# Indoor PV Modeling Based on the One-Diode Model
## 3 Results and Discussion
Tables 7 and 8 show the corresponding NRMSE results for both panels when illuminated by a 12 W CFL light source. At 1000 lux, the discussed methods fit the experimental values very closely, resulting in a low NRMSE. Between 900 and 600 lux, the performance of all three methods is similar. Nevertheless, as seen in Table 7, [PERSON]'s method results in a slightly higher NRMSE of 3.261% at 700 lux, which is more than twice that of the other methods. [PERSON]'s method is also associated with NRMSE values of 6.057%, 4.529%, and 8.385% at 500, 400, and 300 lux, respectively. This is because the translation of the maximum-power voltage is inaccurate, resulting in an increase in the NRMSE. Furthermore, at 200 lux, [PERSON]'s method also struggles to translate the open-circuit voltage due to the iterative thermal voltage. The results show that NRMSE values obtained with [PERSON]'s method reached as high as 14.123%. At 100 lux, the majority of the investigated methods struggle to maintain their accuracy. Due to the inaccuracy of the translation technique, [PERSON]'s method has the highest NRMSE of 28.086%. Since [PERSON]'s method involves the use of the parameter-scaling technique, the NRMSE rises to 6.070%. Nonetheless, the proposed model also had issues at 100 lux, with an NRMSE of 4.269%. It is important to note that potential nonlinearities can occur in the I-V curve, especially under varying indoor conditions. Nevertheless, the two existing techniques used in this study already have an inherent capability to handle potential nonlinearities in the I-V curve. Additionally, the iterative approach was applied in this study, which adjusts the \(R_{s}\) value to handle nonlinearities. In summary, the results show that the proposed model can provide average NRMSE values of 2.463% and 2.857%, which is a 13.029% to 13.091% improvement over the values achieved with [PERSON]'s method. Based on the discussion of the performance achieved with the other investigated methods, it can be concluded that [PERSON]'s method struggles to accurately translate open-circuit voltage due to the iterative thermal voltage and that the assumption of an infinite \(R_{p}\) value causes a lack of accuracy in maximum-power voltage translation at low illuminance levels. Moreover, [PERSON]'s parameter-scaling technique is unable to generate an accurate and consistent I-V curve. The proposed model is shown to provide the best accuracy among these works, with an average improvement of 15.75%. This is because the proposed model adopts the best features of both techniques, i.e., characteristic \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Illuminance Level (lux)**} & \multicolumn{3}{c}{**NRMSE (\%)**} \\ \cline{2-4}  & **[PERSON]** & **[PERSON]** & **Proposed** \\ \hline
1000 & 0.705 & 0.467 & 0.362 \\
900 & 1.165 & 1.191 & 0.889 \\
800 & 1.244 & 1.531 & 1.217 \\
700 & 1.494 & 3.261 & 1.433 \\
600 & 3.221 & 3.797 & 2.033 \\
500 & 2.467 & 6.057 & 2.424 \\
400 & 2.992 & 4.529 & 3.022 \\
300 & 4.022 & 8.385 & 3.879 \\
200 & 5.073 & 14.123 & 4.443 \\
100 & 5.960 & 28.086 & 4.927 \\ Average & 2.834 & 7.143 & 2.463 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: NRMSE of kx0b22\(-\)12x1 with a 12 W CFL. point translation followed by parameter extraction and an iterative adjustment of \(R_{s}\) to match the lower maximum-power point at low illuminance levels.