The building envelope plays a significant role in the energy performance of buildings and windows are a key element in transmitting heating and cooling between the indoor and outdoor environment, and hence an adequate window system is one of the most important retrofit strategies of existing buildings for energy conservation. Therefore, this study presents a method with a theoretical case study to examine the improvement of energy efficiency in a typical high-rise residential building through window retrofitting. A building energy design model in Designbuilder along with a building information modeling (BIM) model in Revit are developed, with 20 common potential glazing alternatives being analyzed to predict the potential energy savings in the same case building with identical orientation located in a variety of climate zones in China. Based on different parameters and considerations, the results demonstrated that the currently relatively expensive low-e window glazing has the best energy performance in all climate zones, but is sufficiently close to conventionally glazed windows in its energy efficiency to discourage its adoption at present, and that, instead, a single dark conventional glazed window is preferred in a hot summer/warm winter climate, double dark traditional glazing in a hot summer/cold winter climate, and a double clear conventional window in a cold climate. Based on the simulated results, an indicative suggestion was provided to select an adequate window system for residential building retrofitting in the studied climates or similar climatic regions.

This study presents a data-driven retrofitting approach by systematically analyzing the energy performance of existing high-rise residential buildings using a normative calculation logic-based simulation method. To demonstrate the practicality of the approach, typical existing buildings in five climate zones of China are analyzed based on the local building characteristics and climatic conditions. The results show that the total energy consumption is 544 kWh/m²/year in the severe cold zone, which is slightly higher than that in the cold zone (519 kWh/m²/year), but double that in the hot summer and cold winter zone, three times higher than that in the warm zone, and five times above that in the temperate zone. The dominant energy needs in different climatic zones are distinctive. The identified potentially suitable retrofitting measures are important in reducing large-scale energy consumption and can be used in supporting sustainable retrofit decisions for existing high-rise residential buildings in different climatic zones.

This study aimed to develop a deterministic decision-making mechanism for finding the optimum set of retrofit solutions of existing high-rise residential buildings in two different climatic zones of China. The retrofit solutions were critically examined with different energy saving targets based on the local climatic conditions, building features, and retrofit costs in cold and severe cold zones comparatively. By making the extensive review and analyzing considerable statistics data and cost information, net present value (NPV) method was employed in the prototype building apartments to develop this deterministic model. The results demonstrated that the heating system is the most important factor in saving energy and obtaining the optimum revenue in these two regions. The highest optimal NPV can be obtained by achieving 60% energy saving in the cold zone, as energy saving is around 319 kWh/m²/year with the total retrofit costs of USD $3560, while it is 281 kWh/m²/year with the total retrofit costs of USD $3480 to achieve the 50% energy-saving target in the severe cold zone. Based on the analysis of energy savings and retrofit costs, the results can be effectively implemented for the purpose of creating sustainable retrofits in existing buildings, and the model can be adapted for selecting appropriate retrofit choices in other climatic zones.

Local data about indoor thermal comfort are in short supply, which are always different from the predicted results produced by models shown in previous studies. Shopping malls that consume substantial energy need to save energy, provided that thermal comfort is maintained. Therefore, this research investigated indoor thermal comfort using field measurements and questionnaires in a typical shopping mall in Danyang, China, with a hot summer and cold winter climate in order to explore local demands and energy-saving potential. The findings are as follows: (1) The average air temperature ($T_a$) and operative temperature ($T_{op}$) are 26.7 °C and 26.4 °C, which implies a minor influence from radiation and other factors on $T_a$. Women are more sensitive to changes in outdoor temperature since clothing insulation ($I_{cl}$) varies by gender: 0.31 clo and 0.36 clo for male and female individuals, respectively. (2) The thermal neutral temperature (TNT) derived from the thermal sensation vote (TSV) is 25.26 °C, which is significantly higher than the 21.77 °C obtained from the predicted mean vote (PMV) model. (3) There is a wide range of acceptable temperatures for thermal comfort because the highest temperature was identified by the thermal comfort vote (TCV) at 27.55 °C, followed closely by 27.48 °C, 26.78 °C, and 25.32 °C, which were separately derived from the thermal acceptance vote (TAV), TSV, and predicted percentage of dissatisfied (PPD) people; these were based on an upper limit of the acceptable 80% range. (4) In total, 94.85% of respondents accepted the indoor air quality, although the median concentration of CO₂ was 772 ppm, and the neutral relative humidity level was 70.60%. Meanwhile, there is an important relationship between air quality satisfaction and operative temperature; thus, the temperature (26.93 °C) with peak satisfaction can enhance air quality perception and thermal comfort. (5) The energy savings that can be achieved are 25.77% and 9.12% at most based on acceptable thermal comfort compared with baseline energy consumption at 23 °C and 26 °C, respectively.