energy-efficient parameters were included in the National Construction Code (NCC), which started on 1 January 2003 []. According to ABS (2021), the number of stand-alone houses in Western Australia is 0.76 million, while the nationwide total is 6.7 million []; among them 70% of houses are built before 2003 []. Millions of residential buildings in Australia require retrofitting to enhance their energy performance, achieve comfort, reduce costs, and increase resilience. The average NatHERS (Nationwide House Energy Rating Scheme) rating of existing dwellings is estimated to be below 2 stars on a 10-star scale [,], while 98.5% of the existing housing stock falls short of achieving optimal economic and energy performance [,]. Australian residential buildings account for 24% of overall electricity consumption and 10% of total emissions []. A study conducted on detached houses in three Australian states (Victoria, New South Wales, and Western Australia) found that upgrading insulation (floor, wall, and ceiling) can reduce annual energy use by an average of 24% and lower emissions by 13%. Effective appliances such as fridge, dishwasher, and washing machine reduce equipment power density by 55% (W/m2) and LED lighting reduced light power density by 85% (W/m2) []. Additionally, a solar panel (5 kW, 25 m2) can produce 7300 kW/year on average. In Australian houses approximately 30% of that amount is used for the house and the rest is stored on the battery or contributed to the national grid [], which also reduces 8.6 t CO2-e/year for every house []. Retrofits also play a significant role in reducing embodied carbon. A new building accounts for 35–40% of its lifecycle emissions from embodied carbon, whereas retrofitting can reduce almost three-quarters of a building’s upfront embodied carbon emissions []. Consequently, operational emissions will represent only about 12% of the home’s total lifecycle carbon []. This article aims to identify optimal energy-efficient design features for retrofitting stand-alone houses in Perth, Western Australia (Australian climate zone 5), using FirstRate5 and evaluating the resulting carbon emissions savings.

2. Literature Review

Retrofit refers to upgrading buildings to respond to climate change [], including renovating, repairing, refurbishing, and restoring old buildings to increase energy efficiency []. The primary objective of retrofitting is to mitigate climate change and enhance building resilience against its impacts. Retrofit can be divided into two types: deep and shallow retrofit. Deep retrofitting is an integrated approach, the most effective way to reduce energy consumption, which is costly, and it reduces up to 70% of heating energy demand. Shallow retrofitting means just changing the appliances, and it is a low-cost option that reduces 30% of heating energy demand []. In Australia, well-planned retrofitting can reduce household heating demand by up to 69% and cooling demand by 38% []. The NCC (National Construction Code) of Australia 2022 requires new homes to achieve a 7-star NatHERS rating, taking into account major fixed appliances as well as on-site energy generation and storage. This is an increase from the previous 6-star requirement and also includes provisions for retrofitting existing homes to improve energy efficiency and reduce emissions []. Retrofit has many benefits, such as improving health issues, reducing fuel poverty, developing a resilient society, and creating employment opportunities []. Numerous studies have demonstrated that retrofitting enhances the energy efficiency of existing buildings. Retrofitting can reduce energy consumption by 80%, requiring high investment and a long payback period []. The energy waste depends on the building age; older buildings waste more energy than new buildings [].
Retrofitting is a common practice for transforming a lower-energy building into an energy-efficient one. It is a complex strategy that involves different stakeholders. Many countries have already implemented retrofitting measures to improve the energy efficiency of their buildings. Studies conducted in South Korea have shown that only exterior wall insulation and window retrofitting reduced the annual energy consumption of low-income residential buildings, which mainly depends on the room location, by 22.61% [,]. Replacing windows and achieving airtightness can save 15.5% and 18.5% in South Korean warm and cold climates []. A study conducted in 44 cities with different climatic conditions in the US found that retrofitting attics with a switchable insulation system in hot and cold seasons benefits energy savings []. In another study in the UK, the most effective retrofit option was wall insulation, compared to window glazing, floor and roof insulation, which cost significantly more and has a payback period of 40 years []. This, however, contradicts another study in the UK, where the most cost-effective option was found to be insulating walls with 40 mm EPS (Expanded Polystyrene), floors with 40 mm XPS (Extruded Polystyrene), and roofs with 30 mm XPS (Extruded Polystyrene) []. Retrofitting with a Trombe wall is very beneficial in hot and arid climates. Concrete in 2/3 of the external wall with glass in a Trombe wall can reduce about 86% heating load in winter, whereas 5% extra energy is necessary for cooling the interior space in summer []. Similarly, in the hot climate region of Saudi Arabia, external wall insulation, roof insulation, and floors exposed to the weather are beneficial for energy retrofitting.
In contrast, landscape around the building reduces cooling energy []. Research conducted by the Australian Government identified retrofitting options for houses in Australian Climate Zone 5 (e.g., Adelaide, Perth, and Sydney), providing specific details based on the houses’ construction periods. For instance, significant retrofitting options for homes built between 1970 and 2000 are adding a solar panel, improving airtightness, a hot water system upgrade, energy-efficient appliances, LED lighting, roof/ceiling insulation, wall insulation, natural ventilation, and an external shading device, which are not difficult to install but enable high energy savings [].
Time is a significant concern in retrofitting because traditional retrofitting is a labour-dependent process, where replacing old windows with new ones and installing insulation on the wall, floor, and ceiling takes weeks to months []. To overcome this problem, an industrialised solution, such as a prefabricated element, could be an alternative to traditional retrofitting. Retrofitting with concrete sandwich panels provides the required R-value with lower CO2 emissions []. Table 1 shows the key building features to improve energy efficiency based on various studies. Based on the local context in Perth and climate zone 5, only the relevant building features are briefly discussed in the following sections.
  • External Wall:
Table 1. Literature for the study of key features and parameters of energy-efficient buildings.
The external wall is the most impactful element for heating and cooling energy demand and indoor comfort []. Proper design and application of the external wall in a residential building reduces electricity consumption for heating, cooling, ventilating, and lighting []. It also accounts for almost 50–60% of the heat transfer of buildings [,]. Thermal performance of the external wall increased in different ways, such as increased thickness of the materials, adding insulation, and introducing an air cavity []. The performance of thermal mass depends on climatic conditions. Hot climatic zones require higher thermal mass compared to cold zones, which require low thermal mass [].
  • Thermal Insulation:
Insulation is used to improve the thermal performance of a building, and optimal insulation thickness can reduce energy consumption by 46.6% []. Insulation is used primarily on the roof, ceiling, floor, and walls to prevent heat flow. Effective use of insulation, especially in exterior walls, enhances the energy efficiency of a building, which reduces up to 19.7% of the energy load [].
  • Window Glazing:
In a building envelope, the window is the most significant element for energy efficiency. Inefficient windows are responsible for a building’s 20–60% energy loss []. In Australia, an estimated 1.5% of heat transfer occurs through windows []. As a result, window glazing significantly improves the performance of windows in improving a building’s energy efficiency [,]. Currently, various types of glazing are available; the most commonly used type are single-glazing units, which are almost twice as inefficient as double-glazing units. Triple-glazing units are the most effective in reducing energy consumption among these three options []. On the other hand, other high-performance window glazing solutions are also available.
  • Window–Wall Ratio:
The window-to-wall ratio has a significant impact on a building’s energy demand. It refers to the ratio of glazing area with mullions and frames to the gross external wall area []. The appropriate window-to-wall ratio according to the site orientation is selected in the design stage to reduce yearly heating and cooling energy []. In a hot climate, lowering the window-to-wall ratio by 20% can save 15% of the energy demand of a building []. Increasing the window-to-wall ratio by 5–25% compared to the optimal situation is the worst configuration in European climatic conditions []. The recommended window-to-wall ratio for southern and eastern facades is 65%, and 95% and 30% for northern and western facades, respectively, in the Mediterranean climate [], like the Australian climate zone 5.
  • Shading Device:
Shading devices protect against the infiltration of solar radiation into the building surface in the summer, while allowing the necessary solar heat gains in the winter to improve thermal performance []. Shading can be operable, such as external louvres, pergolas, curtains, blinds and deciduous trees, and fixed, like eaves, fences, and evergreen trees []. In the Australian context, horizontal shading above the glass is the solution for a north-facing facade that blocks high-angle sun in summer and allows low-angle sun in winter. On the other hand, vertical shading options are mostly operable are suitable for allowing the winter sun’s radiation inside the building [].
  • Airtightness:
Energy loss due to air leakage from building openings is a common phenomenon in old buildings and those with poorly installed openings. A heat loss reduction by almost 33% can be attributed to airtight windows [].
Additional literature suggests that incorporating various building features and parameters can improve energy efficiency in buildings within Perth’s climate, with the associated energy savings resulting from their implementation, as presented in Table 2.
Table 2. Building features for retrofitting and their energy saving or reduction for Perth’s climatic conditions.

