The storage and balancing needs of a simplified European power system, which is based on wind and solar power generation only, are derived from an extensive weather-driven modeling of hourly power mismatches between generation and load. The storage energy capacity, the annual balancing energy and the balancing power are found to depend significantly on the mixing ratio between wind and solar power generation. They decrease strongly with the overall excess generation. At 50 % excess generation the required long-term storage energy capacity and annual balancing energy amount to 1 % of the annual consumption. The required balancing power turns out to be 25 % of the average hourly load. These numbers are in agreement with current hydro storage lakes in Scandinavia and the Alps, as well as with potential hydrogen storage in mostly North-German salt caverns.

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To ensure reliable energy supply from power systems with high shares of variable renewable energy (VRE) sources like solar photovoltaics (PV) and wind, it is essential to include balancing options like storage and backup from dispatchable resources. In this work, we have quantified these balancing requirements for Europe and analyzed how they are influenced by different PV module configurations. We found that a favorable choice of module configuration with respect to balancing reduction is very sensitive to the shares of PV and wind. For high solar shares, highly inclined modules with a less pronounced annual course are favorable, if a storage with a capacity to cover at least 6 h of average hourly load (6 h storage) is available to compensate for the day-night cycle of PV. In a wind-dominated scenario, however, lowly inclined East/West facing modules are most suitable to reduce balancing needs. In absence of storage, a combination of highly inclined East and West facing modules reduces balancing needs as long as the solar share is high enough to distinguish between the contributions from different module configurations, although the price of such configurations in terms of additionally required installed PV capacity can be quite large

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The increasing share of offshore wind energy traded at the spot market requires short term wind direction forecasts to determine wake losses and increased power fluctuations due to multiple wakes in certain wind directions. The information on potential power fluctuations can be used to issue early warnings to grid operators. The current work focuses on analyzing wind speed and power fluctuation time series for a German offshore wind farm. By associating these fluctuations with wind directions, it is observed that the turbines in double or multiple wake situations yield higher fluctuations in wind speed and power compared to the turbines in free flow. The wind direction forecasts of the European Center for Medium-Range Weather Forecast model are compared with Supervisory Control and Data Acquisition (SCADA) data observations of the turbine yaw. The cumulative probability distribution of the difference in forecasted and observed wind directions shows that for a tolerance of +/−10 ∘ , 71% of the observations are correctly forecasted for a lead time of 1 day, which drops to 54% for a lead time of 3 days. The circular continuous rank probability score of the observed wind directions doubles over the lead time of 72 h.