Wind energy variability and links to regional and synoptic scale weather

Millstein, Dev; Solomon-Culp, Joshua; Wang, Meina; Ullrich, Paul; Collier, Craig

doi:10.1007/s00382-018-4421-y

Title: Wind energy variability and links to regional and synoptic scale weather

Journal Article · Fri Aug 31 00:00:00 EDT 2018 · Climate Dynamics

DOI:https://doi.org/10.1007/s00382-018-4421-y· OSTI ID:1543490

^[1]; Solomon-Culp, Joshua ^[1]; Wang, Meina ^[2];

^[2]; Collier, Craig ^[3]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Davis, CA (United States)
DNV GL, San Diego, CA (United States)

The accurate characterization of seasonal and inter-annual site-level wind energy variability is essential during wind project development. Understanding the features and probability of low-wind years is of particular interest to developers and financers. However, a dearth of long-term, hub-height wind observations makes these characterizations challenging, and thus techniques to improve these characterizations are of great value. To improve resource characterization, we explicitly link wind resource variability (at hub-height, and at specific sites) to regional and synoptic scale wind regimes. Our approach involves statistical clustering of high-resolution modeled wind data, and is applied to California for a period covering 1980–2015. With this approach, we investigate the unique meteorological patterns driving low and high wind years at five separate wind project sites. We also find wind regime changes over the 36-year period consistent with global warming: wind regimes associated with anomalously hot summer days increased at half a day per year and stagnant conditions increased at one-third days per year. Despite these changes, the average annual resource potential remained constant at all project sites. Additionally, we identify correlations between climate modes and wind regime frequency, a linkage valuable for resource characterization and forecasting. Our general approach can be applied in any location and may benefit many aspects of wind energy resource evaluation and forecasting.

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Research Organization:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Univ. of California, Oakland, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

DOE Contract Number:: AC02-05CH11231

OSTI ID:: 1543490

Journal Information:: Climate Dynamics, Vol. 52, Issue 7-8; ISSN 0930-7575

Publisher:: Springer-Verlag

Country of Publication:: United States

Language:: English

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