On the inter-annual variability of wind energy generation – A case study from Germany

Christopher Jung and Dirk Schindler

Applied Energy, 2018, vol. 230, issue C, 845-854

Abstract: The intermittent and stochastic nature of the wind resource complicates constant electricity supply in countries with high wind energy share in the electricity mix. Therefore, the goal of this study was to quantify the inter-annual variability of wind energy generation on the national scale by estimating upper and lower limits of annual wind energy generation (WEG). A novel methodology was developed and is presented for Germany, where onshore wind energy already accounts for more than 15% of net electricity consumption. First, a comprehensive wind turbine data set was produced including all onshore wind turbines operating in 2017. Next, the wind speed-wind shear model (WSWS) was used to reconstruct the high spatial resolution (200 m × 200 m) annual wind speed distributions in the wind turbine hub height range 30–179 m above ground level in the period 1979–2017. By using wind turbine-specific power curves, the annual wind energy yield was calculated for each wind turbine. It was summed up for the entire country, yielding WEG. Then, 16 theoretical distributions were fitted to WEG. From the fitted distributions, long-term return values of WEG were calculated. In a 100-year period (probability 98%), WEG lies between 67 and 112 TWh/yr and the annual greenhouse gas mitigation potential varies between 45.6 and 76.3 Mio. tCO2-equiv. under current climate. The great WEG-range emphasizes the importance of considering upper and lower WEG-limits for ensuring constant electricity supply at the national scale.

Keywords: Wind speed-wind shear model; Return level; Wind turbine; Johnson SB distribution; Wind energy availability (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:230:y:2018:i:c:p:845-854

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DOI: 10.1016/j.apenergy.2018.09.019

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