# Evaluating the Effect of Financing Costs on PV Grid Parity by Applying a Probabilistic Methodology
## 3 Results
### 500 kW Case Study
#### 3.3.2 500 kW Case Study Sensibility Analysis  
For the 500 kW case study a sensibility analysis has been performed considering a range of annual yields from 1100 to 1500 kWh/kWp with a step of 100 kWh/kWp in the range. Using the methodology applied in Section 3.1.1, it is possible to calculate the LCOE considering the method described previously, fixing the regulated tariff at 17.4 c/kWh including taxes and with a fixed interest rate of 10%. Table 14 shows the most relevant results for the five cases. Case 1 corresponds to 1100 kWh/kWp and Case 5 corresponds to 1500 kWh/kWp. The positions where the LCOE is lower than the retail cost of energy have been highlighted. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & & & & \multicolumn{3}{c}{**LCOE (\(\ell\)/kWh)**} \\ \cline{3-8}
**PV Module** & **System** & **Interest** & & & & \\
**Cost (\(\ell\)/Wp)** & **Cost (\(\ell\))** & **Rate (\%):** & **12** & **10** & **8** & **6** & **4** \\ \hline
1.0 & 1,022,450 & & 0.2149 & 0.1881 & **0.1625** & **0.1386** & **0.1166** \\
0.8 & 877,250 & & 0.1869 & **0.1638** & **0.1419** & **0.1214** & **0.1025** \\
0.6 & 732,050 & & **0.1588** & **0.1396** & **0.1213** & **0.1042** & **0.0884** \\
0.4 & 586,850 & & **0.1308** & **0.1154** & **0.1007** & **0.0870** & **0.0743** \\
0.2 & 441,650 & & **0.1027** & **0.0911** & **0.0801** & **0.0697** & **0.0602** \\ \hline \hline \end{tabular}
\end{table} 
Table 13: LCOE over a range of interest rates (50,000 W inverter, deterministic method). Figure 15: Analysis of the LCOE against the retail electricity cost at various interest rates (500,000 W inverter, deterministic method). \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & & & & \multicolumn{3}{c}{**LCOE (\(\ell\)/kWh)**} \\ \cline{3-8}
**PV Module Cost** & **System Cost** & **Annual Yield** & **Case 1** & **Case 2** & **Case 3** & **Case 4** & **Case 5** \\
**(\(\ell\)/Wp)** & **(\(\ell\))** & **(\(k\)Wh/kWp):** & **1100** & **1200** & **1300** & **1400** & **1500** \\ \hline
1.0 & 1,022,450 & & 0.188 & 0.174 & **0.162** & **0.151** & **0.143** \\
0.8 & 877,250 & & **0.164** & **0.152** & **0.141** & **0.132** & **0.125** \\
0.6 & 732,050 & & **0.140** & **0.129** & **0.121** & **0.113** & **0.107** \\
0.4 & 586,850 & & **0.115** & **0.107** & **0.100** & **0.094** & **0.089** \\
0.2 & 441,650 & & **0.118** & **0.110** & **0.103** & **0.097** & **0.091** \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Comparison of the LCOE based on the different annual yield for 500 kW. Table 11 considers five cases, but the cost at 0.4 \(\upxi\)/Wp is considered as the current scenario. For that reason, the PDF for the panel cost is log-normal with a mean of 0.4 (\(\upxi\)/Wp) and a standard deviation of 0.2 (\(\upxi\)/Wp). The panel cost floor is set at 0.2 (\(\upxi\)/Wp) so that 95% of the cases are represented in the PDF (Figure 16). Introducing all the variables in the probabilistic analysis with the Monte Carlo method delivers a wide range of results, giving the following representation (Figure 17), with the frequency of the LCOE above and below the retail electricity cost. Introducing the results of the iterations given by the Monte Carlo method for the business model, we obtain the IRR values. The IRR results for the 500 kW business case are shown graphically in Figure 18.  
A success rate parameter (%) is introduced by counting the number of iteration results below the retail cost of the electricity and dividing by the total number of iterations (10,000). Analysing the frequency of the results and the value itself, the success rate for each case can be calculated. In this case of a 500 kW installation, it has been concluded that the success rate would be 99.80%. This means that in 99.80% of the cases, grid parity is achieved as the LCOE is lower than the retail cost. As a business case, the mean of the IRR is positive (14.34%). Therefore, it can be concluded that even though the loan input in the model contributes negatively, the investment is successful.