3. Materials and Methods

This study was conducted in the suburb of Langford, within the City of Gosnells, Perth, Western Australia. The primary case studies were three NCC Class 1A single-dwelling stand-alone houses, representing Perth’s most common housing type (79%) []. Yin (1994) [] defines case study research as an empirical inquiry into a contemporary phenomenon within its real-life context, particularly when the boundaries between them are unclear. He emphasises that the method is the key characteristic of a case study and distinguishes between single- and multiple-case designs. A single-case design addresses the research questions through one case, while a multiple-case design examines two or more cases []. This study adopts a single-case design, investigating seven stand-alone houses. Similarly, Stake (1998) identifies three types of case studies: intrinsic, instrumental, and collective []. This research adopts an instrumental case study. Selected case study homes were built before 2003, before the introduction of energy standards in the Australian National Construction Code (NCC). While not statistically exhaustive, a sample size of three, which is representative, was chosen to allow for an in-depth and resource-feasible investigation. The selected cases provide a reasonable cross-section of typical pre-2003 homes, which dominate the city’s suburban landscape and offer the most significant potential for retrofitting.
The research in this study consists of four parts. Firstly, an intensive literature review was conducted to identify key building features responsible for energy efficiency, mainly in Perth’s climate conditions. Secondly, a physical survey of houses with the field survey datasheet (Appendix A) was conducted. During the survey, data were collected through direct observation, photographs, and by obtaining or drawing layout plans of the houses. Thirdly, energy simulations were run on FirstRate5 for each case study building to understand the energy use patterns in every zone of the houses using the data collected from the physical survey. The authors analysed the simulation to identify the optimum zone that plays a significant role in retrofitting. Lastly, another simulation was run for houses that applied for the most effective retrofitting building options, which were gathered from the literature review and applied to the most effective zones identified in the third phase. The data from these simulations were then compared across the case study buildings’ star ratings and total energy consumption to determine the emission reduction by retrofitting old houses and their contribution to Australia’s net-zero vision.

4. Results

4.1. An Overview of the Case Buildings

All case study buildings surveyed in this research are classified as NCC Class 1A stand-alone single-dwelling houses in the Langford suburb of the City of Gosnells, Perth. A total of three households were investigated. The occupants of Case Studies 1 and 3 are homeowners, whereas the occupants of Case Study 2 are tenants.

4.2. Current Heating and Cooling Energy Use of the Case Study Buildings

Several factors discussed previously influence the heating and cooling energy demand of a building. In this study, FirstRate5, an accredited NatHERS software tool, was employed to calculate the current energy consumption of the case study buildings. Various building-related data were required to perform the simulations, including house type, scaled floor plans, construction material specifications, building features, and location(Table 3). These data were collected during the physical surveys and subsequently input into FirstRate5. In addition to estimating energy use, FirstRate5 provides an Energy Star rating for each house on a scale from 0 to 10, where a lower rating indicates lower energy efficiency and a higher rating reflects greater efficiency.
Table 3. Different features of the case study buildings in Langford.

4.3. Case Study 1

For Case Study 1, Figure 1 (Left) illustrates the architectural plan analysis of the current design features that influence energy efficiency and provides a corresponding photograph (Right).
Figure 1. (Left) Plan analysis of Case Study 1 building. (Right) Photographs show Case Study 1 building’s southwest small window without shading and overshading at the southwest facade.
Table 4 presents the key information required to conduct the energy simulation in FirstRate5 for Case Study 1 house under current conditions.
Table 4. Building energy simulation input data for Case Study 1 under current conditions.
The current energy rating of Case Study 1 is 3.3 stars (Figure 2a). The heating and cooling energy requirements of this house are 151.4 MJ/m2 and 28.9 MJ/m2, respectively, resulting in a total energy demand of 180.3 MJ/m2 (Figure 2b). Notably, the demand for space heating is nearly five times greater than that for space cooling.
Figure 2. (a) Energy simulation in FirstRate5 using data from Table 4 for Case Study 1. (b) Energy usage of Case Study 1 (MJ/m2).
The living area exhibits the highest space-heating demand (Table 5) due to suboptimal window orientation and shading, with a small northwest-facing window and a larger southwest-facing window heavily shaded by a patio (Figure 1). This results in a relatively low cooling load. The combined living/kitchen area shows the second highest heating demand, remaining largely shaded despite two large windows. Bedroom 2 has the highest heating demand among the bedrooms, followed by Bedrooms 1 and 3. Bedrooms 1 and 2 feature two windows on the southwest and southeast facades without shading devices or extended eaves, and one external wall is permanently shaded by a patio, reducing overall thermal performance.
Table 5. Energy loads by zone in Case Study 1.

4.3.1. Case Study 2

For Case Study 2, the architectural plan analysis of the design features impacting energy efficiency is depicted in Figure 3 (Left), and a corresponding photograph is presented in Figure 3 (Right).
Figure 3. (Left) Plan analysis of Case Study 2 building. (Right) Photographs show Case Study 2 building’s north-east and southwest overshading and window air leakage.
The information required for the FirstRate5 energy simulation of Case Study 2 house, based on its current conditions, is presented in Table 6.
Table 6. Building energy simulation input data for Case Study 2 under current conditions.
Case Study 2 currently has an energy rating of 2.3 stars (Figure 4a). The house’s heating and cooling energy demands are 203.8 MJ/m2 and 73.3 MJ/m2, respectively, resulting in a total energy requirement of 277.1 MJ/m2 (Figure 4b). Notably, the energy demand for space heating is nearly three times higher than that for space cooling. Furthermore, the distribution of energy loads across the main zones of the dwelling is presented in Table 7.
Figure 4. (a) Energy simulation in FirstRate5 using data from Table 6 for Case Study 2. (b) Energy usage of Case Study 2 (MJ/m2).
Table 7. Energy loads by zone in Case Study 2.
The living area records the highest heating energy demand (Table 7) primarily because it is located on the southeast side (Figure 3), where a carport shades a large awning window, and the adjacent facade is further obstructed by a patio (Figure 3). The dining space exhibits the highest cooling demand and the second-highest heating demand, as it is southwest-oriented and partially shaded by a patio. The bedrooms are situated on the northeast and northwest sides; among them, Bedroom 3 shows the most significant combined heating and cooling demand due to a northwest-facing window and additional shading from the patio on the southwest side

4.3.2. Case Study 3

The architectural plan analysis of design features influencing energy efficiency in Case Study 3 is illustrated in Figure 5(Left), with Figure 5(Right) presenting a photograph of the buildings.
Figure 5. (Left) Plan analysis of Case Study 3 building. (Right) Photograph shows Case Study 3 building’s southwest overshading, vented attic, and small window at northwest facade.
The data required for the FirstRate5 energy simulation of the Case Study 3 house in its current state are shown in Table 8.
Table 8. Building energy simulation input data for Case Study 3 under current conditions.
Figure 6a shows that Case Study 3 has a current energy rating of 3.3 stars. The house’s heating and cooling energy demands are 148.9 MJ/m2 and 28.9 MJ/m2, respectively, resulting in a total energy requirement of 177.3 MJ/m2 (Figure 6b). Notably, the demand for space heating is nearly six times higher than that for space cooling.
Figure 6. (a) Energy simulation in FirstRate5 using data from Table 8 for Case Study 3. (b) Energy usage of Case Study 3 (MJ/m2).
The distribution of energy loads across the main zones of the dwelling is presented in Table 9. The dining/kitchen area on the southwest side in Figure 5(Left) exhibits the highest overall energy demand. The living area has a higher heating requirement due to its northwest orientation and the presence of only a small window, which limits solar heat gain. In contrast, the southwest-facing dining/kitchen area features two large windows that allow substantial solar heat gain, resulting in the highest cooling demand among all dwelling zones. The three bedrooms are shaded by a carport in Figure 5(Right), effectively reducing their cooling energy requirements.
Table 9. Energy loads by zone in Case Study 3.

