## 2 Methodology
### Case Study  
For simulations, a virtual prototype building was designed (see Figure 4). This prototype case study is an ideal residential building designed according to the minimum energy demand criteria established for new buildings in the countries analyzed [65; 66]. It is a building with a rectangular floor plan of dimensions of \(12\times 10\) m and it has two dwellings per floor. The internal space of each dwelling is divided into a bedroom, a bathroom, a kitchen, a living room, and a corridor. The use of a virtual prototype of case studies to establish considerations and operational hypotheses has been used in various studies: (i) [PERSON] et al. [66] used a virtual prototype of a two-story building to analyze optimal solutions in the life cycle of an autonomous building; (ii) [PERSON] and [PERSON] [67] designed a virtual test-room to analyze the influence of the periodic thermal transmittance and the internal areal heat capacity on the energy demand of the interior space; (iii) [PERSON] et al. [68] and [PERSON] et al. [69] designed a wide variety of virtual prototypes of residential buildings using the Evolutionary Program for the Space Allocation Problem algorithm to assess the influence of thermal properties on energy performance; (iv) [PERSON] [70] and [PERSON] et al. [71] analyzed different virtual prototypes of buildings included in the ASHRAE Standard 90-2010 to evaluate energy conservation measures; (v) [PERSON] et al. [72] analyzed the performance of the variable refrigerant flow and the rooftop variable air volume systems in a virtual prototype of an office building; (vi) [PERSON] and [PERSON] [73] used a virtual prototype of a single-family home to assess the effect of occupancy on energy performance; (vii) [PERSON] and [PERSON] [74] used a four-story virtual office building to evaluate the installation of daylight controllers; (viii) [PERSON] et al. [75] used a virtual prototype of the Pacific Northwest National Laboratory office building to analyze air leaks in the parallel fan-powered  
Figure 3: Examples of the internal operative temperature obtained in the current scenario in the city of Seville with adaptive models with tolerance of 0.00, 1.50, and 3.00 \({}^{\circ}\)C, and the static model. The heating setpoint temperature is represented in red line, and the cooling setpoint temperature in blue line. terminal units; (ix) [PERSON] et al. [57] used a virtual prototype of a residential building to assess its energy demand with climate change in different cities in Europe. Regarding the virtual prototype used in the research, it is important to highlight that, to reduce the elements through which heat transfers take place, the case study corresponded to an intermediate floor, so that heat losses or gains produced through the roof were reduced. Given the aim of this study (analyzing the effect of the variation of setpoint temperatures on the energy consumption), both thermal properties and the load profile were the same in all locations, so there were no other factors varying the energy consumption: variations in the energy consumption were caused by setpoint temperatures. The thermal properties of the vertical elements are specified in Table 3. Regarding windows, a design with a thermal transmittance of 4.2 W/(m\({}^{2}\)K) and a constant solar heat gain coefficient (SHGC) of 0.6 were used. Regarding the load profile, a similar profile than that used in previous research studies was used [42; 48]. Figure 5 presents the hourly percentage contribution of each load. The profile considers that the occupancy of the case study varies depending on the day: from Monday to Friday, the occupancy varies from 25 to 100%, whereas Saturdays and Sundays the case study has an occupancy of 100%. The load of lighting devices and equipment has the same usage profile, which varies depending on the time of the day.