## 3 Results
### Use of the Developed Application in the Analysis of Some Parameters of Two PV Plants
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Table Name** & **Plant 1** & **Plant 2** \\ \hline Total power (\(k\)W) & 217.6 & 1843.2 \\ Number of inverters & 2 & 17 \\ Inverter model & SMA SC-100 & SMA SC-100 \\ Number of modules per inverter & 640 & 640 \\ Module power connected to each & 108.8 & 105.6 and 108.8 \\ inverter (\(k\)W) & 1280 & 10,880 \\ Total number of modules & 1280 & 10,880 \\ Module model & BP-3170 & BP-3165 and BP-3170 \\ Module nominal power (W) & 170 & 165 and 170 \\ Single-phase or Three-phase & Three-phase & Three-phase \\ Rooftop or ground & Rooftop & Ground \\ Geographical location & Pozoblanco & Pozoblanco \\ Rural or city area & Rural, industrial area & Rural \\ Latitude & 38\({}^{\circ}\)21\({}^{\prime}\)33\({}^{\prime\prime}\) N & 38\({}^{\circ}\)20\({}^{\prime}\)8\({}^{\prime\prime}\) N \\ Longitude & 4\({}^{\circ}\)50\({}^{\prime}\)40\({}^{\prime\prime}\) O & 4\({}^{\circ}\)49\({}^{\prime}\)41\({}^{\prime\prime}\) O \\ Tilt & Adapted to the ground & 9\({}^{\circ}\) \\ Orientation & South & 10\({}^{\circ}\) deviation respect South \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Main technical characteristics of PV plants analysed. system were assigned a null value. The graphs obtained for the rest of the inverters on the two plants show very similar behaviour to that of the inverter on the same floor shown in Figure 12.  
Although these graphs show the general behaviour of the \(P_{ac}\) production of each inverter, it is not always easy to visualise in them small deviations in the production of any inverter, which could alert us to problems in any of the elements of the plant, especially if the behaviour of numerous inverters must be supervised, as is the case of plant 2. Given that the inverters are close together and receive practically similar irradiance values, if their production is compared with each other, and it is not the same, this would be an indication of a failure or problem in one of the elements. To do this, a simple Python script was developed that asks the user for the date of the day to be analysed, and a graphical representation of a correlation matrix will be available, which, after correlating the production value of each inverter on the chosen day with that of the rest of the inverters in the plant, shows the value of the Pearson correlation index of these correlations. This coefficient measures the linear dependence of the production of each inverter with all the rest. The closer the value is to 1, the better the relationship between the output of pairs of inverters. If the value were 0, it would mean that there is no relationship between the output of any two inverters. The diagonal in these matrices appears by default with the value unity since they correspond to the comparison of the production of each inverter  
Figure 12: Instantaneous \(P_{ac}\) values recorded at the output of inverters 1 of plant 1 (**a**) and 10 of plant 2 (**b**), in the period from 1 November 2021 to 4 July 2022.  
with itself. This type of graphical representation makes it easy to visually detect possible fault situations or small deviations that could lead to faults in the future. As an example of these types of graphs, Figure 13 shows those obtained for two different days for inverters 1 and 2 of plant 1. On one of these days, 15 February 2021 (a), it can be seen that the correlation index of the production of the two inverters has the value of 1, which shows that the two inverters are producing power at the same rate. This is not the case on 26 January 2021 (b), where the value of the correlation coefficient is less than 1 (0.53), which indicates that one of the inverters did not produce the same amount as the other, indicating the presence of a fault in one of them. The colour variation in the graph also warns of this possible deviation. Figure 13: Graphical representation of the correlation index matrix between \(P_{ac}\) values for inverters 1 and 2 of plant 1 on 15 February 2021 (**a**) and 26 January 2021 (**b**).