4.4. Overall Findings from Case Study Buildings

The findings from the case study buildings are presented in two parts: data directly collected through the physical survey and results obtained from energy simulations conducted using FirstRate5. The physical survey provided detailed information on building features that improve energy efficiency or increase demand. Additional data required to run the FirstRate5 simulations was also gathered during this survey.
One of the most significant findings concerns building orientation, which in many cases contradicts the climatic requirements of Perth. This issue primarily arises from designers’ limited awareness during the design phase. Ideally, living rooms should face north to maximise winter solar heat gain and reduce heating demand. However, this design principle was not effectively implemented in any of the three case study buildings. Instead, all houses exhibited overshading issues, which increased heating demand and reduced daylight penetration. Consequently, occupants relied more on artificial lighting during the daytime, further elevating energy consumption. In many instances, these overshading elements, such as patios, storage rooms, and carports, were added after the original construction of the houses.
All three case study buildings lacked wall and ceiling insulation, significantly contributing to higher energy demand. Among them, one house employed a brick veneer construction system. Its thermal performance was considerably poorer than the two double-brick houses because it lacked insulation between the external brick and the internal plasterboard. Furthermore, all three buildings exhibited air leakage problems, as no weather-stripping was installed on doors or windows.
Following the physical survey, energy simulations were conducted using FirstRate5 to evaluate the overall heating and cooling energy demand of the case study buildings and to determine their current star ratings (Figure 7).
Figure 7. Current star rating of case study buildings from FirstRate5 simulation.
Detailed zone-level energy consumption data generated from the simulations were also analysed to identify the most energy-intensive spaces and to compare these findings with the existing literature. The results indicate that the living room consistently exhibits the highest energy demand, followed by the dining area in all three case study buildings (Figure 8). These insights are further applied to guide the selection of optimal retrofitting strategies aimed at improving the overall energy performance of each dwelling.
Figure 8. Energy usage by different zones in case study houses (MJ).

4.5. Proposed Optimum Retrofitting Options for Case Study Buildings

Deep or whole-house retrofitting is more beneficial for energy efficiency, while shallow retrofitting offers a more affordable option. Additionally, the main barriers to deep retrofitting are the time required and the disturbance it causes to occupants. Every state in Australia faces a housing crisis [], and relocating to another house or taking a long time to complete whole-house retrofitting is often tricky. For these reasons, selecting optimal retrofitting options that require minimal time and do not necessitate relocating occupants during the retrofit work is essential. Modular precast retrofitting options are more suitable for completing the retrofitting work quickly. For instance, a modular low-carbon precast concrete sandwich panel (Figure 9) for the external wall, which could improve the overall thermal quality and energy efficiency of the building’s external wall, is a viable option for external wall retrofitting with lower emissions. Retrofitting aims to reduce energy demand, supporting Australia’s commitment to achieving net-zero emissions by 2050. The selection of optimal retrofitting options is informed by the literature review, which applied the case study building to compare the overall improvement of energy efficiency of those buildings.
Figure 9. Modular low-carbon precast concrete sandwich panel [].
Formula for R-value:
R = d/k
where
R = thermal resistance (m2K/W).
d = thickness of the material (m).
k = thermal conductivity of the material (W/mK).
For Multiple Layers
If you have several materials (e.g., wall layers), the total R-value is the sum of each layer’s R-value:
Rtotal = R1 + R2 + R3 + …
For Pre Low-Carbon Sandwich Panel R = 2.42 []
Thermal Transmittance U = 1/R
              =1/2.42
              =0.41

4.5.1. Case Study 1

In Case Study 1, the living and dining areas account for the majority of the energy demand. To enhance performance, a prefabricated modular concrete sandwich panel is proposed for the exterior wall of the living room. Furthermore, the entire house was sealed to minimise air leakage, all windows were replaced with double glazing, and the ceiling was insulated with high-performance insulation batts. Table 10 provides detailed information on the modifications incorporated into the FirstRate5 energy simulation for Case Study 1.
Table 10. Building energy simulation input data for Case Study 1 after retrofitting.
After the retrofit modifications, the Case Study 1 house achieved an 8.2-star rating (Figure 10a), with a total energy consumption of 39.8 MJ/m2 (Figure 10b). In addition, heating and cooling energy demand decreased by approximately one-sixth and one-third, respectively, compared to the current condition.
Figure 10. (a) Energy simulation after retrofitting in FirstRate5 using data from Table 10 for Case Study 1. (b) Energy usage after retrofitting in FirstRate5 of Case Study 1 (MJ/m2).
After retrofitting, the views of the Case Study 1 house are presented in Figure 11 along with details of the low-carbon concrete panel. In addition, the proposed on-site energy production from a solar system is also illustrated.
Figure 11. The views show Case Study 1 after retrofitting and prefabricated plugin installation details.

4.5.2. Case Study 2

In Case Study 2, the living, dining, and kitchen areas account for most of the energy demand, similar to Case Study 1. To enhance performance, the external walls of these areas were replaced with low-carbon prefabricated modular concrete sandwich panels. Additionally, all windows were upgraded to double glazing, the ceiling was insulated, and all doors and windows were weather-sealed. Table 11 provides detailed information on the modifications incorporated into the FirstRate5 energy.
Table 11. Building energy simulation input data for Case Study 2 after retrofitting.
The retrofit improved the star rating of Case Study 2 from 2.3 to 8.1 stars (Figure 12a). The total energy demand decreased by approximately one-seventh, with heating and cooling energy demands of 42.1 MJ/m2 and 35.1 MJ/m2, respectively (Figure 12b).
Figure 12. (a) Energy simulation after retrofitting in FirstRate5 using data from Table 11 for Case Study 2. (b) Energy usage after retrofitting in FirstRate5 of Case Study 2 (MJ/m2).
Figure 13 presents the post-retrofit views of the Case Study 2 house, highlighting the low-carbon concrete panel. It also illustrates the proposed on-site solar energy generation system.
Figure 13. The views show Case Study 2 after retrofitting and prefabricated plugin installation details.

4.5.3. Case Study 3

In Case Study 3, the living, dining, and kitchen areas represent the highest energy demand, consistent with Case Studies 1 and 2 observations. To improve building performance, the external walls of these spaces were upgraded with low-carbon prefabricated modular concrete sandwich panels. In addition, all windows were replaced with double glazing, the ceiling was insulated, and all doors and windows were weather-sealed. Table 12 provides a detailed summary of the modifications implemented in the FirstRate5 energy simulation for Case Study 3.
Table 12. Building energy simulation input data for Case Study 3 after retrofitting.
Following the retrofit, the star rating of Case Study 3 rose from 3.3 to 7.7 (Figure 14a). At the same time, total energy demand declined by roughly one-third, with heating and cooling energy consumption of 37.4 MJ/m2 and 20.9 MJ/m2, respectively, as shown in Figure 14.
Figure 14. (a) Energy simulation after retrofitting in FirstRate5 using data from Table 12 for Case Study 3. (b) Energy usage after retrofitting in FirstRate5 of Case Study 3 (MJ/m2).
Figure 15 shows the Case Study 2 house after retrofitting, featuring the low-carbon concrete panel and the proposed on-site solar energy generation system.
Figure 15. The views show Case Study 2 after retrofitting and prefabricated plugin installation details.

