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This is done in order to compare the inter-year variation in powers for a given periodicity.
However, the linearly regressed 10.7 cm flux and fractional variation in powers diverge in cycles 22 and 24, indicating that the relationship between the mode powers and the 10.7 cm flux is not consistent from one cycle to the next.
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Ambient temperature affects the variation in power demand.
An analysis of Pc1 2 events indicates a seasonal variation, consistent with a similar variation in power.
Generally, wind speed is stochastic, which leads to variation in power coefficient.
This figure shows the variation in power with height and the tendency to layering.
Because this tip speed ratio gets affected, it will lead to the variation in power coefficient.
This technique monitors each variation in power output and integrates those variations over a specified sample period.
Quantitative analysis of power consumption involves three parameters: rate of variation in power consumption, interactive mode and ratio of power consumption.
A compromise can be achieved between loads and variation in power without any information of the damping of wind turbine (Yolanda et al. 2012).
This paper investigated the variation in power to detect a change in the spatial distribution in the presence of spatial aggregation.
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