API Reference¶

class wind_stats.GWAReader¶

Methods

`load`(fp)	Deserialize fp GWC file-like object to dataset.
`loads`(s[, encoding])	Deserialize s (a str, bytes or bytearray instance containing a GWC document) to Dataset.

static load(fp: SupportsRead) → Dataset¶: Deserialize fp GWC file-like object to dataset.

static loads(s: str | bytes, encoding: str = 'ASCII') → Dataset¶: Deserialize s (a str, bytes or bytearray instance containing a GWC document) to Dataset.

class wind_stats.PowerCurve(wind_speed: Quantity, power: Quantity)¶

Power curve.

Parameters:

wind_speed: `pint.Quantity`: wind speed data
wind_speed: `pint.Quantity`: power data

Methods

__call__(x)

Linear interpolation on the power curve.

Examples

>>> power_data = [
        43.0,
        184.0,
        421.0,
        778.0,
        1270.0,
        1905.0,
        2593.0,
        3096.0,
        3268.0,
        3297.0,
        3300.0,
    ] * units.kW
>>> wind_speeds = np.arange(3, 13) * units("m/s")
>>> power_curve = PowerCurve(wind_speeds, power_data)
>>> power_curve(8  * units("m/s"))
<Quantity(1905.0, 'kilowatt')>
>>> power_curve(40  * units("m/s"))
<Quantity(0.0, 'kilowatt')>

class wind_stats.Site(latitude: float, longitude: float, distribution: ~wind_stats.models.WindDistribution, elevation: float = 0.0, avg_temperature=<Quantity(15, 'degree_Celsius')>, avg_humidity: float = 0.0)¶

Site location.

Attributes

latitude
longitude
distribution: WindDistribution
elevation
avg_temperature

Methods

`create_gwa_data`(latitude, longitude, ...)	Create Site with Global Wind Atlas Data.
`get_mean_power_density`()	Get mean power density in W/m².

property air_density¶

classmethod create_gwa_data(latitude: float, longitude: float, roughness_length: float | List[float], height: float, **kwargs) → Site¶

Create Site with Global Wind Atlas Data.

Retrieve GWA data & initiate Site with Wind distribution.

get_mean_power_density() → Quantity¶

Get mean power density in W/m².

Notes

Mean power density :

\[\bar{P}_{density} = \frac{1}{2} \cdot \rho \cdot \int_{0}^{\infty}[v^3 pdf(v)] dv\]

property mean_power_density: Quantity¶

property mean_wind: Quantity¶: Mean wind speeds at site in m/s.

class wind_stats.WindDistribution(distribution: rv_continuous)¶

Wind distribution.

Attributes

mean_wind_speed

Methods

`from_data`(wind_speed_data, roughness_length, ...)	Create KDE WindDistribution based on measurement data.
`from_gwc`(gwc_dataset, roughness_length, height)	Create Weibull WindDistribution based on GWC file dataset.
`moment`(n)	Get n-raw moment of the distribution.
`pdf`(x)	Probability density function.
`weibull`(A, k)	Create Weibull WindDistribution.

classmethod from_data(wind_speed_data, roughness_length: float | List[float], measurement_height: float, height: float) → WindDistribution¶: Create KDE WindDistribution based on measurement data.

classmethod from_gwc(gwc_dataset: xr.Dataset, roughness_length: float | List[float], height: float) → WindDistribution¶: Create Weibull WindDistribution based on GWC file dataset.

property mean_wind_speed: Quantity¶

moment(n: int) → float¶: Get n-raw moment of the distribution.

pdf(x: float) → float¶: Probability density function.

classmethod weibull(A: float, k: float) → WindDistribution¶: Create Weibull WindDistribution.

class wind_stats.WindTurbine(name: str, power_curve: Tuple[Quantity, Quantity], diameter: float, height: float)¶

Attributes

rotor_area

Swept rotor area.

Methods

`get_annual_energy_production`(site)	Get annual energy production.
`get_energy_production`(site, time)	Calculate energy output over a period of time.
`get_mean_power`(site)	Mean power output.
`get_power_coefficients`()	Get Cp coefficients for wind speeds defined in the power curve.

get_annual_energy_production(site: Site) → Quantity¶

Get annual energy production.

Integrate wind frequency with power curve & annual hours.

Parameters:

site: Site: Site where the wind turbine is located.

Returns:

energy: pint.Quantity: Annual energy to be expected in Wh.