4.6. Comparative Analysis: Before and After Retrofitting of Case Study Buildings

The primary objective of retrofitting is to reduce a building’s energy demand. Figure 13 presents the energy consumption of the case study buildings before and after retrofitting. The total energy demand of case study houses 1–3 was initially 180.3 MJ/m2, 277.1 MJ/m2, and 177.3 MJ/m2, respectively, and decreased to 39.8 MJ/m2, 42.1 MJ/m2, and 58.3 MJ/m2 following retrofitting (Figure 13). Consequently, the energy performance ratings of these buildings improved due to the reduction in energy demand. All three case study buildings initially had ratings below 3.5 stars, which increased to over 7.5 stars after retrofitting (Figure 16 and Figure 17).
Figure 16. Energy use of case study houses (MJ/m2) (current situation and after optimal retrofitting).
Figure 17. Star rating of case study houses (current situation and after optimal retrofitting).

5. Discussion

From the literature review, energy savings achieved through the implementation of energy-efficient building features for retrofitting in Perth’s climatic conditions can be roughly estimated by summing the lower-bound values of the features listed in Table 2, resulting in a total energy savings of approximately 80% (40% + 20% + 5% + 5% + 10%). In this study, case studies 1–3 achieved reductions in energy consumption of 77.9%, 84.8%, and 67.1%, respectively, with an average decrease of 76.6%, closely aligning with the findings reported in the literature. In Australia, 70% of stand-alone houses were constructed before 2003 [], i.e., before implementing energy-efficiency requirements in the National Construction Code (NCC). Based on this proportion, people built 538,326 stand-alone households in Western Australia and 4,697,407 stand-alone households nationwide before 2003 []. The Australian Government has recently set a 2035 target of reducing emissions by 62–70% below 2005 levels, focusing on retrofitting existing housing to enhance energy efficiency and expand on-site renewable energy generation as part of its Scope 2 emission reduction strategy []. If the Government takes initiatives for retrofitting those houses within the next five years by 2030, it will contribute to a 3.16% reduction in its national target by 2035, equivalent to 12.73 Mt CO2-e. At the same time, it will contribute to a 9.2% reduction in emissions in the built environment sector (Appendix B for detailed calculation). This amount will contribute to the national target of 40.3 Mt CO2-e abatement from existing houses by 2050 [].
Western Australia’s Sectoral Emissions Reduction Strategy (SERS) outlines that the building sector should achieve near-zero emissions by 2050, prioritising improvements in efficiency, electrification, greater use of distributed solar and storage, and more substantial upgrades as reliance on gas decreases and to comply with the Paris Agreement, the target for the building sector is a 41% reduction in emissions by 2030 and 70% by 2040 compared to 2005 levels []. In Western Australia, this retrofitting reduces 1.3 Mt CO2-e carbon emissions yearly (Appendix B for detailed calculation), which will help the state achieve its emissions reduction targets for 2030 and 2040 Additionally, the provision of solar energy for stand-alone houses built before 2003 reduces carbon emissions by 4.6 Mt CO2-e per year by using 5 kW (25 m2) solar panel to their roof top [].

6. Conclusions

This study contextualises the key building features significantly improving energy efficiency in Australia’s Climate Zone 5, specifically in Perth, Western Australia. In Perth’s climate, the most effective retrofitting measures include improving the insulation of the building envelope, optimising the window-to-wall ratio with upgraded glazing, achieving airtightness, implementing appropriate shading, and removing overshadowing. Additional features relevant to Perth’s residential buildings include orienting the longitudinal axis of the house north–south, providing a north-facing living room with large windows; prefabricated plugin solutions are promising due to their time-efficiency and the ability to avoid occupant relocation.
The research also highlights that pre-retrofitting assessments are essential for identifying optimal interventions, which can deliver more effective outcomes than whole-house retrofitting. FirstRate5 simulations evaluated current energy demand and the reductions achievable through retrofitting. The results indicated that lowering energy demand translates into reduced energy bills and decreased emissions from the residential sector. Although FirstRate5 has certain limitations, the simulation outcomes are broadly consistent with findings reported in the literature. Retrofitting measures can improve the energy rating of case houses from below 2.3–3.3 stars to above 7.7–8.2 stars. These interventions could contribute approximately 3.16% of the carbon emission reductions required to meet Australia’s national target by 2035, equivalent to 12.73 Mt CO2-e/year. In Western Australia, such retrofitting would reduce emissions by approximately 1.3 Mt of CO2-e annually.
Furthermore, integrating 5 kW solar energy systems (25 m2) of the targeted stand-alone houses could provide an additional reduction of 4.5 Mt CO2-e/year, contributing further to the national net zero target by 2050. The main limitation of this study is the exclusion of occupants’ perspectives on retrofitting, along with the methodological constraints of FirstRate5, which relies on standardised assumptions and may not fully capture real-world conditions. Future research should consider occupants’ perspectives, use complementary modelling to capture real-world situations, and validate outcomes through longitudinal and post-occupancy studies.

Author Contributions

Conceptualization, T.M.R., A.Z. and T.A.; methodology, T.M.R. and A.Z.; software, T.M.R.; validation, T.M.R., T.A. and A.Z.; formal analysis, T.M.R.; investigation, T.M.R. and T.A.; resources, T.M.R.; data curation, T.M.R.; writing—original draft preparation, T.M.R.; writing—review and editing, T.M.R. and A.Z.; visualisation, T.M.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data will be made available upon request.

Acknowledgments

The authors sincerely appreciate the valuable feedback and insightful suggestions provided by the anonymous reviewers, which have significantly enhanced the quality of this paper.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Urbansci 09 00421 i001
Urbansci 09 00421 i002
Urbansci 09 00421 i003

Appendix B

  • ELECTRICITY CONSUMPTION AND CARBON EMISSION CALCULATION
  • Current Condition (Case Study Houses): From Simulation
Average Household Size (Case Study) = 94 m2
Average Electricity Consumption (Case Study house) = 211.57 MJ/m2
Total Electricity Consumption Case Study House = 211.57 × 94 = 19,887.58 MJ = 5524.68 kWh
  • After Retrofitting: From Simulation
Average Household Size (Case Study) = 94 m2
Average Electricity Consumption (Case Study house) = 46.73 MJ/m2
Total Electricity Consumption Case Study House = 46.73 × 94 = 4392.62 MJ = 1220.28 kWh
Energy Savings Per House = (5524.68 − 1220.28) kWh = 4304.4 kWh
(Electricity Savings by Retrofitting = 76.6% from simulation, which is close to the literature review Table 2)
  • Western Australia Scenario:
Australia’s carbon emission factor for electricity = 0.56 kg CO2-e/kWh []
Number of stand-alone houses in WA = 769,038 nos []
(70% Household Built Before 2003 []) Stand-alone House Built Before 2003 in Western Australia = 769,038 × 70% = 538,326 nos
Total emissions avoided/reduction for Western Australia = 4304.3 kWh × 0.56 = 2410.41 =2.4 t CO2-e/household = 2.4 × 538,326 nos = 1.3 Mt CO2-e
  • Australia Scenario:
Australia’s carbon emission factor for electricity = 0.63 kg CO2-e/kWh []
Number of stand-alone houses in Australia = 6710,582 nos []
(70% Household Built Before 2003) Stand-alone House Built Before 2003 in Australia = 6,710,582 × 70% = 4,697,407 nos.
Total emissions avoided/reduction for Western Australia = 4304.3 kWh × 0.63 = 2711.71 kg CO2-e = 2.71 t CO2-e/household = 2.71 × 4,697,407 nos = 12,729,974.97 t CO2-e = 12.73 Mt CO2-e
  • Emission Target For Australia:
Total net carbon emissions in 2005 = 610.6 Mt CO2-e [,]
Total net carbon emissions target by 2035 = 62–70% [] = 402.97 Mt CO2-e from 2005 base level (66% average).
  • Emission Reduction Achieved by Retrofitting:
Retrofitting contributes to achieving the emission target for Australia by 2035 = (12.73/402.97 × 100) % = 3.16%
Reduction contributes to the built environment sector by 2035 = 402.97 × 0.34 (34% emission caused by the built environment []) = (137 Mt CO2-e = 12.73/137 × 100) = 9.2%

