Fig 1.
Example of assigned ranks for one wind park of 20 turbines with energy yield data covering 10 years.
The ranks were assigned according to the median ratio of ideal and real capacity factors normalized by their median per month and park.
Fig 2.
Map of Germany's 10 main postal code zones (PLZ) and their total installed capacity of wind turbines in December 2014.
Main postal code zones are divided in up to a maximum of 1000 postal code areas. Seven zones were included as fixed effect in the model: PLZ0 to PLZ5 and PLZ6+. The latter includes PLZ6 to PLZ9 as in the south of Germany the installed capacity is low.
Fig 3.
Changes in onshore wind turbine characteristics in Germany from the year 2000 to 2014.
The panels show (a) the age of wind turbines, (b) turbine capacity, (c) rotor swept area, (d) specific power and (e) park size (in terms of N, the number of turbines per park) and (f) the density of installed capacity per postal code area. The black lines refer to the mean of the distribution of values, while the shaded areas indicate the range of values in terms of the 25%-75% percentile (dark blue) and the 5%-95% percentile (light blue).
Fig 4.
Temporal variability of capacity factors illustrated as (a) time series of monthly capacity factors of all turbines in the BDByield database and as (b) seasonal variability of monthly mean capacity factors per turbine.
Table 1.
Estimated fixed effects, their standard errors (SE), and the t-values obtained from the mixed-effects model.
Fig 5.
Reported and estimated annual yield for onshore wind energy generation in Germany.
The sum of estimated yields and losses due to the age effect, park effect and other effects equals the annual ideal wind energy yield as estimated from wind speed, air density, and turbine characteristics (source of reported yields: [24]).
Table 2.
Reported and estimated annual wind energy yields as well as relative losses of energy yield due to effects of age, park size, and other unknown effects.
The estimated annual energy yield corresponds to the sum of monthly yields of all turbines in BDBsites. Monthly yields of the turbines were derived from capacity factor predictions of the mixed-effects model.