## 3 Results
### String Fault Behavior  
In this section, the situation resulting from a fault in a DC fuse is examined. Each inverter has four strings which are connected to the inverter with fuses. From 4 April 2015 to 9 April 2015, the values of nRMSE are observed to exceed 30% during the period when the fault occurred, as seen in Table 5. The maximum value was observed on 9 April, 2015, when the inverter operation was shut down in order to replace the fuse. The respective values of the MAPE, MAE and MBE are all at significantly higher levels than in normal operation. This effect is also observed in Figure 4, where the simulated and measured values are compared. Furthermore, the values of PR, which is an important performance metric, are observed to be significantly lower in Table 5 for  
A closer observation of the simulated and actual operation in Figure 4 allows to visualize how the onset of faulty operation occurs, after an initial period of normal operation. The deviation between simulated and real power is clear even for a cloudy day, 5 April 2014. Comparing statistical metrics for the period of normal operation with those for the faulty operation period, the remarkable deviation between simulated and actual performance observed for the days where this type of error occurs corresponds to error levels exceeding 30%, both with regard to the nRMSE and MAPE. This is also depicted in the daily energy production and PR of the deviation between simulated and actual values, presented in Table 6.  
This type of fault is inspected in PVS3 with the aid of ANN network n3 that is trained with ambient temperature and irradiance as inputs. Values of n RMSE > 30% may be safely correlated with the same error in one string of the inverter as it is observed from ANN n1, which differentiates in the type of temperature received as input. This is depicted in Table 7 and Figure 4, and is also validated from PR decrease (Table 8).  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **kWh** & **PR** \\ \hline
1/4/15 & 78.48 & 0.88 \\
2/4/15 & 83.71 & 0.89 \\
3/4/15 & 78.35 & 0.91 \\
4/4/15 & 70.74 & 0.84 \\
5/4/15 & 16.11 & 0.71 \\
6/4/15 & 42.48 & 0.67 \\
7/4/15 & 43.78 & 0.69 \\
8/4/15 & 38.52 & 0.72 \\
9/4/15 & 61.08 & 0.78 \\
10/4/15 & 86.93 & 0.92 \\
11/4/15 & 85.46 & 0.89 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Energy production and PR for the period 1 April 2015–11 April 20215.  
Figure 4: Actual output of inverter 8 (PVS1), compared with the ANN simulated output from n1, for the period 1 April 2015 to 11 April 2015 (abnormal operation due to faulty DC fuse observed from 5.4 to 9.4).  
Figure 5 shows a comparison between the simulated and actual behavior of AC power output during a normal operation period that is followed by faulty operation. A statistically significant deviation between simulated and actual power output is observed from 13 August 2014 to 15 August 2014. Significant deviations are also observed on 16 April 2014, when an inverter shut-down became necessary in order to repair the fault. Comparing the statistical metrics of normal operation with faulty operation, we observe the same remarkable deviation of over 30% in nRMSE and MAPE, as in case of PVS1. This is also depicted in the daily energy production and PR values of Table 7.  
The above observations point to the conclusion that a faulty operation in a string is confirmed when n1 and n3 demonstrate the same type of behavior, despite the fact that these networks have different temperature inputs. The values of nRMSE fluctuated over 30% when the error occurred all day round. The same behavior was observed with the respective values of MAPE.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & **N** & **RMSE** & **MBE** & **MAPE** & **MAE** & **nRMSE** \\ \hline
05/08/14 & 47 & 16.93 & 75.32 & 1.25 & 90.94 & 1.68 \\
06/08/14 & 33 & 33.29 & 74.45 & 1.14 & 132.