## 4 Results and Discussion
### Comparison of PLR Values Using STL and YoY  
While the methodology of calculating PR is widely accepted and standardized, the degradation of PV systems is estimated using different approaches. For that reason, in this section, we compare the PLR values presented in Section 4.2 with the ones retrieved using the YoY approach. For the YoY approach, the PLR calculation is mainly focused on using sensor-based data, but additional analysis is also performed using a clear sky model.  
As shown in Figure 10a, the PLR calculation based on monitoring data showed that p-Si modules degraded the least while the highest rate was observed for the a-Si modules. On average, p-Si modules degrade at \(-0.93\%\)/year, followed by mono-Si at \(-1.01\%\)/year, HIT at \(-1.07\%\)/year, CIGS at \(-1.2\%\)/year, CdTe at \(-1.38\%\)/year, and a-Si at \(-1.63\%\)/year. If we apply the clear sky model for the calculation, the lowest PLR is observed for the HIT modules with \(-0.12\%\)/year, while the a-Si system still experiences the highest PLR at \(-1.22\%\)/year. In between, CIGS degrades at \(-0.17\%\)/year, mono-Si at \(-0.28\%\)/year, p-Si at \(-0.53\%\)/year, and CdTe at \(-0.82\%\)/year.  
When the PLR values were grouped by climate, as shown in Figure 10b. while using sensor data, the lowest PLR was observed in the Cfb climate of Bolzano at \(-0.8\%\)/year, followed by Bwh in Alice Springs at \(-1.11\%\)/year. The largest PLR was observed in the climate of Af in Indonesia at \(-1.6\%\)/year. This confirms the previous study that higher PLR values occur in hotter climates compared to more moderate climates [(8)]. The annual average T\({}_{\text{amb}}\) in Bolzano, Alice Springs, and Indonesia during their corresponding reporting periods were, respectively, \(13\), \(26\), and \(31\)\({}^{\circ}\)C. Moreover, calculations using the clear sky model showed different results, where the lowest PLR was in the BWh climate at \(-0.4\%\)/year, followed by climate Af at \(-1.29\%\)/year, and the highest rate was in the climate of Cfb at \(-1.41\%\)/year. It has to be kept in mind, however, that clear sky modeling of irradiance data will inevitably result in higher uncertainties. It is usually used to cross-compare the quality of measured irradiance and as an alternative if no or corrupted irradiance measurements are available.  
Appendix A, Table A1 shows a complete performance matrix of the PV systems. The PR and PR\({}_{\text{ann}}\) values of all systems fall between \(76\%\) and \(88\%\), while the values of PR\({}_{\text{stc}}\) are slightly higher. According to [(56)], the typical PR of present PV systems ranges from \(80\%\) to \(90\%\). For most of the PV systems, the relative values of PLR using STL are smaller compared to the sensor-based PLR values using YoY, with a significant difference ranging from \(-12\%\) to \(-20\%\) for mono-Si in Alice Springs and \(-13\%\) to \(-60\%\) for p-Si in the same location. The differences in degradation values retrieved from STL and YoY were caused by the underlying differences in the methods themselves. The PLR using STL  
Figure 10: Performance loss rate of the PV systems using YoY. (**a**) Grouped by module technologies, (**b**) grouped by climate. Left: based on monitoring sensors, right: based on the clear sky model.  
was calculated based on a decomposition of the temperature corrected PR while the YoY-based PLR was calculated using the differences in daily instances of PR and renormalized energy using PVWatts.