References

  1. GABC. Not Just Another Brick in the Wall: The Solutions Exist. Scaling Them Will Build on Progress and Cut Emissions Fast. New York. 2025. Available online: https://globalabc.org/sites/default/files/2025-03/Global-Status-Report-2024_2025.pdf (accessed on 3 September 2025).
  2. UNEP. Beyond Foundations: Mainstreaming Sustainable Solutions to Cut Emissions from the Buildings Sector. New York. 2024. Available online: https://globalabc.org/sites/default/files/2024-11/global_status_report_buildings_construction_2023.pdf (accessed on 29 September 2025).
  3. Masson-Delmotte, V.; Zhai, P.; Pörtner, H.-O.; Roberts, D.; Skea, J.; Shukla, P.R.; Pirani, A.; Moufouma-Okia, W.; Péan, C.; Pidcock, R.; et al. (Eds.) Global Warming of 1.5 °C: IPCC Special Report on Impacts of Global Warming of 1.5 °C Above Pre-Industrial Levels in Context of Strengthening Response to Climate Change, Sustainable Development, and Efforts to Eradicate Poverty; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2018. [Google Scholar]
  4. ACT. Climate Change Authority Emissions Reduction Plan 2024. 2024. Available online: https://www.climatechangeauthority.gov.au/sites/default/files/documents/2024-10/CCA%20Emissions%20Reduction%20Plan%202024.pdf (accessed on 3 September 2025).
  5. Department of Climate Change Energy the Environment and Water. Buildings. Available online: https://www.dcceew.gov.au/energy/energy-efficiency/buildings? (accessed on 3 September 2025).
  6. Dadzie, J.; Runeson, G.; Ding, G.; Bondinuba, F.K. Barriers to Adoption of Sustainable Technologies for Energy-Efficient Building Upgrade—Semi-Structured Interviews. Buildings 2018, 8, 57. [Google Scholar] [CrossRef]
  7. Whitehouse, M.; Osmond, P.; Daly, D.; Kokogiannakis, G.; Jones, D.; Picard-Bromilow, A.; Cooper, P. (Low Carbon Living CRC); Guide to Low Carbon Residential Buildings—Retrofit; Low Carbon Living CRC: Sydney, Australia, 2018; Available online: https://apo.org.au/sites/default/files/resource-files/2019-05/apo-nid235556.pdf (accessed on 9 May 2024).
  8. ABS. Housing: Census. Available online: https://www.abs.gov.au/statistics/people/housing/housing-census/latest-release? (accessed on 3 September 2025).
  9. NatHERS. Home Energy Ratings. 2021. Available online: https://www.nathers.gov.au/owners-and-builders/home-energy-star-ratings (accessed on 7 November 2023).
  10. ABS. Greater Perth. 2021. Available online: https://www.abs.gov.au/census/find-census-data/quickstats/2021/5GPER (accessed on 19 September 2025).
  11. Nicholas, J. Why so many Australian homes are either too hot or too cold. In The Guardian; Guardian News & Media (GNM): London, UK, 2024; Available online: https://www.theguardian.com/news/ng-interactive/2024/jul/03/why-so-many-australian-homes-are-either-too-hot-or-too-cold (accessed on 10 September 2025).
  12. Australian Government. Home Energy Ratings Disclosure Framework Version 1; Canberra. 2024. Available online: https://www.energy.gov.au/sites/default/files/2024-07/home-energy-ratings-disclosure-framework-version-1.pdf (accessed on 5 September 2025).
  13. Rajagopalan, P.; Chen, D.; Ambrose, M. Investigating envelope retrofitting potential and resilience of Australian residential buildings—A stock modelling approach. Energy Build. 2024, 325, 114990. [Google Scholar] [CrossRef]
  14. Moore, T.; Berry, S.; Ambrose, M. Aiming for mediocrity: The case of australian housing thermal performance. Energy Policy 2019, 132, 602–610. [Google Scholar] [CrossRef]
  15. DCCEEW. Residential Buildings. Available online: https://www.dcceew.gov.au/energy/energy-efficiency/buildings/residential-buildings (accessed on 26 September 2025).
  16. Mills, B.; Schleich, J. Household transitions to energy efficient lighting. Energy Econ. 2014, 46, 151–160. [Google Scholar] [CrossRef]
  17. Solar Calculator. Solar Panel Efficiency. Available online: https://solarcalculator.com.au/solar-panel-efficiency/ (accessed on 26 September 2025).
  18. Solar Energy Masters. Benefits of Solar Panels. Available online: https://solarem.com.au/benefits-of-solar-panels/ (accessed on 26 September 2025).
  19. Dean, T.; Mortensen, J.; Partington, N.; Wren, M. Slattery Embodied Carbon Series: Retrofitting Reimagined. 2024. Available online: https://slattery.com.au/wp-content/uploads/2024/03/Slattery-carbon-planning-06-Retrofitting-reimagined-web.pdf (accessed on 5 September 2025).
  20. Green Building Council Australia. Our Homes Weigh a Tonne (of Carbon Per Square Metre): A Report Quantifying the Upfront Carbon in Australian Houses. 2025. Available online: https://www.cefc.com.au/media/d4kf04mx/gbca-homes-report.pdf (accessed on 20 September 2025).
  21. Baeli, M. Residential Retrofit: 20 Case Studies; RIBA Publishing, Ed.; RIBA Publishing: London, UK, 2014; Available online: https://www.ribaj.com/intelligence/residential-retrofit-20-case-studies (accessed on 10 January 2024).
  22. LETI (London Energy Transformation Initiative). LETI Climate Emergency Retrofit Guide: How Existing Homes Can Be Adapted to Meet UK Climate Targets; London Energy Transformation Initiative: London, UK, 2021; Available online: https://www.leti.uk/_files/ugd/252d09_c71428bafc3d42fbac34f9ad0cd6262b.pdf? (accessed on 20 January 2024).
  23. Biloria, N. Keen to Retrofit Your Home to Save Energy? University of Technology Sydney: Sydney, Austrila, 2022; Available online: https://www.uts.edu.au/news/2022/06/keen-retrofit-your-home-save-energy? (accessed on 10 January 2024).
  24. ECCMC. Update to the Trajectory for Low Energy Buildings. 2025. Available online: https://www.energy.gov.au/sites/default/files/2025-08/update-to-the-trajectory-for-low-energy-buildings.pdf (accessed on 20 September 2025).
  25. IPEEC. Existing Building Energy Efficiency Renovation: International Review of Regulatory Policies. 2017. Available online: https://www.dcceew.gov.au/sites/default/files/documents/existing-building-energy-effciency-renovation-international-review-regulatory-policies.pdf (accessed on 9 May 2024).
  26. Yang, X.; Chen, Z.; Zou, Y.; Wan, F. Improving the Energy Performance and Economic Benefits of Aged Residential Buildings by Retrofitting in Hot-Humid Regions of China. Energies 2023, 16, 4981. [Google Scholar] [CrossRef]
  27. Alavirad, S.; Mohammadi, S.; Hoes, P.-J.; Xu, L.; Hensen, J.L.M. Future-Proof Energy-Retrofit strategy for an existing Dutch neighbourhood. Energy Build. 2022, 260, 111914. [Google Scholar] [CrossRef]
  28. ABS. Climate Zone. Available online: https://www.abs.gov.au/ausstats/abs@.nsf/Lookup/4671.0main+features172012#:~:text=Zone%205%20%E2%80%93%20Warm%20temperate%20(low,hot%20summers%20with%20moderate%20humidity (accessed on 7 November 2023).
  29. Basińska, M.; Kaczorek, D.; Koczyk, H. Economic and Energy Analysis of Building Retrofitting Using Internal Insulations. Energies 2021, 14, 2446. [Google Scholar] [CrossRef]
