Understanding and Reducing Barriers to Wind Energy Expansion in California

Accurately characterizing site-level wind energy variability is essential during wind project development. Understanding the features and probability of low-wind years is of interest to developers and financers. Numerous and varied wind observations makes these characterizations challenging, thus techniques to improve these characterizations are valuable. To improve resource characterization, this research links site-level, hub-height, wind resource variability to regional wind variability of meteorological patterns (for either the central or southern California region) to a-scale greater than 600 miles. The approach involves statistical clustering of high-resolution modeled wind data for California from 1980 to 2015. Application of these methods reveal unique meteorological patterns driving low and high wind years at five wind project sites. Correlations between climate modes (recurring large-scale climate patterns such as El Niño/La Niña) and the frequency of different regional wind patterns, a linkage valuable for wind resource characterization and forecasting, are identified. This approach can be applied across locations and may benefit many aspects of wind energy resource evaluation and forecasting. Researchers also focused on climate change impacts on California wind resources. First, the research team examined the 36-year historical high-resolution modeling for temporal trends, illuminating already-occurring wind regime changes that are consistent with global warming: anomalously hot summer days increased at half a day per year, and stagnant conditions increased at one-third of a day per year. Second, the Variable-Resolution Community Earth System Model was used to investigate climate change impacts on wind resources between a 1980-2000 period and a midcentury 2030-2050 period. These projections suggest that wind power generation capacity throughout California is expected to increase during the summer and decrease during fall and winter, based on significant changes at several wind farm sites. Large-scale seasonal patterns from these model simulations were investigated to understand the synoptic-scale impact on localized wind speed change.