Wind Power¶

Estimates wind turbine power output from a wind speed variable.

`winpow`¶

Converts wind speed to power using a third-order polynomial fitted to a reference turbine power curve, then applies cut-in, rated, and cut-out speed limits.

Parameter	Type	Default	Description
`turbine_power`	float	—	Rated power output in kW. Required.
`cutin`	float	`3.0`	Cut-in wind speed (m/s). Output is zero below this.
`rated`	float	`10.61`	Rated wind speed (m/s). Output is capped at `turbine_power` above this.
`cutout`	float	`25.0`	Cut-out wind speed (m/s). Output is zero above this.
`agg`	str \| null	`"mean"`	Aggregation applied after computing instantaneous power (`"mean"`, `"max"`, etc.). Set to `null` to return the full power time series.
`group`	str \| null	`null`	Time grouping (`month`, `season`, `year`). Only valid when `agg` is set.

Power curve¶

The polynomial is fitted to a reference 16 MW offshore turbine curve. The relationship between wind speed and output power follows:

P(v) = a·v + b·v² + c·v³ + d    for  cutin < v < rated
P(v) = turbine_power              for  rated ≤ v < cutout
P(v) = 0                          for  v ≤ cutin  or  v ≥ cutout

The polynomial coefficients are fitted internally — only turbine_power is needed to scale the output to your turbine's rated capacity.

Examples¶

Mean power output for a 15 MW turbine:

- func: winpow
  dim: time
  data_vars: [wspd]
  turbine_power: 15000   # kW
  agg: mean

Monthly mean and maximum power with custom speed limits:

- func: winpow
  dim: time
  data_vars: [wspd]
  turbine_power: 8000
  cutin: 4.0
  rated: 12.0
  cutout: 25.0
  agg: mean
  group: month

Return the full instantaneous power time series (no aggregation):

- func: winpow
  dim: time
  data_vars: [wspd]
  turbine_power: 15000
  agg: null

Note

winpow operates on the first variable in data_vars. Pass a single wind-speed variable per call.

API reference¶

`gridstats.ops.windpower.winpow(data: xr.Dataset, *, dim: str = 'time', turbine_power: float, cutin: float = 3.0, rated: float = 10.61, cutout: float = 25.0, agg: str | None = 'mean', group: str | None = None, **kwargs) -> xr.Dataset` ¶

Estimate wind turbine power from wind speed.

Fits a third-order polynomial to a reference power curve, then applies cut-in, rated, and cut-out speed thresholds.

Parameters:

Name	Type	Description	Default
`data`	`Dataset`	Input dataset. Must contain a wind-speed variable (first data var is used as the wind-speed input).	required
`dim`	`str`	Time dimension name.	`'time'`
`turbine_power`	`float`	Rated mechanical power output (kW).	required
`cutin`	`float`	Cut-in wind speed below which output is zero (m/s).	`3.0`
`rated`	`float`	Rated wind speed above which output is capped (m/s).	`10.61`
`cutout`	`float`	Cut-out wind speed above which output is zero (m/s).	`25.0`
`agg`	`str \| None`	Aggregation to apply after computing instantaneous power ('mean', 'max', etc.). Pass None to return the full time series.	`'mean'`
`group`	`str \| None`	Time component to group by (only supported when agg is set).	`None`

Returns:

Type	Description
`Dataset`	Dataset with wind power variable(s).

Raises:

Type	Description
`NotImplementedError`	If group is provided without agg.