  30. Ballarini, I.; Corrado, V.; Madonna, F.; Paduos, S.; Ravasio, F. Energy refurbishment of the Italian residential building stock: Energy and cost analysis through the application of the building typology. Energy Policy 2017, 105, 148–160. [Google Scholar] [CrossRef]
  31. Dehwah, A.H.A.; Krarti, M. Cost-benefit analysis of retrofitting attic-integrated switchable insulation systems of existing US residential buildings. Energy 2021, 221, 119840. [Google Scholar] [CrossRef]
  32. Lingard, J. Residential retrofit in the UK: The optimum retrofit measures necessary for effective heat pump use. Build. Serv. Eng. Res. Technol. 2021, 42, 279–292. [Google Scholar] [CrossRef]
  33. Ferreira, M.; Almeida, M.; Rodrigues, A.; Silva, S.M. Comparing cost-optimal and net-zero energy targets in building retrofit. Build. Res. Inf. 2016, 44, 188–201. [Google Scholar] [CrossRef]
  34. Leila, M.; Alidoost, S.; Norouzi, F.; Sattary, S.; Banihashemi, S. Trombe wall’s thermal and energy performance-A retrofitting approach for residential buildings in arid climate of Yazd, Iran. J. Renew. Sustain. Energy 2022, 14, 045101. [Google Scholar] [CrossRef]
  35. Aldabesh, A.; Soufi, J.; Omer, S.; Haredy, A. Unlocking the Residential Retrofitting Potential in a Three-Degree World: A Holistic Approach to Passive Design in Hot Climates. Buildings 2021, 11, 228. [Google Scholar] [CrossRef]
  36. Hejtmánek, P.; Sojková, K.; Volf, M.; Lupíšek, A. Development of a Modular Retrofitting System for Residential Buildings and Experience from Pilot Installation. IOP Conf. Ser. Earth Environ. Sci. 2019, 290, 012132. [Google Scholar] [CrossRef]
  37. Tushar, Q.; Zhang, G.; Bhuiyan, M.A.; Navaratnam, S.; Giustozzi, F.; Hou, L. Retrofit of Building Façade Using Precast Sandwich Panel: An Integrated Thermal and Environmental Assessment on BIM-Based LCA. Buildings 2022, 12, 2098. [Google Scholar] [CrossRef]
  38. Albatayneh, A.; Albadaineh, R.; Juaidi, A.; Abdallah, R.; Zabalo, A.; Manzano-Agugliaro, F. Enhancing the Energy Efficiency of Buildings by Shading with PV Panels in Semi-Arid Climate Zone. Sustainability 2022, 14, 17040. [Google Scholar] [CrossRef]
  39. Sedaghat, A.; Kalbasi, R.; Narayanan, R.; Mehdizadeh, A.; Soleimani, S.M.; Ashtian Malayer, M.; Iyad Al-Khiami, M.; Salem, H.; Hussam, W.K.; Sabati, M.; et al. Integrating solar PV systems for energy efficiency in portable cabins: A case study in Kuwait. Sol. Energy 2024, 277, 112715. [Google Scholar] [CrossRef]
  40. Yin, Q.; Li, A.; Han, C. The Role of Solar Photovoltaic Roofs in Energy-Saving Buildings: Research Progress and Future Development Trends. Buildings 2024, 14, 3091. [Google Scholar] [CrossRef]
  41. Albatayneh, A.; Albadaineh, R.; Karasneh, D. The impact of PV panels on cooling and heating loads of residential buildings in a humid subtropical climate zone. Energy Explor. Exploit. 2023, 41, 1762–1778. [Google Scholar] [CrossRef]
  42. Almushaikah, A.S.; Almasri, R.A. Evaluating the potential energy savings of residential buildings and utilizing solar energy in the middle region of Saudi Arabia—Case study. Energy Explor. Exploit. 2021, 39, 1457–1490. [Google Scholar] [CrossRef]
  43. Joshi, M.; Buddhi, D.; Singh, R. Effect of Overhang Shade on the Solar Heat Gain through Window in Composite Climatic in Mid-Western India. J. Sci. Ind. Res. 2022, 81, 1098–1106. [Google Scholar] [CrossRef]
  44. Koç, S.G.; Maçka Kalfa, S. The effects of shading devices on office building energy performance in Mediterranean climate regions. J. Build. Eng. 2021, 44, 102653. [Google Scholar] [CrossRef]
  45. Karthick, S.; Sivakumar, A.; Bhanu Chander, S.; Bharathwaj, S.; Kumar, B.V.V.N. Effect of Building Orientation, Window Glazing, and Shading Techniques on Energy Performance and Occupant Comfort for a Building in Warm-Humid Climate. In Recent Advances in Energy Technologies; Springer Nature: Singapore, 2023. [Google Scholar]
  46. Lu, W. Dynamic Shading and Glazing Technologies: Improve Energy, Visual, and Thermal Performance. Energy Built Environ. 2024, 5, 211–229. [Google Scholar] [CrossRef]
  47. Alhuwayil, W.K.; Abdul Mujeebu, M.; Algarny, A.M.M. Impact of external shading strategy on energy performance of multi-story hotel building in hot-humid climate. Energy 2019, 169, 1166–1174. [Google Scholar] [CrossRef]
  48. Nazari, S.; Keshavarz Mirza Mohammadi, P.; Sareh, P. A multi-objective optimization approach to designing window and shading systems considering building energy consumption and occupant comfort. Eng. Rep. 2023, 5, e12726. [Google Scholar] [CrossRef]
  49. Vishnubhotla, L.V.; Shanmugam, S.; Tadepalli, S. Developing climate-responsive passive strategies for residential envelopes in the warm humid climate of South India. Open House Int. 2022, 47, 428–450. [Google Scholar] [CrossRef]
  50. Ahmad, A.; Prakash, O.; Brar, L.S.; Irshad, K.; Hasnain, S.M.M.; Paramasivam, P.; Ayanie, A.G. Effect of Wall, Roof, and Window-to-Wall Ratio on the Cooling and Heating Load of a Building in India. Energy Sci. Eng. 2025, 13, 1255–1279. [Google Scholar] [CrossRef]
  51. Alsehail, A.; Almhafdy, A. The Effect of Window-to-Wall Ratio (WWR) and Window Orientation (WO) on the Thermal Performance: A preliminary overview. Environ.-Behav. Proc. J. 2020, 5, 165–173. [Google Scholar] [CrossRef]
  52. Jayaram, J.; Sundaram, L. Evaluation of Window-to-Wall Ratio, Shading Devices, and Site Vegetation for Enhanced Daylight Availability—Optimization of Fenestration for School Classrooms in Chennai. Preprints 2025. [Google Scholar] [CrossRef]
  53. Alwetaishi, M. Energy performancein residential buildings: Evaluationof the potential of buildingdesignand environmental parameter. Ain Shams Eng. J. 2022, 13, 101708. [Google Scholar] [CrossRef]
  54. Murano, G.; Magrini, A. The relation between nZEB requirements, local climate, and building features. The nZEB model application to two sample buildings, in different climatic conditions. Model. Meas. Control B 2018, 87, 180–187. [Google Scholar] [CrossRef]
  55. Amani, N. Energy efficiency of residential buildings using thermal insulation of external walls and roof based on simulation analysis. Energy Storage Sav. 2025, 4, 48–55. [Google Scholar] [CrossRef]
  56. Wang, X.; Xing, K.; Feng, X.; Li, Z. Low-energy building insulation through external wall modification: A case study on Lanzhou Academy of Painting in China. Int. J. Low-Carbon Technol. 2024, 19, 1547–1560. [Google Scholar] [CrossRef]
  57. Abdulsada, G.K.; Salih, T.W.M. The impact of efficient insulation on thermal performance of building elements in hot arid region. Renew. Energy Environ. Sustain. 2022, 7, 2. [Google Scholar] [CrossRef]
  58. Jouhara, H.; Yang, J. Energy efficient HVAC systems. Energy Build. 2018, 179, 83–85. [Google Scholar] [CrossRef]
