reskit.wind.core.power_profile

reskit.wind.core.power_profile#

Functions#

apply_power_profile_projection(measured_wind_speed, ...)

Estimates wind speed values at target height based on another measured wind speed at a known height subject to a power-law scaling factor.

alpha_from_levels(low_wind_speed, low_height, ...)

Obtains the scaling factor given two wind speeds measured at two different known heights.

Module Contents#

reskit.wind.core.power_profile.apply_power_profile_projection(measured_wind_speed, measured_height, target_height, alpha=1 / 7)#

Estimates wind speed values at target height based on another measured wind speed at a known height subject to a power-law scaling factor.

Parameters:

measured_wind_speed (array_like) –

The raw wind speeds to be adjusted. If a single dimension array is given, it is assumed to represent timeseries values for a single location If a multidimensional array is given, the assumed dimensional context is (time, locations), and ‘targetLoc’ must be an iterable with the same length as the ‘locations’ dimension

measured_height : array_like The measurement height of the raw windspeeds. Must either be a single value, or an array of values with the same length as the “locations” dimension of measured_wind_speed

target_height : numeric or array_like The (hub) height to project each wind speed timeseries to Must either be a single value, or an array of values with the same length as the “locations” dimension of measured_wind_speed

alpha : numeric or array_like, optional The scaling factor used to project each wind speed timeseries, by default 1/7 Must either be a single value, or an array of values with the same length as the “locations” dimension of measured_wind_speed

Notes

The default scaling factor, alpha, equal to 1/7 corresponds to neutral stability conditions. Alpha values can also be computed using the following function:

alpha_from_levels(low_wind_speed, low_height, high_wind_speed, high_height)

Returns:

  • array_like

  • projected wind speeds with the same dimensions as measured_wind_speed

reskit.wind.core.power_profile.alpha_from_levels(low_wind_speed, low_height, high_wind_speed, high_height)#

Obtains the scaling factor given two wind speeds measured at two different known heights.

Parameters:

  • low_wind_speed (numeric or array_like) – The measured windspeed at the ‘lower height’

  • low_height (numeric or array_like) – The measured height at the ‘lower height’

  • high_wind_speed (numeric or array_like) – The measured windspeed at the ‘higher height’

  • high_height (numeric or array_like) – The measured height at the ‘higher height’

Returns:

The corresponding scaling factor The output dimensionality follows the broadcasting rules of Numpy

Return type:

numeric or array-like

Notes

The projection of wind speed values at a given height using the returned scaling factors can be computed using the following function:

apply_power_profile_projection(measured_wind_speed, measured_height, target_height, alpha)