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Sub-national variability of wind power generation in complex terrain and its correlation with large-scale meteorology

Bibliographic Data

ID15545917
AuthorsBryn Pickering (0000-0003-4044-6587, ETH Zurich, corresponding author), Christian M Grams (0000-0003-3466-9389, Karlsruhe Institute of Technology), Stefan Pfenninger (0000-0002-8420-9498, ETH Zurich)
Year2020
Volume15
Issue4
Pages044025-044025
Publication date2020-01-29
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/ab70bd
OpenAlexW3004026634
LanguageEN
Citations received3
References cited13

The future European electricity system will depend heavily on variable renewable generation, including wind power. To plan and operate reliable electricity supply systems, an understanding of wind power variability over a range of spatio-temporal scales is critical. In complex terrain, such as that found in mountainous Switzerland, wind speeds are influenced by a multitude of meteorological phenomena, many of which occur on scales too fine to capture with commonly used meteorological reanalysis datasets. Past work has shown that anticorrelation at a continental scale is an important way to help balance variable generation. Here, we investigate systematically for the first time the possibility of balancing wind variability by exploiting anticorrelation between weather patterns in complex terrain. We assess the capability for the Consortium for Small-scale Modeling (COSMO)-REA2 and COSMO-REA6 reanalyses (with a 2 and 6 km horizontal resolution, respectively) to reproduce historical measured data from weather stations, hub height anemometers, and wind turbine electricity generation across Switzerland. Both reanalyses are insufficient to reproduce site-specific wind speeds in Switzerland’s complex terrain. We find however that mountain-valley breezes, orographic channelling, and variability imposed by European-scale weather regimes are represented by COSMO-REA2. We discover multi-day periods of wind electricity generation in regions of Switzerland which are anticorrelated with neighbouring European countries. Our results suggest that significantly more work is needed to understand the impact of fine scale wind power variability on national and continental electricity systems, and that higher-resolution reanalyses are necessary to accurately understand the local variability of renewable generation in complex terrain

Cartography · Climatology · Electricity generation · Geography · Meteorology · Orographic lift · Orography · Power (physics · Precipitation · Scale (ratio · Terrain · Wind power · Wind speed · Energy Load and Power Forecasting · Engineering · Environmental Science · Integrated Energy Systems Optimization · Meteorological Phenomena and Simulations · Geology

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Citations per year0.6
Citation span2021 - 2024 (4)
Highly citedNo

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