the long-term AEP estimate and adding additional years does not provide a significant reduction in the uncertainty connected with the long-term estimate. As already mentioned in Section 2, these results are obtained for wind plants in mostly simple terrain and with a moderate-to-strong correlation between reanalysis wind resource and wind energy production and, therefore, with an overall low operational AEP uncertainty. We acknowledge that the inclusion of wind plants with a weaker correlation with the reanalysis products would modify the relative contribution of the various uncertainty components (e.g., the importance of the regression uncertainty would increase).

Correlation Between Operational-Based AEP Uncertainty Components
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To be able to assess the validity of the uncorrelated assumption when combining different uncertainty components, we assess potential correlations between uncertainty components by analysing the Pearson’s correlation coefficients $R_{ij}$ (needed in Equation \[unc\_corr\] to calculate $\sigma_{\text{tot,corr}}$) from each pair of AEP uncertainty components across the 472 wind plants, and we summarize the results in the correlation matrix in Figure \[unc\_corr\_heatmap\].

![image](f06){width="12cm"}

To assess which of the obtained correlations have statistical significance, we calculate the $p-$value [@westfall1993resampling] associated with the ten correlation coefficients. The test reveals that for three pairs of uncertainty components, the probability of finding 