## 1 Introduction
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Set-Point Range (’C’)**} & \multicolumn{2}{c}{**Building**} & \multicolumn{2}{c}{**Location**} & \multicolumn{2}{c}{**Study**} & \multicolumn{2}{c}{**Data Source**} & \multicolumn{2}{c}{**Comment**} & \multicolumn{1}{c}{**Reference**} \\ \hline
**Heating** & **(Ref.)** & **Cooling** & **(Ref.)** & **Type** & **Location** & **Subject** & & & Adjusting the cooling set-point temperature from 20 \({}^{\circ}\) C to 24 \({}^{\circ}\) C reduces the energy demand by 9.4\%. The experimental facility’s thermal & 285 \\ - & & 20.0–24.0 & (20.0) & Experimental facility & Not stated & Energy savings & Field & 99.4\%. The experimental facility’s thermal & 285 \\  & & & facility & & savings & & envelope characteristics are not specified nor are the weather conditions. The conclusions can have limited extrapolation capability and application to other cases. & \\ \hline
0.31T\({}_{\rm p+14.3}\) & (20.0) & 0.31T\({}_{\rm p+21.3}\) & (25.0) & Residential & Spain & Energy savings & & Assessees the impact of the prevailing mean outdoor temperature on the definition of adaptive comfort bands and their impact on the energy consumption of residential HVAC systems. \(T_{\rm p}\) corresponds to the prevailing mean outdoor temperature. & 295 \\ \hline
0.33T\({}_{\rm p+14.8}\)+AT & (22.5) & 0.33T\({}_{\rm p+18.8}\)+AT & (24.5) & Residential & Portugal, Spain, Italy, and Greece & Energy savings & & Assessees the impact of implementing an adaptive set-point temperature [30] on energy demand for different cities across southern Europe. Due to the number of locations, it assumes only one type of residential building and a construction solution. & 31 \\
0.33T\({}_{\rm p+14.8}\)+AT & (20.0) & 0.33T\({}_{\rm p+14.7}\) & (25.0) & Residential & Spain & Energy savings & & Evaluates the potential of energy savings:by implementing an adaptive set-point temperature [30] for two residential buildings. An adaptive set-point temperature on reduce 40\%. of energy demand for heating and cooling. Focuses only on three types of Spanish climates (B4, D3, and E1). \(T_{\rm o}\) corresponds to the running mean outdoor temperature according to E1 16798-12019 standard [30]. & & Evaluates the potential of energy savings:by implementing an adaptive set-point temperature [30] for two residential buildings. An adaptive set-point temperature on reduce 40\%. of energy demand for heating and cooling. Focuses only on three types of Spanish climates (B4, D3, and E1). \(T_{\rm o}\) corresponds to the running mean outdoor temperature according to E1 16798-12019 standard [30]. & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._On the other hand, the occupant's thermal comfort may be affected depending on how far we go with changes to the thermostat. For cooling in office buildings, small changes in the room temperature are not perceived by the occupant [16], and if they are encouraged, they prefer a low comfort level [21]. However, increasing the room temperature above 27 \({}^{\circ}\)C reduces the thermal acceptance below 80% [20]. Conversely, in residential buildings during the winter season, reducing the room temperature to 18 \({}^{\circ}\)C diminishes the thermal acceptance by the occupants by 70% [33]. Nevertheless, the high acceptability for a such low temperature can be conditioned by the economic constraints of the householders, the quality of the indoor environment, and the clothing adaptability of the occupants [33]. The definition of the temperature set-point is challenging; on one side we can have higher savings, and on the other side, we can have unsatisfied users [24]. Assuming that the occupants can adapt to less favourable conditions, some authors explored the impact of using an adaptative set-point temperature on residential buildings, where the savings can be very expressive in some cases [23; 26; 27; 29; 31; 32].