# Sustainable Building Tool by Energy Baseline: Case Study
## 3 Case Study  
A classroom building on the UAO University campus (Figure 3), is studied as an application of the EnBL. The UAO University campus has seven buildings in operation [58]. The campus has four classroom buildings with four floors, offices, and classrooms mainly for undergraduate and postgraduate classes, a university wellness building where offices and cafeterias are located, a gym building with lightning toward the football fields, and lots. On the UAO campus, electrical energy is distributed through 3 substations that feed different sectors of the campus. Substation one, with a capacity of 500 kVA, provides loads to the main building; substation two has a power capacity of 1000 kVA, and it feeds loads to the common areas of the campus, the four classroom buildings, the university wellness building, and the Physical Conditioning and Health Centre (CAFS). Substation three, with a capacity of 800 kVA, feeds the air conditioning system of the main building, except for its handlers. Regarding photovoltaic solar energy, there are eight solar systems on the roofs of parking lots, classrooms, the main building, and the university wellness building. The solar generation is connected to the nearest distribution boards; the total installed capacity is 404 kWp. The UAO campus has an electrical energy measurement system that monitors consumption. This system has 19 SCHNEIDER meters with telemetry systems that collect information on active, reactive, and apparent power and energy with a 15-min periodicity; the data are reported and stored in Power Monitor-CGE software (V7). The methodology proposed above is also used for study to analyze the best model for the selection of the EnBL. Figure 4a,b show the southwest and northwest views of the lecture hall building, as designed using Design Builder software for dynamic energy simulation. The boundaries of this research are set on the case study. The analysis period corresponds to three consecutive years. Experimental data have been obtained through monitoring. The data used for the analysis of the different methods applied to obtain LBEn are energy monitoring data with a recording frequency of 15 min per variable, data from the weather station installed at the university and the IDEAN weather station, and occupancy data. In this case, the data include the semester schedule of classes and the occupancy. Figure 3: Lecture hall building of a university campus. Several issues related to data precision have been identified, particularly the lack of calibration in several installed meters and the recurrent communication failures between the meters and data management software, which result in unrecorded measurements. These are systematic errors that significantly affect data analysis and the accuracy of forecasting models. Additionally, in terms of building occupancy, there is uncertainty related to academic scheduling and the use of classrooms, auditoriums, and offices, further complicating energy consumption predictions. The analyses of the relevant variables and static factors include the information provided during the study period. As a whole, they include data from meteorological stations installed at the UAO University that provide the climatological variables. In addition, information on educational planning is obtained that is related to the occupation of different spaces and the energy consumption of the building. The final energy consumption of the building is also obtained. In this case, it constitutes the dependent variable. It comprises the consumption of the electric meter located in the building, plus the energy generated by the photovoltaic (PV) panels installed on the roof. The daily dry outdoor air temperature is calculated from the hourly information available from the weather station. The daily relative humidity of the outside air is available from the weather station. The average solar radiation is calculated considering the daily radiation time (direct and diffuse radiation).