## 4 Discussion  
Our main goal was to determine the effect of particular parameters on the results of energy use and on the indoor air temperature of this simulated system. The focus of the research was on the use of accurate data obtained from measurements and on the possible generalization of the data needed for the simulations.  
The simulations on the validated model confirmed that five of the identified parameters (short-term large internal gains in the winter, extraction of energy caused by ventilation, short-term insufficient energy supply for cooling in the summer, window opening, use of internal roller blinds) that were mainly influenced by users did not have a significant effect on the result of energy use on an annual basis. It was also found that the last, sixth observed parameter, the adjustments of temperature setting with the room temperature controllers caused by users, had a relatively large effect on the annual use of energy. However, an additional analysis revealed that the effect of the five specific parameters contrasts with the effect of the users' temperature adjustments to the room temperature controllers. However, the effect of the users' temperature adjustments to the room temperature controllers nonetheless dominated the annual energy use.  
It can be concluded that the individual effects of usually unknown specific parameters can be relatively low, but their common effect can considerably reduce the largest effect on energy use, i.e., the users' temperature adjustments to the room temperature controllers. Moreover, if the temperature setting of the room regulators used in such a simulation model would take into account the users' adjustments of the temperature with the room temperature controllers, these lower effects could cancel out the largest one, i.e., the room regulator temperature adjustments, almost completely.  
The analysis of the results clearly showed that for the energy simulation the model does not need very accurate data (which are usually unknown). Therefore, parameters such as manual window opening and manual shading can also be predicted or simplified to certain fixed values. However, this is not the case when it comes to evaluating the indoor air temperatures due to the necessity of providing user comfort. That is why it is necessary to include in the models an additional indicator of the modeled indoor environment, i.e., the indoor air temperature. As confirmed by this research, the simulated indoor air temperature showed that a particular solution that meets the targeted requirements for maximum energy efficiency could negatively affect a user's thermal comfort. Therefore, the choice of solutions based exclusively on the favorable results of the energy use of individual variations is by no means recommended.  
This research addressed very detailed parameters within one specific building with a particular system, i.e., offices equipped with radiant ceiling panels. The obtained results, of course, relate to this system. However, most of these parameters generally and in most cases vary independently of the type of heating/cooling system or are virtually unaffected by the heating/cooling system's influence. It could, therefore, be expected that an analysis of such parameters in buildings of the same type would show very similar results. Consequently, our results could probably be applied generally, although the present study was primarily focused on offices equipped with radiant ceiling panels.