Seasonal prediction and predictability of wind power potential over North America

Abstract

The capacity factor (CF) is a critical indicator for quantifying wind turbine efficiency, and therefore has been widely used to measure the impact of interannual wind variability on wind energy production. Using the seasonal prediction products from GFDL’s Seamless System for Predicton and Earth System (SPEAR), we assess the seasonal prediction skill of CF over North America. SPEAR shows high skill in predicting winter CF over the western United States. The seasonal wind speed and CF variations associated with large-scale circulation anomalies are examined to understand the predictability mechanism of CF. The source of the skillful seasonal CF prediction can be attributed to year-to-year variations of ENSO and North Pacific Oscillation, which produce large-scale anomalous wind patterns over North America. The skillful seasonal prediction of CF is potentially beneficial to various stakeholders in the energy sector, including wind energy production, trading, and transmission.