## 3 Results and Discussion

Table 10: Electricity consumption in campus buildings in 2022. Figure 6: Building studio’s heating demand calculation process. Given the electricity consumption associated with VRF systems and the heating demand in 2022 in Building B2, the SCOP in 2022 \(\left(SCOP_{month/year}^{2022}\right)\) is determined. Since the determined SCOP value corresponds to the climatic conditions of 2022, the CF for the typical climatic year in Segovia is applied and this is calculated using Equation (2). Table 12 shows the following values for the months of the heating period: the monthly heat demand in 2022 for Building B2 \(\left(D_{H\left(B2\right)}^{2022}\right)\), determined from the specific demand for both buildings, and electricity consumption VRF in 2022 for Building B2 \(\left(E_{EVRV}^{2022}\right)\), which is determined by subtracting the base electricity consumption from the electricity consumption. Monthly Seasonal Coefficient of Performance (VRF) in 2022 \(\left(SCOP_{month/year}^{2022}\right)\) is determined as the quotient between the heat demand and the electricity consumption in 2022. The following temperatures are recorded: Monthly Dry Temperature in 2022 \(\left(T_{d}^{2022}\right)\) and Monthly Dry Temperature in RC \(\left(T_{d}^{RCZ}\right)\). The SCOP is linked to the outside temperature, which allows for determining a CF coefficient, which relates SCOP to the climatic conditions, and, finally, the Monthly Seasonal Coefficient of Performance (VRF) in RCZ \(\left(SCOP_{month/year}^{RCZ}\right)\) is determined. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Month**} & \multirow{2}{*}{\begin{tabular}{c} **B1** \\ **ECP22** \\ **(kWh)** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **B2** \\ **D16** \\ **(kWh)** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **B2** \\ **D17** \\ **(kWh)** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **B2** \\ **D18** \\ **(kWh)** \\ \end{tabular} } \\ \hline January & 230,650 & 219,579 & 39.39 & 321,350 \\ February & 174,666 & 166,282 & 29.83 & 243,350 \\ March & 197,583 & 188,099 & 33.74 & 275,285 \\ April & 112,634 & 107,228 & 19.23 & 156,930 \\ May & - & - & - & - & - \\ June & - & - & - & - \\ July & - & - & - & - \\ August & - & - & - & - \\ September & - & - & - & - \\ October & 40,236 & 38,305 & 6.87 & 56,060 \\ November & 60,181 & 57,292 & 10.28 & 83,850 \\ December & 85,746 & 81,630 & 14.64 & 119,464 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: NG consumption, Building B1 demand, specific heating demand, and Building B2 demand. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Month**} & \multirow{2}{*}{ \begin{tabular}{c} **D16** \\ **(kWh)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **(E202** \\ **(kWh)** \\ \end{tabular}  )} & \multirow{2}{*}{ \begin{tabular}{c} **SCOP** \\ **(kWh)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **D202** \\ **(kWh)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **T4** \\ **(kWh)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **R2** \\ **(kWh)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **T6** \\ **(\(\lx@sectionsign\)**C)** \\ \end{tabular}  } & \multirow{2}{*}{\ \begin{tabular}{c} **FC** \\ **(\(\lx@sectionsign\)**C)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **SCOP** \\ **(\(\lx@sectionsign\)**C)** \\ \end{tabular}  } \\ \hline January & 321,350 & 69,445 & 4.627 & 1.68 & 4.88 & 0.987 & 4.567 \\ February & 243,350 & 54,574 & 4.459 & 4.44 & 6.41 & 0.992 & 4.423 \\ March & 275,285 & 56,048 & 4.912 & 7.38 & 8.24 & 0.997 & 4.897 \\ April & 156,930 & 20,647 & 7.601 & 8.75 & 10.55 & 0  
VRF systems exceed the regulatory SCOP threshold of 2.5, meeting 83% of the energy demand through the use of renewable energy sources. Building B1 is predominantly heated using a low-temperature water system with a Low-Temperature Condensing Boiler (LTCB) for climate control, which consumes NG, along with a pumping system consuming electricity.