  59. Ebrahimi, P.; Ridwana, I.; Nassif, N. Solutions to Achieve High-Efficient and Clean Building HVAC Systems. Buildings 2023, 13, 1211. [Google Scholar] [CrossRef]
  60. Brudermueller, T.; Potthoff, U.; Fleisch, E.; Wortmann, F.; Staake, T. Estimation of energy efficiency of heat pumps in residential buildings using real operation data. Nat. Commun. 2025, 16, 2834. [Google Scholar] [CrossRef]
  61. Franco, A.; Miserocchi, L.; Testi, D. HVAC Energy Saving Strategies for Public Buildings Based on Heat Pumps and Demand Controlled Ventilation. Energies 2021, 14, 5541. [Google Scholar] [CrossRef]
  62. Emami Javanmard, M.; Ghaderi, S.F.; Sangari, M.S. Integrating energy and water optimization in buildings using multi-objective mixed-integer linear programming. Sustain. Cities Soc. 2020, 62, 102409. [Google Scholar] [CrossRef]
  63. Oneda, T.M.S.; Ghisi, E. Analysing the Water–Energy Nexus Considering Rainwater Harvesting in Buildings. Water 2025, 17, 1037. [Google Scholar] [CrossRef]
  64. Knutsson, J.; Knutsson, P. Water and energy savings from greywater reuse: A modelling scheme using disaggregated consumption data. Int. J. Energy Water Resour. 2021, 5, 13–24. [Google Scholar] [CrossRef]
  65. Rashid, F.L.; Al-Obaidi, M.A.; Al Maimuri, N.M.L.; Ameen, A.; Agyekum, E.B.; Chibani, A.; Kezzar, M. Mechanical Ventilation Strategies in Buildings: A Comprehensive Review of Climate Management, Indoor Air Quality, and Energy Efficiency. Buildings 2025, 15, 2579. [Google Scholar] [CrossRef]
  66. Arun, M.; Gopan, G. Effects of natural light on improving the lighting and energy efficiency of buildings: Toward low energy consumption and CO2 emission. Int. J. Low-Carbon Technol. 2025, 20, 1047–1056. [Google Scholar] [CrossRef]
  67. Giama, E. Review on Ventilation Systems for Building Applications in Terms of Energy Efficiency and Environmental Impact Assessment. Energies 2022, 15, 98. [Google Scholar]
  68. Zahed, F.; Pardakhti, A.; Motlagh, M.S.; Mohammad Kari, B.; Tavakoli, A. The effect of airtightness required in building energy conservation regulations on indoor and outdoor originated pollutants. Heliyon 2023, 9, e20378. [Google Scholar] [CrossRef]
  69. Ambrose, M.; Syme, M. Air Tightness of New Australian Residential Buildings. Procedia Eng. 2017, 180, 33–40. [Google Scholar] [CrossRef]
  70. Ghosh, A.; Sundaram, S.; Mallick, T.K. Colour properties and glazing factors evaluation of multicrystalline based semi-transparent Photovoltaic-vacuum glazing for BIPV application. Renew. Energy 2019, 131, 730–736. [Google Scholar] [CrossRef]
  71. Hannoudi, L.; Saleeb, N.; Dafoulas, G. The impact of glass properties on the energy efficiency and embodied carbon of multi-angled façade systems. J. Clean. Prod. 2024, 437, 140725. [Google Scholar] [CrossRef]
  72. Li, X.; Wu, Y. A review of complex window-glazing systems for building energy saving and daylight comfort: Glazing technologies and their building performance prediction. J. Build. Phys. 2025, 48, 496–540. [Google Scholar] [CrossRef]
  73. Lee, Y.-J.; Kim, S.-H.; Ryu, J.-H.; Lee, K.-H. Optimizing Window Glass Design for Energy Efficiency in South Korean Office Buildings: A Hierarchical Analysis Using Energy Simulation. Buildings 2023, 13, 2850. [Google Scholar] [CrossRef]
  74. Dudzińska, A. Efficiency of Solar Shading Devices to Improve Thermal Comfort in a Sports Hall. Energies 2021, 14, 3535. [Google Scholar] [CrossRef]
  75. Ibrahim, A.; Freewan, A.; Obeidat, A. An Evaluation Study of Shading Devices and Their Impact on the Aesthetic Perception vs. Their Energy Efficiency. J. Facade Des. Eng. 2023, 11, 037–060. [Google Scholar] [CrossRef]
  76. Avcı, P.; Ekici, B.; Kazanasmaz, Z.T. A review on adaptive and non-adaptive shading devices for sustainable buildings. J. Build. Eng. 2025, 100, 111701. [Google Scholar] [CrossRef]
  77. Pérez-Carramiñana, C.; González-Avilés, Á.B.; Castilla, N.; Galiano-Garrigós, A. Influence of Sun Shading Devices on Energy Efficiency, Thermal Comfort and Lighting Comfort in a Warm Semi-Arid Dry Mediterranean Climate. Buildings 2024, 14, 556. [Google Scholar] [CrossRef]
  78. de, S.; Letschert, V.; Agarwal, S.; Park, W.Y.; Kaggwa, U. Energy efficiency improves energy access affordability. Energy Sustain. Dev. 2022, 70, 560–568. [Google Scholar] [CrossRef]
  79. Blasch, J.E.; Filippini, M.; Kumar, N.; Martinez-Cruz, A.L. Boosting the choice of energy-efficient home appliances: The effectiveness of two types of decision support. Appl. Econ. 2022, 54, 3598–3620. [Google Scholar] [CrossRef]
  80. Elangovan, A.; Babu, M. Path to sustainability: Analyzing usage intention of energy-efficient appliances. Energy Nexus 2025, 18, 100406. [Google Scholar] [CrossRef]
  81. Nguyen, H.V.; Le, B.N.; Lim, W.M.; Dang-Van, T.; Nguyen, N. Consumer purchases of energy-efficient appliances: A systematic literature review and research agenda. Energy Effic. 2025, 18, 29. [Google Scholar] [CrossRef]
  82. Aflaki, A.; Mahyuddin, N.; Al-Cheikh Mahmoud, Z.; Baharum, M.R. A review on natural ventilation applications through building façade components and ventilation openings in tropical climates. Energy Build. 2015, 101, 153–162. [Google Scholar] [CrossRef]
  83. Ma, W.; Wang, X.; Shou, W.; Wang, J. Energy-efficient façade design of residential buildings: A critical review. Dev. Built Environ. 2024, 18, 100393. [Google Scholar] [CrossRef]
  84. Meng, X.; Huang, Y.; Cao, Y.; Gao, Y.; Hou, C.; Zhang, L.; Shen, Q. Optimization of the wall thermal insulation characteristics based on the intermittent heating operation. Case Stud. Constr. Mater. 2018, 9, e00188. [Google Scholar] [CrossRef]
  85. Ascione, F.; Bianco, N.; Maria Mauro, G.; Napolitano, D.F. Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones. Energy 2019, 174, 359–374. [Google Scholar] [CrossRef]
  86. Petrosyan, A.L. Determination of optimal thermal insulation layer thickness of outer structures of buildings according to the load of heating and cooling system. IOP Conf. Ser. Mater. Sci. Eng. 2019, 698, 022058. [Google Scholar] [CrossRef]
  87. Pomada, M.; Kieruzel, K.; Ujma, A.; Palutkiewicz, P.; Walasek, T.; Adamus, J. Analysis of Thermal Properties of Materials Used to Insulate External Walls. Materials 2024, 17, 4718. [Google Scholar] [CrossRef]
  88. Bentoumi, L.; Bouacida, T.; Bessaïh, R.; Bouttout, A. Impact of thermal insulation on energy consumption in buildings. J. Therm. Eng. 2024, 10, 924–935. [Google Scholar] [CrossRef]
  89. Zhang, J.; Chen, P.; Chen, M.; Chen, Y. Analysis of Energy-Saving Effects of Different Building Exterior Wall Insulation Materials. In Environmental Governance, Ecological Remediation and Sustainable Development; Springer Nature: Cham, Switzerland, 2024. [Google Scholar]
  90. Moghaddam, S.A.; Serra, C.; Gameiro da Silva, M.; Simões, N. Comprehensive Review and Analysis of Glazing Systems towards Nearly Zero-Energy Buildings: Energy Performance, Thermal Comfort, Cost-Effectiveness, and Environmental Impact Perspectives. Energies 2023, 16, 6283. [Google Scholar] [CrossRef]
