## 4 Sensitivity Analysis  
A sensitivity analysis was performed to observe the influence of the main cost parameters on the LCOE values. \(CI\) and \(OM\) costs varied from \(-30\%\) to \(+30\%\), considering a \(\pm 10\%\) variation. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model** & **LCOE** & **LCOE** & **PV Technology** & **Country** \\
**Year** & **[c/kWh]** & **Installed Power** & **PV Technology** & **Country** \\ \hline
[9] & 13 & 5.5 MW & organic absorber layers & Fiji \\
2021 & 19 & 5.5 MW & perovskite absorber layers & \\ \hline
[10] & 12 & 1 MW & & \\
2016 & 6.3 & 5 MW & & \\
2016 & 7.3 & 10 MW & not specified & India \\
2016 & 5.9 & 25 MW & & \\
6.1 & 151 MW & & & \\ \hline
[11] & 6.7–15 & around 100 MW & not mentioned & China \\
2024 & 6.7–13 & residential & & \\
2011 & 8.8–44 & commercial & not specified & North America \\
2011 & 5.5–40 & utility scale & & \\ \hline
[13] & 5.2–13 & variable & & South Australia \\
2025 & 4.9–7.9 & variable & not mentioned & Southern California \\ \hline  & 2.46–3.19 & & N-type & \\ Proposed—with & 2.39–3.21 & 7 kW & TOPCon & \\ incentives & 2.50–3.16 & 5 kW & Bifacial TOPCon & Romania \\  & 2.41–3.16 & 3 kW & PERC & \\  & 2.92–3.24 & & HJT & \\ \hline  & 6.18–7.40 & & N-type & \\ Proposed—without & 6.05–7.38 & 7 kW & TOPCon & \\ incentives & 6.17–7.33 & 5 kW & Bifacial TOPCon & Romania \\  & 6.32–7.52 & 3 kW & PERC & \\  & 6.51–7.94 & & HJT & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Summary of LCOE values. First, \(CI\) was varied. The \(LCOE_{1}\) values are presented in Figure 6. The 3 kW PV systems are not influenced by the variation of the \(CI\), because of the incentives received from the Romanian government, which cover all the initial costs. Even if \(CI\) increases by 30%, the subsidies are enough to sustain the acquisition of the PV system, maintaining \(LCOE_{1}\) values around 3.2 cC/kWh. Similar results are obtained for the 5 kW systems. TOPCon and PERC technologies' \(LCOE_{1}\) values are not influenced by any variation in the \(CI\) cost, keeping their approximately values of 3 cC/kWh. N-type and bifacial TOPCon \(LCOE_{1}\) values increase only when \(CI\) cost is varied by 30%. Meanwhile, HJT \(LCOE_{1}\) values are affected by the slight increase in \(CI\) cost, which means that the subsidies barely cover the initial investment of HJT systems. An increase in \(CI\) may generate additional costs for the owners which chose HJT modules for their PV system, the \(LCOE_{1}\) values reaching almost 3.5 cC/kWh at a +30% variation. For 7 kW systems, the variation in \(CI\) has a great impact on the \(LCOE_{1}\) values of the studied PV technologies. A decrease in \(CI\) cost lowers the \(LCOE_{1}\) for each PV technology, the incentives covering a larger percentage of the initial costs, even cover all the expenses as in the case of TOPCon and PERC technologies at any variation, where the \(LCOE_{1}\) values get as lower as 2.2 cC/kWh. Meanwhile, the increase in \(CI\) cost generates higher \(LCOE_{1}\) values for each PV technologies, making them less profitable for potential investors. The highest values are achieved by HJT technology, with 4.23 cC/kWh at a +30% variation. Without subsidies granted by the government, a variation in \(CI\) affects all the 15 PV systems studied, even if \(OM\) costs remain the same. As presented in Figure 7, a decrease in \(CI\) lowers \(LCOE_{2}\) values for all the PV technologies, regardless of their installed power, making the investment more profitable and attracting new investors. The lowest values are obtained for 7 kW systems, with an \(LCOE_{2}\) value of around 5 cC/kWh. Figure 6: Results obtained for \(LCOE_{1}\) based on change in \(CI\) cost. However, an increase in _CI_ cost increases also the _LCOE\({}_{2}\)_ values, making the potential investors rethink their investment strategies. All the _LCOE\({}_{2}\)_ values exceed 7 c\(\epsilon\)/kWh for the 7 kW systems and reach 9 c\(\epsilon\)/kWh for 3 kW systems. The _OM_ costs were also varied.