Seasonal prediction of renewable energy generation in Europe based on four teleconnection indices

Continental Complementarity of Renewable Energy Mixes

“…At a landscape point or at a regional scale, the potential for PV solar power shows a generally negative covariation with both wind power and hydropower; however, this behaviour is modi ed when the resource variability is assessed over a large region, i.e., Europe. In particular, the North Atlantic Oscillation induces an oscillating inverse behaviour of dry-cold and wet-warm weather conditions in the northern and southern parts of Europe (Lledó et al, 2022). Here, we found that the cross-covariance spectra of wind power versus solar power show a signi cant negative correlation in the annual period for the spatial distribution of power production (Fig.…”

“…Similarly, it has recently been argued that seasonal hydroclimatic predictions can increase the effectiveness of production management (Orlov et al, 2020). Recent ndings show that both wind and solar intensity exhibit reverse correlations with different teleconnection indices in northern and southern Europe, suggesting that their variances are signi cantly lower when aggregated on continental scales compared to their regional behaviour (Lledó et al, 2022). This nding suggests that virtual energy storage arises primarily from management over large regions, hence accounting for the autocovariation and the cross-covariations of the energy components inherent in the climatic system.…”

“…Climate uctuations re ected in atmospheric and oceanic teleconnections can cause signi cant variation in the access to renewable energies, from daily erratic behaviour to periodic patterns with durations of many years to decades (Engeland et al, 2017;Wei et al, 2020;Lledó et al, 2022). Both short-term intermittency and long-lasting low renewable energy availability can potentially cause "energy droughts" (Raynaud et al, 2018;Orlov et al, 2020;Gernaat et al, 2021), which may lead to electric supply failure with a great impact on society (Demski, 2018).…”

How do North American weather regimes drive wind energy at the sub-seasonal to seasonal timescales?

“…needed to translate atmospheric variables to energy properties 8 . Particularly, bridging methods allow forecasts of the state of the climate into another variable of interest over welldefined large areas, if a robust linkage between them is found in observational records.…”

“…Forecasting the wind power generation over time periods ranging from hours to several days ahead has had tremendous improvement 5 , while the skill of forecasts beyond 2 weeks remains poor. In recent years, there has been an increasing need for forecasting power generation at the subseasonal to seasonal (S2S, 2 weeks to one season) timescales to support the operation, management, and planning of the wind-energy system [6][7][8] . Knowledge of the fluctuations of power production at the S2S timescales can also help guide deployment pathways that balance power generation from wind and other renewables 6 .…”