solarforecastarbiter.reference_forecasts.main.run¶

solarforecastarbiter.reference_forecasts.main.run(site, model, init_time, start, end)[source]¶

Calculate benchmark irradiance and power forecasts for a site.

The meaning of the timestamps (instantaneous or interval average) is determined by the model processing function.

It’s currently the user’s job to determine time parameters that correspond to a particular Forecast Evaluation Time Series.

Parameters:	site : datamodel.Site model : function NWP model loading and processing function. See `solarforecastarbiter.reference_forecasts.models` for options. init_time : pd.Timestamp NWP model initialization time. start : pd.Timestamp Start of the forecast. end : pd.Timestamp End of the forecast.
Returns:	ghi : pd.Series dni : pd.Series dhi : pd.Series temp_air : None or pd.Series wind_speed : None or pd.Series ac_power : None or pd.Series

Examples

The following code would return hourly average forecasts derived from the subhourly HRRR model.

>>> from solarforecastarbiter import datamodel
>>> from solarforecastarbiter.reference_forecasts import models
>>> init_time = pd.Timestamp('20190328T1200Z')
>>> start = pd.Timestamp('20190328T1300Z')  # typical available time
>>> end = pd.Timestamp('20190329T1300Z')  # 24 hour forecast
>>> modeling_parameters = datamodel.FixedTiltModelingParameters(
...     ac_capacity=10, dc_capacity=15,
...     temperature_coefficient=-0.004, dc_loss_factor=0,
...     ac_loss_factor=0)
>>> power_plant = datamodel.SolarPowerPlant(
...     name='Test plant', latitude=32.2, longitude=-110.9,
...     elevation=715, timezone='America/Phoenix',
...     modeling_parameters = modeling_parameters)
>>> ghi, dni, dhi, temp_air, wind_speed, ac_power = run(
...     power_plant, models.hrrr_subhourly_to_hourly_mean,
...     init_time, start, end)