Climate variability on Fit for 55 European power systems

shaping the pattern of energy-relevant variables across the continent (for an in-depth analysis, we refer the reader to [50–55]). In the patterns that can be associated with a positive state of the NAO—as the Atlantic Trough (AT), Zonal Regime (ZO) and Scandinavian trough (ScTr)– there is an increase of wind power in the north and a decrease in the south. Conversely, for the pattern Greenland Blocking (GL), that can be associated with a negative state of NAO, Italy and Iberia show an increase in wind power of between 5% and 15%, with a decrease in the rest of the continent. We further observe an anti-correlation between variable renewable energy generation and regions associated with the various weather patterns. For example, in the region CWE (428 GW of installed wind and solar), the daily generation of wind and solar is 54 GWh more than the average during the AT pattern, and -37 GWh during the EuBL pattern (Fig 7). The differ- ence between the two patterns, chosen as the most distant in terms of renewable generation, is less marked in the other regions. Moreover, as also mentioned in [23], the figure highlights that the EuBL/AT patterns do not seem to have any impact on wind and solar generation in the SEE region. This is in contrast to the CWE region. In general, as shown in Fig 6, wind gen- eration in SEE seems to exhibit behaviour that does not correlate with the other regions. For hydropower inflow, the regions tend to show the same sign of change in general, with the notable exception of the pattern EuBL, where CEE, SEE and Iberia shows an increase (par-

ticularly large in Iberia >35%) and Northern and UK & Ireland a decrease. A reversed pattern, albeit with a weaker signal, can be observed for ZO. Analysis of the association between large-scale weather regimes and daily power systems operations shows how multiple patterns can affect the entire continent. Our results regarding the wind and solar power generation in each analysed pattern are consistent with the results Fig 6. Percentage change from the daily average across all the climatic years of six energy variables for each pattern considered. Only the values with the p-value of a T-Test smaller than 0.001 are shown. For each pattern we specify its average number of days per year. https://doi.org/10.1371/journal.pone.0289705.g006 PLOS ONE Climate variability on Fit for 55 European power systems PLOS ONE | https://doi.org/10.1371/journal.pone.0289705 December 20, 2023 10 / 16