## 4 Results  
In Section 1, the methodology is shown and in Section 2 it is particularized for 12 case studies. The results obtained in each step are presented below. The first step, after the case studies are presented, is the application of the tabu algorithm to obtain an optimal solution in LCC, taking into account the costs of the construction elements of the building envelope. The solution is shown in Table 5. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**Irradiation**} \\ \cline{3-5}  & & \multicolumn{2}{c}{**Horizontal**} & \multicolumn{2}{c}{**Optimally**} & \multicolumn{2}{c}{**Plane at Angle:**} & \multicolumn{2}{c}{**Optimal**} \\
**Climatic Zone** & **City** & \multicolumn{2}{c}{**Plane**} & \multicolumn{2}{c}{**Inclined Plane**} & \multicolumn{2}{c}{**90 deg.**} & **Inclination** \\ \cline{3-5}  & & \(H_{B}\) & \(H_{opt}\) & \(H_{90}\) & \\  & & **(Wh/m\({}^{2}\)/day)** & **(Wh/m\({}^{2}\)/day)** & **(Wh/m\({}^{2}\)/day)** & **\(I_{opt}\) (deg.)** \\ \hline A3 & Málaga & 5210 & 5990 & 3710 & 33 \\ \hline A4 & Almería & 5310 & 6130 & 3820 & 34 \\ \hline B3 & Valencia & 4960 & 5840 & 3800 & 36 \\ \hline B4 & Sevilla & 5200 & 5980 & 3720 & 33 \\ \hline C1 & Bilbao & 3540 & 4060 & 2700 & 35 \\ \hline C2 & Barcelona & 4630 & 5510 & 3670 & 37 \\ \hline C3 & Granada & 5170 & 5950 & 3710 & 33 \\ \hline C4 & Cáceres & 4980 & 5760 & 3650 & 34 \\ \hline D1 & Lugo & 3960 & 4560 & 2990 & 35 \\ \hline D2 & Valladolid & 4590 & 5310 & 3420 & 34 \\ \hline D3 & Madrid & 4860 & 5680 & 3670 & 35 \\ \hline E1 & Soria & 4510 & 5250 & 3440 & 35 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Global irradiation data. Comparing the results shown in Tables 3 and 5, it can be observed that the changes regarding the passive elements of the building allow us to improve the energy efficiency. From the human design with the energy rating label C (Table 3) to energy rating label B (Table 5). However, to achieve the highest rating, the use of renewable energy would be necessary. Comparing Tables 3 and 5, there was a certain reduction in demand. The improvement in heating demand can lead to an increase in cooling need. The locations in the north of Spain have greater heating need, see Bilbao (C1) and Soria (E1) with a higher demand for heating comparing to Seville (B4) where the demand is lower and more balanced. Likewise, the LCC of the same building to achieve similar energy efficiency is higher for cold climates. After the optimization of elements in the first step, in the second step a new optimal solution includes the active elements. The solution is shown in Table 6. This table shows data regarding the demand, the decision taken regarding the number of solar panels, their characteristics, those of the necessary inverter, and lastly, the estimation of the LCC and the EEI. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & & & & & & & & & & & & & & \\ \cline{2-11}  & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** & **11** & **12** \\ \hline
**Climatic Zones** & **A3** & **A4** & **B3** & **B4** & **C1** & **C2** & **C3** & **C4** & **D1** & **D2** & **D3** & **E1** \\ \hline \multicolumn{11}{c}{**Needs**} \\ \hline Heating demand & 4 & 3.3 & 4.45 & 6.52 & 22.5 & 7.71 & 10.3 & 10.3 & 28.4 & 26.3 & 16.1 & 34.8 \\ \hline Cooling demand & 3.64 & 5.89 & 6.82 & 7.7 & 0 & 3.39 & 4.33 & 10.8 & 0 & 1.44 & 4.97 & 0.41 \\ \hline \multicolumn{11}{c}{\% Renewables} & 100 & 100 & 100 & 100 & 100 & 100 & 100 & 61 & 94 & 100 & 64 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Building envelope and active element with optimization.