  91. Simko, T.; Moore, T. Optimal window designs for Australian houses. Energy Build. 2021, 250, 111300. [Google Scholar] [CrossRef]
  92. Chen, J.; Gong, Q.; Lu, L. Evaluation of passive envelope systems with radiative sky cooling and thermally insulated glazing materials for cooling. J. Clean. Prod. 2023, 398, 136607. [Google Scholar] [CrossRef]
  93. Ohlsson, K.E.A.; Nair, G.; Olofsson, T. Uncertainty in model prediction of energy savings in building retrofits: Case of thermal transmittance of windows. Renew. Sustain. Energy Rev. 2022, 168, 112748. [Google Scholar] [CrossRef]
  94. Vallati, A.; Di Matteo, M.; Fiorini, C.V. Retrofit Proposals for Energy Efficiency and Thermal Comfort in Historic Public Buildings: The Case of the Engineering Faculty’s Seat of Sapienza University. Energies 2023, 16, 151. [Google Scholar]
  95. Bouchlaghem, N. Optimising the design of building envelopes for thermal performance. Autom. Constr. 2000, 10, 101–112. [Google Scholar] [CrossRef]
  96. Xue, P.; Li, Q.; Xie, J.; Zhao, M.; Liu, J. Optimization of window-to-wall ratio with sunshades in China low latitude region considering daylighting and energy saving requirements. Appl. Energy 2019, 233–234, 62–70. [Google Scholar] [CrossRef]
  97. Troup, L.; Phillips, R.; Eckelman, M.J.; Fannon, D. Effect of window-to-wall ratio on measured energy consumption in US office buildings. Energy Build. 2019, 203, 109434. [Google Scholar] [CrossRef]
  98. Tawfeeq, H.; Qaradaghi, A.M.A. Optimising Window-to-Wall Ratio for Enhanced Energy Efficiency and Building Intelligence in Hot Summer Mediterranean Climates. Sustainability 2024, 16, 7342. [Google Scholar]
  99. Allouhi, A.; Boharb, A.; Saidur, R.; Kousksou, T.; Jamil, A. 5.1 Energy Auditing. In Comprehensive Energy Systems; Dincer, I., Ed.; Elsevier: Oxford, UK, 2018; pp. 1–44. [Google Scholar] [CrossRef]
  100. Al-Yasiri, Q.; Szabó, M. A short review on passive strategies applied to minimise the building cooling loads in hot locations. Analecta Tech. Szeged. 2021, 15, 20–30. [Google Scholar] [CrossRef]
  101. YourHome. Shading. Available online: https://www.yourhome.gov.au/passive-design/shading (accessed on 25 August 2025).
  102. Cuce, E. Role of airtightness in energy loss from windows: Experimental results from in-situ tests. Energy Build. 2017, 139, 449–455. [Google Scholar] [CrossRef]
  103. Insulation Extract. What Are the Requirements for Insulation in WA? 2024. Available online: https://www.insulationextract.com.au/post/what-are-the-requirements-for-insulation-in-wa (accessed on 15 September 2025).
  104. Baş, H. Energy-efficient house design in the mediterranean climate. E3S Web Conf. 2024, 546, 01003. [Google Scholar] [CrossRef]
  105. Goia, F. Search for the optimal window-to-wall ratio in office buildings in different European climates and the implications on total energy saving potential. Sol. Energy 2016, 132, 467–492. [Google Scholar] [CrossRef]
  106. V-Star Energy. Window-to-Wall Ratio. Available online: https://vstarenergy.com.au/2024/08/19/window-to-wall-ratio/ (accessed on 11 September 2025).
  107. Mohammed, A.; Tariq, M.A.U.R.; Ng, A.W.M.; Zaheer, Z.; Sadeq, S.; Mohammed, M.; Mehdizadeh-Rad, H. Reducing the Cooling Loads of Buildings Using Shading Devices: A Case Study in Darwin. Sustainability 2022, 14, 3775. [Google Scholar] [CrossRef]
  108. Echarri-Iribarren, V.; Gómez-Val, R.; Ugalde-Blázquez, I. Energy Losses or Savings Due to Air Infiltration and Envelope Sealing Costs in the Passivhaus Standard: A Review on the Mediterranean Coast. Buildings 2024, 14, 2158. [Google Scholar] [CrossRef]
  109. Wills, A.D.; Beausoleil-Morrison, I.; Ugursal, V.I. A modelling approach and a case study to answer the question: What does it take to retrofit a community to net-zero energy? J. Build. Eng. 2021, 40, 102296. [Google Scholar] [CrossRef]
  110. Governemnt of Western Australia. The Housing We’d Choose: A study for Perth and Peel. 2013. Available online: https://www.wa.gov.au/system/files/2021-05/FUT_the-housing-we-d-choose-summary.pdf (accessed on 10 January 2024).
  111. Yin, R.K. Case Study Research: Design and Methods (Applied Social Research Methods), 2nd ed.; SAGE Publications: Thousand Oaks, CA, USA, 1994; Available online: https://www.amazon.com/Case-Study-Research-Methods-Applied/dp/0803920571 (accessed on 25 September 2024).
  112. Stake, R.E. The Art of Case Study Research; SAGE Publications: Thousand Oakes, CA, USA; London, UK, 1998; Available online: https://books.google.com.au/books?id=ApGdBx76b9kC&printsec=frontcover&redir_esc=y#v=onepage&q&f=false (accessed on 10 January 2024).
  113. Akgüç, A.; Yılmaz, A.Z. Determining HVAC system retrofit measures to improve cost-optimum energy efficiency level of high-rise residential buildings. J. Build. Eng. 2022, 54, 104631. [Google Scholar] [CrossRef]
  114. Your Home. Precast Concrete. Available online: https://www.yourhome.gov.au/materials/precast-concrete (accessed on 10 May 2024).
  115. DCCEEW. Built Environment Sector Plan. 2025. Available online: https://treasury.gov.au/sites/default/files/2025-09/p2025-698821.pdf (accessed on 23 September 2025).
  116. COAG Energy Council. Report for Achieving Low Energy Existing Homes, Commonwealth of Australia 2019. 2019. Available online: https://www.dcceew.gov.au/sites/default/files/documents/report-for-achieving-low-energy-existing-homes.pdf (accessed on 10 January 2024).
  117. DWER. Sectoral Emissions Reduction Strategy for Western Australia Pathways and Priority Actions for the State’s Transition to Net Zero Emissions. 2023. Available online: https://www.wa.gov.au/system/files/2024-07/sers-final-report-20240702.pdf (accessed on 3 May 2024).
  118. DCCEEW. Australian National Greenhouse Accounts Factors: For Individuals and Organisations Estimating Greenhouse Gas Emissions. 2024. Available online: https://www.dcceew.gov.au/sites/default/files/documents/national-greenhouse-account-factors-2024.pdf (accessed on 10 January 2025).
  119. DEE. National Inventory Report 2017. 2019. Available online: https://www.dcceew.gov.au/sites/default/files/documents/national-inventory-report-2017-volume-1.pdf (accessed on 10 February 2024).
  120. Kennedy, A. Have Emissions Fallen Since 2005, and Are They the Lowest They’ve Ever Been, as Liberal MP Katie Allen Says? ABC News: Australia. 2019. Available online: https://www.abc.net.au/news/2019-11-08/fact-check-carbon-emissions-under-the-coalition/11662018 (accessed on 24 February 2024).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Download PDF
Core–Periphery Dynamics and Spatial Inequalities in the African Context: A Case Study of Greater Casablanca
Previous
Second-Life EV Batteries for PV–SLB Hybrid Petrol Stations: A Roadmap for Malaysia’s Urban Energy Transition
Next