The influence of weather regimes on European renewable energy production and demand

• Main Authors: van der Wiel, Karin, Bloomfield, Hannah, Lee, Robert W, Stoop, Laurens, Blackport, Russell, Screen, James, Selten, Frank M
• Other Authors: Sub Algorithmic Data Analysis, Algorithmic Data Analysis
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2019
• Subjects: energy meteorology; energy transition; renewable energy; weather regimes; wind energy; solar energy; energy demand; North Atlantic; North Atlantic oscillation
• Online Access: https://dspace.library.uu.nl/handle/1874/385454

The growing share of variable renewable energy increases the meteorological sensitivity of power systems. This study investigates if large-scale weather regimes capture the influence of meteorological variability on the European energy sector. For each weather regime, the associated changes to wintertime—mean and extreme—wind and solar power production, temperature-driven energy demand and energy shortfall (residual load) are explored. Days with a blocked circulation pattern, i.e. the 'Scandinavian Blocking' and 'North Atlantic Oscillation negative' regimes, on average have lower than normal renewable power production, higher than normal energy demand and therefore, higher than normal energy shortfall. These average effects hide large variability of energy parameters within each weather regime. Though the risk of extreme high energy shortfall events increases in the two blocked regimes (by a factor of 1.5 and 2.0, respectively), it is shown that such events occur in all regimes. Extreme high energy shortfall events are the result of rare circulation types and smaller-scale features, rather than extreme magnitudes of common large-scale circulation types. In fact, these events resemble each other more strongly than their respective weather regime mean pattern. For (sub-)seasonal forecasting applications weather regimes may be of use for the energy sector. At shorter lead times or for more detailed system analyses, their ineffectiveness at characterising extreme events limits their potential.