## 3 Results and Discussion
Overall, apartment 2A is able to steal 1160 kWh from its neighbors, which would have accounted for 20% of its energy consumption in the base scenario. However, in this scenario, the average seasonal difference of indoor temperature between apartment 2A and the other heated apartment is about 3.6 \({}^{\circ}\)C, which is 1.0 \({}^{\circ}\)C lower than the one of apartment 5A in the similar scenario. From the analysis of the results it can be observed that heat transfer between a heated dwelling toward an adjacent unheated, ranges 20-25% of its theoretical energy need, which is much lower than the estimated 70-90% in available literature [10, 12, 13]. This is essentially due to the fact that the investigated building is poorly insulated (i.e., low thermal insulation both in the internal partitioning walls and towards the external environment); thus, the energy need of dwellings is mainly determined by their thermal dispersion towards the outdoor environment (compared to which the heat transfers toward other apartments are certainly lower). On the contrary, in [8, 9, 10, 12, 13] the investigated case-study buildings presented highly insulated external facades and they were mainly located in cold continental climates. The milder climatic conditions under which the present simulation has been \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**from** **to** & **1C** & **2A** & **3B** & **4C** & **5A** & **6B** & **7C** & **SA** & **9B** & **Total** \\ \hline
1C & & 25 & & 265 & & & & & 290 & kWh \\  & (0.5\%) & & (5.7\%) & & & & & & (6.2\%) & \\ \hline
2A & \(-\)25 & & 19 & & \(-\)520 & & & & \(-\)520 & kWh \\  & (-0.4\%) & & (0.3\%) & & (-8.5\%) & & & & & (\(-\)8.6\%) \\ \hline
3B & & \(-\)19 & & & & \(-\)65 & & & \(-\)85 & kWh \\  & (-0.3\%) & & & & (-0.9\%) & & & & (\(-\)1.2\%) \\ \hline
4C & \(-\)265 & & & \(-\)208 & & \(-\)303 & & & \(-\)76 & kWh \\  & (-4.2\%) & & & & (-3.3\%) & & (-4.7\%) & & & (\(-\)12.2\%) \\ \hline
5A & & 520 & 208 & & 156 & & 364 & & 1249 & kWh \\  & & (n.a.) & (n.a.) & & (n.a.) & & (n.a.) & & (n.a.) \\ \hline
6B & & & 65 & \(-\)156 & & & & 165 & 74 & kWh \\  & & (1.1\%) & & (-2.5\%) & & & & (2.6\%) & (1.2\%) \\ \hline
7C & & & 303 & & & & \(-\)13 & & 200 & kWh \\  & & & (3.9\%) & & & & (\(-\)0.2\%) & & (3.8\%) \\ \hline
8A & & & & \(-\)364 & 13 & & & 101 & \(-\)250 & kWh \\  & & & (-5.2\%) & & (0.2\%) & & & (1.4\%) & (\(-\)3.6\%) \\ \hline
9B & & & & \(-\)165 & & \(-\)101 & & \(-\)266 & kWh \\  & & & (-1.9\%) & & (-1.2\%) & & & (\(-\)3.1\%) \\ \hline \hline \end{tabular}  
* to be read row by column, (-) signs meaning that the row apartment is giving energy to the column apartment; (+) signs meaning that the row apartment is stealing energy to the column apartment.  
\end{table} 
Table 6: Percentage * of heat given or stolen between adjacent apartments, scenario a, kWh and (%). Figure 9: Indoor temperature variation of apartments 2A, 5A and 8A in a representative week of the heating season, scenario a.  
carried out also affect the extent of heat stolen, thanks to not-negligible solar heat gains, which in scenario a determine an inversion of heat exchanges during the central hours of sunny days. As a matter of fact, in a Mediterranean climate, the compensation of heat costs based on average indoor temperature [7; 8; 9] or on static heat flows [11], would tend to overestimate the stolen heat between apartments, not taking into consideration the dynamic behavior of this phenomenon. It is highlighted that the results obtained within the present research could be useful to analyze similar buildings in terms of climatic conditions and orientation. However, in order to allow a greater and general applicability of the results, it would be necessary to carry out a dedicated sensitivity analysis to the variation of the abovementioned parameters.