## 2 Materials and Methods
### Performance Loss Rate Evaluation Using Mixed-Effects Linear Models
\begin{table}
\begin{tabular}{c l l l l l l} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Covariates**} & \multicolumn{1}{c}{**Estimation**} & \multirow{2}{*}{**SE**} & \multirow{2}{*}{_p_**-Value**} & \multicolumn{2}{c}{**95\% CI**} \\  & & **APR (month)** & & & & & \\ \hline Null & Time & \(-3.910\times 10^{-4}\) & \(1.673\times 10^{-5}\) & \(<\)0.001 & \(-4.230\times 10^{-4}\) & \(-3.580\times 10^{-4}\) \\ \hline \multirow{3}{*}{Typology} & Time & \(-2.370\times 10^{-4}\) & \(6.257\times 10^{-5}\) & \(<\)0.001 & \(-3.600\times 10^{-4}\) & \(-1.150\times 10^{-4}\) \\  & Manufacturer & \(-5.118\times 10^{-5}\) & \(4.811\times 10^{-5}\) & \(0.287\) & \(-1.450\times 10^{-4}\) & \(4.312\times 10^{-5}\) \\  & Technology & \(1.271\times 10^{-5}\) & \(4.204\times 10^{-5}\) & \(0.762\) & \(-6.968\times 10^{-5}\) & \(9.511\times 10^{-5}\) \\  & NominalP & \(-8.977\times 10^{-6}\) & \(3.289\times 10^{-6}\) & \(0.006\) & \(-1.542\times 10^{-5}\) & \(-2.529\times 10^{-6}\) \\ \hline \multirow{3}{*}{Location} & Time & \(-3.960\times 10^{-4}\) & \(5.130\times 10^{-5}\) & \(<\)0.001 & \(-4.970\times 10^{-5}\) & \(-2.960\times 10^{-4}\) \\  & Edge & \(1.320\times 10^{-4}\) & \(5.062\times 10^{-5}\) & \(0.009\) & \(3.292\times 10^{-5}\) & \(2.310\times 10^{-4}\) \\ \cline{1-1}  & LengthSt & \(-1.177\times 10^{-5}\) & \(3.755\times 10^{-6}\) & \(0.002\) & \(-1.913\times 10^{-5}\) & \(-4.412\times 10^{-6}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: \(\Delta\)_PR_ estimation for the three mixed models: null model without covariates; typology model with covariates _Manufacturer_, _Technology_, and _NominalP_; and the location model with covariates _Edge_ and _LengthSt_. SE: standard error; 95% CI: 95% confidence interval. Figure 6: Variation of the PR for PV production units made with modules of 155 W to 175 W per elapsed month. Own elaboration. implemented with the covariates: _Edge_ (to distinguish between PV production units that were placed at the easternmost border of the facility from those who were not in this position) and _LengthSt_ (to evaluate the impact of having different number of PV production units per street). Thus, considering the _Edge_ covariate, it was found that the monthly \(\Delta\)_PR_% _of_ a PV production unit located at the easternmost edge (or border) was 0.0132% higher than those not located at such position (or no border) (see Table 6). Moreover, by considering this result on a yearly period, this difference becomes 0.1584% (see Figure 7). Again, in economic terms, this means that, by the year 2019, a PV production unit located at the easternmost border earned, on average, EUR 8.11/kW less than one not located at such a position. Finally, taking into account the _LengthSt_ covariate, the results indicate that the number of PV production units per street also influences their \(\Delta\)_PR_%. In fact, \(\Delta\)_PR_% increases, on average, by 0.00117% per month for each PV unit that increases the length of the street (see Table 6 and Figure 8). As before, this is an effect that also adds up; thus, for instance, a street that has 10 PV production units was, on average 0.1264%/year above one who has just one PV unit. In economic terms, this means that, by 2019, having a street with 10 PV production units is supposed to earn, on average, EUR 6.41/kW less than having one made with only a single PV unit. The last two results reflect the effect of exposure to the prevailing winds, which are the trade winds that blow from the northeast most of the year in this area. On the one hand, those winds help to transport particles of dust and ambient humidity, which become fixed mainly to those PV production units who are more exposed (which are the ones located by  
Figure 8: Variation of the PR for PV production units in streets that have 1 to 15 units per elapsed month. Own elaboration. Figure 7: Variation of the PR for a PV production unit located or not placed at the edge per elapsed month. Own elaboration. the easternmost border of the installation), contributing to their soiling.