## 3 Results and Discussion  
Besides the design phase of the plants and of the control logic, the authors carried out an extensive analysis of recorded data during the period May 2012-April 2017 for the first case study. Furthermore, they realized a detailed dynamic simulation for the second case study. In both cases, the main scope was to analyze the energy performance of the plant. Here the main results are very briefly summarized [19; 20]. First Case Study: The Importance of Monitoring for the Energy Performance during the Years Operation  
Referring to Figure 7, many cumulative energy flows were logged hourly:  
* Condenser and evaporator of each heat pump (at the collectors);
* Ground circuits, separately for ventilation and space heating;
* Primary circuit of AHU heating coils and run-around coils;
* Solar circuit;
* Primary circuit of the radiant floor. The natural gas (NG) consumption obtained from the monthly bills was almost steady or in a slight decrease during the 2012-2017 period, so the management was not worried at all. Instead, the availability of data records and a careful analysis allowed us to identify the bad working of the solar section for long periods (due to the failure of one single collector without its replacement), and the wrong priority of the boiler with respect to the heat pumps (Table 4). As a consequence, the total PER (\(\text{PER}_{\text{tot}}\), the ratio between the useful thermal energy produced (for heating and for ventilation by heat pumps, boiler, and free renewable energy (solar + static recuperator)), and the primary (non-renewable) energy consumed) in the 14/15 and 15/16 heating seasons decreased noticeably with respect to the first two (12/13 and 13/14) (Figure 10). The monitoring of energy data revealed that the \(\text{PER}_{\text{tot}}\) and the specific primary energy (PE) demand (NG consumption (expressed in kWh) per square meter of heated area) newly featured acceptable values during the last season 2016-2017, due to the correct operation of the solar field and the heating section heat pumps, even in the presence of a long heat pump stop for maintenance. A comparison was carried out between the monitored seasons in terms of the annual thermal energy supply, the NG consumption, and the HDD (Figure 11). The percentage variation of supplied energy and NG consumption with respect to the first heating season is reported as well. The main information from the figure is that the comparison based on NG consumption only can be misleading. For example, during the 2013/2014 season (the one with the highest efficiency, Figure 10), NG consumption was 9% lower than the 2015/2016 season, even if the supplied thermal energy was 16% higher. As a matter of fact, other than HDD variables influence the building energy demand as can be observed by a thermal demand 16% higher in the 13/14 season with respect to the 15/16, even with a 11% lower HDD. For example, different settings in the room thermostats by lowering the values of 23-24 \({}^{\circ}\)C (recorded during the first years of operation) or by attenuating the \begin{table}
\begin{tabular}{c c c c} \hline \hline  & & **Heating Section** & \\ \hline
**Heating Season** & **Generator Priority** & **Generator Backup** & **Solar Field** \\ \hline
2012–2013 & HP3 + HP4 & Condensing boiler & 09/12–04/13 OFF \\
2013–2014 & HP3 + HP4 until 02/14, then & Condensing boiler till 02/14, & Till 12/13 OFF \\  & condensing boiler & then HPs & \\
2014–2015 & Condensing boiler & HP3 + HP4 & 08/14–04/15 OFF \\
2015–2016 & Condensing boiler & HP3 + HP4 & 05/15–04/16 OFF \\  & condensing boiler until 01/17, & HP3 + HP4 until 01/17, then & \\  & then HP3 + HP4 first & condensing boiler & 05/16–09/16 OFF \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Heating section generator priority and solar field operation during the five heating seasons monitored. temperature during Christmas holidays can be one effective variable.