# Energy Demand and Supply Simultaneous Optimization to Design a Nearly Zero-Energy House
## 3 Results
### Energy Objective--Integrated Optimization  
To complete the analysis, integrated optimization was performed to minimize the total primary energy objective function (Equation (3)). Results are reported in the summary in Table 7.  
Since the objective function of the optimization process did not consider any costs, the reported results were representative of the best performance that could be reached for the defined set of design \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Parameter** & **Unit** & **Energy-Optimal Value** & \
\begin{tabular}{c} **Relative** \\ **Frequency** \\ **(All)** \\ \end{tabular} &
\begin{tabular}{c} **Relative** \\ **(Neigh.)** \\ \end{tabular} \\ \hline \multirow{6}{*}{Building parameters} & ResO & [m\({}^{2}\)K/W] & 9.0 & 12\% & 18\% \\  & TO & [m] & 0.5 & 75\% & 56\% \\  & ResR & [m\({}^{2}\)K/W] & 16.2 & 68\% & 85\% \\  & ResS & [m\({}^{2}\)K/W] & 8.1 & 22\% & 28\% \\  & WT-South & [-] & Triple glazing, low-e, air & 85\% & 95\% \\  & WT-East/West/North & [-] & Triple glazing, low-e, air & 75\% & 80\% \\  & RWT & [-] & Triple glazing, low-e, Argon & 100\% & 100\% \\  & GWW & [m] & 7.2 & 57\% & 84\% \\  & FWW & [m] & 2.2 & 15\% & 20\% \\  & RWH & [m] & 0 & 74\% & 98\% \\ \hline \multirow{6}{*}{System parameters} & N\_coll & [-] & 14 & 63\% & 83\% \\  & Slope\_coll & [”] & 18 & 59\% & 77\% \\  & Type\_coll & [-] & Flat plate & 90\% & 100\% \\  & St\_ratio & [[L/m\({}^{2}\)] & 50 & 52\% & 47\% \\  & Type\_PV & [-] & Polycrystalline & 85\% & 100\% \\  & Slope\_PV & [”] & 30 & 63\% & 84\% \\  & N\_PV & [-] & 18 & 80\% & 93\% \\  & Type\_heat & [-] & Geo HP & 94\% & 100\% \\ \hline \multirow{6}{*}{Results} & Global cost & [kWhep/m\({}^{2}\)] & & 1118.53 & \\  & Solar coverage—heating & [kWh/m\({}^{2}\)] & & 37.25\% & \\ \cline{1-1}  & Self-consumption— electricity & [kWh/m\({}^{2}\)] & & 2766.14 & \\ \cline{1-1}  & EP\({}_{\text{nen}}\) & [kWh/m\({}^{2}\)] & & 55.97 & \\ \cline{1-1}  & EP\({}_{\text{tot}}\) & m\({}^{3}\) & & 74.04 & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Results of the integrated optimization energy objective. Figure 15: Active parameters in the optimum neighborhood: integrated optimization and financial objective. variables with their variability range. Indeed, concerning the opaque building envelope, optimal values of the insulation layer's thermal resistance were close the maximum allowed. For the windows, regardless of their orientation, low-emissive triple glazing with air was selected. The optimal thickness of the external wall was 0.50 m, thus increasing the positive effect of thermal inertia. Regarding the system, the geothermal reversible heat pump was selected as the heat generator because of its higher efficiency compared to the biomass boiler. Predictably, renewable energy sources were exploited to the maximum possible extent. The optimal solution, in fact, consisted of 14 solar thermal collectors and 18 photovoltaic panels. The ideal number of (solar) thermal collectors found by the algorithm allowed exploiting, to the greatest extent, solar energy for DHW production during the summer season. Regarding the PV system, polycrystalline silicon panels were chosen, as they were characterized by the highest efficiency in relation to peak power. Finally, concerning the systems, a different slope for solar thermal collectors and PV panels was selected by the algorithm. Indeed, the ideal slope in the first case was 18\({}^{\circ}\), while in the second case it was 30\({}^{\circ}\). This configuration led to an overall primary energy consumption of 74.04 kWhPEtot/m\({}^{2}\). This value lowered to 55.97 kWhPEnren/m\({}^{2}\) contribution of renewable energy sources was not considered. Finally, the correspondent global cost was 1118.53 \(\upxi\)/m\({}^{2}\). These results show that, with the defined set of design parameters, it was not possible to reach the net zero energy target. With respect to the cost-optimal energy performance, the energy optimum reduced primary energy consumptions by 23%.