## 3 Results
### Effect of Six Specific Parameters Included in the Validated Model
The analysis of the results indicated that some short-term, yet large, inputs have a very small influence on the annual energy level. At the same time, continuous dynamics, such as the use of internal roller blinds, have a very small positive effect in one season and a negative one in another. On the annual level, however, its effect is insignificantly small, as it amounted to only 0.5%. Two inputs in this analysis, i.e., the window opening and the extraction of extra heat with the exhausted air of the mechanical ventilation system due to air-temperature difference, did result in a large effect during one season of 7.0% and more. Their total annual energy effects were thus 3.2% and 3.5%, respectively (Figure 3). The simulations confirmed that the integration of the first five identified parameters had a predominantly moderate but opposite effect on the energy use (decrease or increase) in a particular season. Therefore, they did not have a significant influence on the result of the energy use for a whole year. However, in total they slightly reduced the annual use of energy. Additionally, the analysis proved that, compared with these parameters, the effect of the last, sixth examined parameter, the adjustments of the temperature setting using the room temperature controllers made by users, was the greatest. The use of energy for cooling increased significantly, which is why the annual energy use increased as well. The analysis revealed that the effect of the five specific parameters contrasts with the effect of the data for the users' temperature adjustments of the temperature setting on the room temperature controllers (they are counteracting). The latter is also the largest; therefore, it dominated in the total annual energy use. It is also clear that the individual effects of specific inputs can be relatively small,  
Figure 3: Simulated energy and indoor air temperatures for variations without a specific parameter in comparison with validated model (V. M.): A—without large internal gains; B—without extraction of energy with exhausted air; C—without insufficient energy supply for cooling; D—without window opening by occupants; E—without use of internal roller blinds; F—without temperature adjustments using regulators; and G—without all six specific parameters. but their total influence can considerably reduce this largest effect caused by the users when adjusting the room temperature controllers. At the same time, the simulations also showed one very important fact, which is the relatively large effect on the indoor air temperature in the rooms. In the case when we eliminated all six identified parameters from the model, the average indoor air temperature in the cooling season was noticeably higher; it amounted to 0.85 K (Figure 3). It is clear that the largest contribution to this deviation was caused by the sixth parameter. Based on the results of this research we can assume that the interactions of energy effects of such usually unknown parameters could be to a large extent eliminated, in the manner that all the parameters together do not have a significant effect on the result of annual energy use. However, the same does not apply to the indoor air temperatures, for which the results showed crucial and non-negligible deviations.