Sensors

Sensors (base class)

class onwards.Sensors(i_bf: int, data_path: str, snrs_args: dict)

Bases: object

Prototype Sensors class.

Parameters

i_bf (int) – Index of the wind turbine
farm_data_dir (str) – Path to the data directory path.
snrs_args (dict) – Dictionary containing the parameters used for the turbines Sensors initialization (refer to Sensors).

SensorsPy

class onwards.sensors.SensorsPy(data_path: str, fs: float = None, field_names: List[float] = None, time_bnds: list[float] = None, zero_origin: bool = False, **kwargs)

Bases: onwards.sensors.Sensors

Inits a SensorPy object that extract data from AD output files.

This class allows to read data extracted by the Actuator Disks used within the high fidelity Large Eddy Simulation solver (developed at UCLouvain 1). The Actuator Disk provides a full description of the wind turbine operating settings (rotation speed, pitch angle, etc.) and loads. The later are obtained by projecting the disk loads over fictive blades.

The SensorsPy object serves as an interface between the High Fidelity numerical environment and the OnWaRDS framework.

Parameters

data_path (str) – Path to the data directory path.
fs (float, optional) – Sampling frequency in [Hz]. If None (by default), the original time sampling is preserved.
field_names (list, optional) – Name of the measurements to be extracted from the Actuator Disk data.
time_bnds (list[float], optional) – Data range to be extracted: time_bnds[0] is the simulation start time and time_bnds[-1] is the end time, by default None.
zero_origin (bool, optional) – If set to True, the time vector will be updated so that the initial time is set to 0, by default False.

Raises

KeyError – If the data field/measurement requested is not available.

References

1

Moens, M. Duponcheel, G. Winckelmans, and P. Chatelain. An actuator disk method with tip-loss correction based on local effective upstream velocities. Wind Energy, 21(9):766-782, 2018.

get_buffer_data(fld, i_b=None)

Retrieves the current value of the measurement fld.

Parameters

fld (str) – Name of the measurement.
i_b (int, optional) – Blade index, by default None.

Returns

The current value of measurement fld (for blade i_b).

Return type

float

get_sensor_data(fld, t, i_b=None)

interp(fs: float = None, time_bnds: List[float] = None)

Reinterpolate the data within the specified bounds with the specified frequency.

Parameters

fs (float, optional) – Sampling frequency in [Hz]. If None (by default), the original time sampling is preserved.
time_bnds (list[float], optional) – Data range to be extracted: time_bnds[0] is the simulation start time and time_bnds[-1] is the end time, by default None.

Raises

ValueError – If the sensors time bounds selected fall outside the available range.
Exception – If reference LES data could not be cast to the correct format.

iterate()

Updates the Sensors object.

Returns: The new time in [sec].
Return type: float

reset(time: Optional[float] = None): Reset the Sensors to its initial state.

SensorsPreprocessed

class onwards.sensors.SensorsPreprocessed(i_bf: int, farm_data_dir: str, name: str, fs: float, **kwargs)

Bases: onwards.sensors.SensorsPy

Imports the wind turbine estimated states from past simulations.

Along with the StateExport class, it allows direct feed through of the sensors measurements to the Farm.lag_solver.

This allows for fast computations when evaluating the performances of the Lagrangian (ie: skips the turbine states estimation step).

Parameters

i_bf (int) – Index of the wind turbine
farm_data_dir (str) – Path to the data directory path.
name (str) – Name of the subdirectory where the preprocessed sensor file where saved (ie: export_args[‘name’])
fs (float) – Sampling frequency in [Hz]. If None (by default), the original time sampling is preserved.