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The article demonstrates the characteristics of wind power variability and net load variability in multiple power systems based on real data from multiple years. Demonstrated characteristics include probability distribution for different ramp durations, seasonal and diurnal variability, and low net load events. In some characteristics the power systems are different, but in others they are significantly similar. Somewhat surprisingly there seems to be no straightforward correlation between wind power penetration level and variability. As long as there are several wind power plants with enough geographical spread, most of the smoothing impact is captured. Wind power variability is mainly explained by the extent of geographical spread, but also higher capacity factor causes higher variability. It was also shown how wind power ramps are auto correlated and dependent on the operating output level. In most cases wind power did not have strong diurnal or seasonal variations in the variability. However, there can be exceptions depending on the latitude and on the local characteristics of the wind resource., QC 170309, Elektra 36141: Korttidsplanering av vatten-värmekraftsystem vid stora mängder vindkraft: System-perspektivet

Variability of large scale wind power generation isdependent on several factors: characteristics of installed windpower plants, size of the area where the plants are installed,geographic dispersion within that area and its weatherregime(s). Variability can be described by ramps in powergeneration, i.e. changes from time period to time period. Givenenough data points, it can be described with a probabilitydensity function. This approach focuses on two dimensions ofvariability: duration of the ramp and probability distribution.This paper proposes an index based on these two dimensionsto enable comparisons and characterizations of variabilityunder different conditions. The index is tested with real, largescale wind power generation data from several countries.Considerations while forming an index are discussed, as wellas the main results regarding what the drivers of variabilityexperienced for different data., QC 20150409, Elektra 36141: Korttidsplanering av vatten-värmekraftsystem vid stora mängder vindkraft: System-perspektivet