Impact of weather regimes on wind power variability in western Europe

• Published in: Applied energy Vol. 264; p. 114731
• Main Authors: Garrido-Perez, Jose M., Ordóñez, Carlos, Barriopedro, David, García-Herrera, Ricardo, Paredes, Daniel
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.04.2020
• Subjects: Atmospheric circulation; Weather regimes; Wind energy; Wind power; Wind resources; Atmospheric circulation; Wind energy; Wind power; Weather regimes; Wind resources
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2020.114731

•New set of weather regimes that improve the capability to reproduce wind power.•Monthly correlations of wind power with weather regime occurrence up to ~0.8.•High reproducibility of wind farms’ capacity factors in Iberia and the United Kingdom.•Weather regimes explain day-to-day evolution of anomalous regional wind episodes. We have assessed the dependency of wind power resources in Western Europe on the atmospheric circulation as represented by a new set of 8 tailored weather regimes (WRs). For this purpose, we have derived wind capacity factors (CFs) from a meteorological reanalysis dataset and from high-resolution data simulated by the Weather Research and Forecasting (WRF) model. We first show that WRs capture effectively year-round onshore wind power production variability across Europe, especially over northwestern/central Europe and Iberia. Since the influence of the large-scale circulation on wind energy production is regionally dependent, we have then examined the high-resolution CF data interpolated to the location of more than 100 wind farms in two regions with different orography and climatological features, the United Kingdom and the Iberian Peninsula. The use of the monthly frequencies of occurrence of WRs as predictors in a multi-linear regression model allows explaining up to two thirds of the month-to-month CF variability for most seasons and sub-regions. These results outperform those previously reported based on Euro-Atlantic modes of atmospheric circulation, indicating that the use of WRs customized to the region of study is preferred to reproduce the evolution of wind energy resources. Finally, we have applied these WRs to understand the day-to-day evolution of specific episodes with anomalous regional wind power production. In particular, the wind energy deficit of summer 2018 in the United Kingdom and the surplus of March 2018 in Iberia stemmed from the combination of WRs associated with low and high CFs, respectively. These findings are relevant for the forecast of wind energy resources as the large-scale features of the atmospheric circulation captured by WRs can be modelled with considerably less uncertainty than wind speeds at wind farm sites.