## 3 Results
### Template-Based Thermal Comfort with Cooling  
To get insights into the impact of future weather scenarios for heating and cooling loads, the use case is first simulated with enabled heating and cooling set points. Figure 5 displays heating and cooling loads for the weather scenarios, showing a major decrease of the heating loads (\(-36.04\,\%\) for 2050 and \(-51.96\,\%\) for 2080). The observed cooling loads drastically increase by \(174.60\,\%\) for 2050 and \(256.15\,\%\) for 2080. These calculated energy loads for heating and cooling align with the observations from related research [19; 68] for future climate scenarios for the years 2050-2100.  
The analysis of the heating and cooling loads shows that in future climate scenarios, significantly higher energy demands occur to meet the cooling set points and likewise the thermal comfort requirements. For an overview on the impact of climate change on thermal comfort under the previously defined conditions, Figures 6  
Figure 4: Use Case: FZK Haus.  
Figure 5: Annual energy demand for heating and cooling per building floor area.  
\begin{table}
\begin{tabular}{l l l} \hline \hline  & **Heating** [\({}^{\circ}\)C] & **Coiling** [\({}^{\circ}\)C] \\ \hline Living & 21 & 28 \\ WC Residential & 24 & 32 \\ Kitchen Residential & 20 & 26 \\ Single office & 21 & 26 \\ Traffic area & 18 & 32 \\ Bedroom & 21 & 28 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Heating and cooling set points.  
mean PMV values per thermal zone (solid lines) and the daily mean outdoor temperature (dashed line) for the summer months between April and October.  
For TMYx (2007-2021), the daily mean PMV ranges from \(-1.21\) (Living_2) in December to 1.73 (Bedroom) in July. For SSP5-8.5 (2080), the daily mean PMV ranges from \(-1.04\) (Living_2) in January to 2.06 (Traffic area) in August. The characteristics of the PMV reflect the set points and weather data that have been used for simulation. The cooling set points are reflected in the PMV data, where the PMV reaches a \"plateau\" in summer (e.g., for the Single office) since the choice of cooling set points indirectly limits the level of PMV. The weather data are reflected in the PMV, where the outdoor temperature has a qualitatively high similarity with the PMV, which is true for the PMV in Figure 6 for the TMYx weather data, but only in April, May, and October for the SSP-5-8.5 weather data in Figure 7. We can observe a stronger correlation between outdoor temperature and PMV for the TMYx data here since the cooling set points are only reached for a smaller period in summer than for the SSP5-8.5 weather scenario.  
For TMYx (2007-2021) data, the low PMV during winter is caused by larger differences between zone mean air temperature (used for set point control) and the actual operative  
Figure 6: TMYx (2007–2021) mean daily PMV with cooling.  
Figure 7: SSP5-8.5 (2080) mean daily PMV with cooling.  
air temperature that has been used to calculate the PMV (i.e., even with a set point of 21 \({}^{\circ}\)C, the actual operative temperature was below 20 \({}^{\circ}\)C, causing occupants to feel cold). For the SSP5-8.5 (2080) scenario, the least comfortable status can be seen in the thermal zones without cooling (e.g., traffic area). For the analysis of the proposed clothing and activity parameters, a larger range of set points and building types needs to be tested, ideally supported by measured data and validation.  
In Germany, most of the building stock (residential but also a large amount of public office buildings and schools) rely on natural ventilation and do not have cooling devices. Thus, as for fully conditioned buildings, thermal comfort can be accomplished by spending more energy (or by choosing a resilient building design during the design stage, which also could be supported by our proposed methods); we perform a more detailed analysis of our approach without cooling.