## 5 Simulation Results  
The solar PV power generation was simulated using an hourly irradiance profile for Lebanon at a latitude of 33.8\({}^{\circ}\) N and a longitude of 35.5\({}^{\circ}\) E. The solar constant is around 1460 W/m\({}^{2}\), and the average annual solar radiation is 5.49 kWh/m\({}^{2}\)/day. The monthly solar radiation profile is shown in Figure 6. The characteristics of the solar PV panels used are provided in Table 2.  
Figure 5: Simulation algorithm flow chart. The primary limitation of the NEM billing scheme is the issue of unremunerated excess energy, which refers to the amount of energy that is injected back into the grid and exceeds the prosumer's annual energy demand. In NEM programs, any excess energy exported to the grid is credited at the same rate as retail electricity. These credits can accumulate over time if the customer consistently exports more energy than they consume. They can then be used to offset future electricity purchases, effectively rolling over the excess energy to the next billing period. However, at the end of the year, an annual settlement process takes place where all bills are reset, potentially resulting in a loss of any rolled over excess energy. This process may also involve reconciling any remaining excess energy credits, with the utility potentially compensating the customer at a predetermined rate for any unused credits. In our case, it is considered that at the end of the year, any rolled-over excess energy will be reset. Table 3 displays the amount of annual excess energy wasted by the three prosumer profiles under scenarios 1 and 2 using a NEM billing scheme. Under both scenarios, the annual energy bill will be null for all prosumers, because both solar PV systems (12.8 kWp and 10 kWp) can generate enough energy to fully compensate for the prosumer's annual energy consumption. \begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{2}{c}{**Panel Characteristics**} \\ \hline Maximum Power Pmax (W) & 330 Wp \\ \hline Maximum Power Voltage Vmpp (V) & 37.8 \\ \hline Maximum Power Current Impp (A) & 8.74 \\ \hline Open-Circuit Voltage Voc (V) & 46.9 \\ \hline Short-Circuit Current Isc (A) & 9.14 \\ \hline Module Efficiency (\%) & 17.01 \\ \hline Module Dimensions (mm) & 1956 \(\times\) 992 \(\times\) 40 \\ \hline Module Weight (kg) & 22.5 \\ \hline Cell Type & Polycrystalline 157 \(\times\) 157 mm \\ \hline Number of Cells & 72 (6 \(\times\) 12) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Solar PV panel characteristics. Figure 6: Monthly solar radiation profile. At another level, the issue with FiT billing schemes is the monopolized process of setting a tariff for grid-injected energy. Often, existing utilities are responsible for buying the energy and managing the grid. If there is only one utility company in an area (a monopoly), they have some control over setting the FiT rate. Critics argue that a monopoly utility might reduce the FiT rate to minimize costs, hindering renewable energy growth. This issue is avoided with P2P energy trading models since direct negotiations between the prosumer and the buyer set the rates. The annual gains of the three prosumers, under scenarios 1 and 2, are presented, respectively, in Figures 7 and 8. The gains under the NEM billing mechanism are the lowest for all prosumers due to the unremunerated lost excess energy, while FiT and P2P mechanisms present comparable gains. P2P has higher total savings because its average negotiated rate, even after the deduction of the wheeling charge, is higher than the FiT tariff. Additionally, simulation results show that the gap between P2P energy trading and the other two billing mechanisms is greater in the case of highly energy-efficient prosumers or occasionally occupied households.