## 3 Results and Discussion
### Performance Parameters
A PR higher than 1 is uncommon and can only be accomplished under particularly favorable weather conditions, such as high solar insolation values when cell temperatures are much below the temperatures at STC. In this case, deviations of PR values from the usual ones occurred in the winter months (December, January, and February) due to higher insolation, mild temperatures, and less precipitation and snow, which is unusual for that time of year. On the other hand, plotting the regression line of PR during the 10 years shows a very slight linear decrease over the years, with a regression coefficient of \(1-0.0000583\,|\), representing the slope in a regression model. So, in this case, the PR, that is, the rate of effective produced energy with the energy the PV system would generate if it continually worked on its efficiency at STC, did not change statistically significantly over the 10 years of its operation. In other words, the losses in the PV system, which include soiling and aging of the system components, during its 10-year operation are insignificant (almost negligible) for the observed period. Thus, as PR is a quantitative characteristic of all PV system losses, including soiling and aging of the system's components, the results show that the behavior of the given PV system over 10 years of its operation does not change significantly; that is, the PV system degradation over 10 years is minimal. Based on the specific yield factor, the capacity factor (CF) can be calculated, which presents the ratio of the yearly specific yield factor and yearly theoretical PV production capability. In this case, the yearly average of CF over the 10-year period range from 12.88% (2014) to 14.02% (2019). On the other hand, the average value of total energy losses in the given PV system could be calculated as the difference between \(Y_{r}\) and \(Y_{f}\), and for the 10-year measurement period, it is 22.3%. Although solar radiation, to a great extent, affects the PV arrays' electricity output, ambient temperature also affects electricity production and, therefore, other PV system performance parameters, such as PR. Ambient temperature can lead to heating of the  
Figure 6: Graphics of the change of yearly average values of Performance Ratio (PR) for a 10-year period. solar module surface, resulting in reduced PV system efficiency. Generally, an increase in temperature of 1 \({}^{\circ}\)C causes a decrease in relative PV efficiency between 0.14% and 0.47%, depending on the PV installation type [40]. Recently studies have shown that there are different PV cooling methods that noticeably increase the PV system efficiency but passive ventilation of the PV system, i.e., PV cooling under natural air convection, is the simplest and most inexpensive method for application [40; 41]. With the natural air convection appearing behind the PV modules, the temperature of solar cells can decrease by about 15-20 K, as reported in [42]. In this case, as the ventilation of a given PV system unfolds naturally (passive air cooling), so solar modules' cooling is done only by the wind influence. The ratio between the average monthly values of PV system energy efficiency (\(\eta_{\rm syst}\)) and the wind speed (\(v\)) for 10-year measurements is given in Figure 7.  
Based on simple linear regression, the plotted regression line for each month during the 10 years (Figure 7) allows for the identification of the slope so that, in this case, the regression coefficient (slope in the regression model) amounts to 0.214411 and responds to the average change of the expected value of the dependent variable \(\eta_{syst}\) for the unit change of the independent variable \(v\). Figure 7 also shows that, with increasing wind speed, PV system efficiency linearly increases. However, this type of PV cooling does not significantly increase the system efficiency.