def test_sandia_float(cec_inverter_parameters):
vdcs = 25.
idcs = 5.5
pdcs = idcs * vdcs
pacs = inverter.sandia(vdcs, pdcs, cec_inverter_parameters)
assert_allclose(pacs, 132.004278, 5)
# test at low power condition
vdcs = 25.
idcs = 0
pdcs = idcs * vdcs
pacs = inverter.sandia(vdcs, pdcs, cec_inverter_parameters)
assert_allclose(pacs, -1. * cec_inverter_parameters['Pnt'], 5)
def test_sandia_Pnt_micro():
"""
Test for issue #140, where some microinverters were giving a positive AC
power output when the DC power was 0.
"""
inverter_parameters = {
'Name': 'Enphase Energy: M250-60-2LL-S2x (-ZC) (-NA) 208V [CEC 2013]',
'Vac': 208.0,
'Paco': 240.0,
'Pdco': 250.5311318,
'Vdco': 32.06160667,
'Pso': 1.12048857,
'C0': -5.76E-05,
'C1': -6.24E-04,
'C2': 8.09E-02,
'C3': -0.111781106,
'Pnt': 0.043,
'Vdcmax': 48.0,
'Idcmax': 9.8,
'Mppt_low': 27.0,
'Mppt_high': 39.0,
}
vdcs = pd.Series(np.linspace(0, 50, 3))
idcs = pd.Series(np.linspace(0, 11, 3))
pdcs = idcs * vdcs
pacs = inverter.sandia(vdcs, pdcs, inverter_parameters)
assert_series_equal(pacs, pd.Series([-0.043, 132.545914746, 240.0]))
def test_sandia(cec_inverter_parameters):
vdcs = pd.Series(np.linspace(0, 50, 3))
idcs = pd.Series(np.linspace(0, 11, 3))
pdcs = idcs * vdcs
pacs = inverter.sandia(vdcs, pdcs, cec_inverter_parameters)
assert_series_equal(pacs, pd.Series([-0.020000, 132.004308, 250.000000]))
def test_sandia_float(cec_inverter_parameters):
vdcs = 25.
idcs = 5.5
pdcs = idcs * vdcs
pacs = inverter.sandia(vdcs, pdcs, cec_inverter_parameters)
assert_allclose(pacs, 132.004278, 5)
def basic_chain(times,
latitude,
longitude,
module_parameters,
temperature_model_parameters,
inverter_parameters,
irradiance=None,
weather=None,
surface_tilt=None,
surface_azimuth=None,
orientation_strategy=None,
transposition_model='haydavies',
solar_position_method='nrel_numpy',
airmass_model='kastenyoung1989',
altitude=None,
pressure=None,
**kwargs):
"""
An experimental function that computes all of the modeling steps
necessary for calculating power or energy for a PV system at a given
location.
Parameters
----------
times : DatetimeIndex
Times at which to evaluate the model.
latitude : float.
Positive is north of the equator.
Use decimal degrees notation.
longitude : float.
Positive is east of the prime meridian.
Use decimal degrees notation.
module_parameters : None, dict or Series
Module parameters as defined by the SAPM. See pvsystem.sapm for
details.
temperature_model_parameters : None, dict or Series.
Temperature model parameters as defined by the SAPM.
See temperature.sapm_cell for details.
inverter_parameters : None, dict or Series
Inverter parameters as defined by the CEC. See
:py:func:`inverter.sandia` for details.
irradiance : None or DataFrame, default None
If None, calculates clear sky data.
Columns must be 'dni', 'ghi', 'dhi'.
weather : None or DataFrame, default None
If None, assumes air temperature is 20 C and
wind speed is 0 m/s.
Columns must be 'wind_speed', 'temp_air'.
surface_tilt : None, float or Series, default None
Surface tilt angles in decimal degrees.
The tilt angle is defined as degrees from horizontal
(e.g. surface facing up = 0, surface facing horizon = 90)
surface_azimuth : None, float or Series, default None
Surface azimuth angles in decimal degrees.
The azimuth convention is defined
as degrees east of north
(North=0, South=180, East=90, West=270).
orientation_strategy : None or str, default None
The strategy for aligning the modules.
If not None, sets the ``surface_azimuth`` and ``surface_tilt``
properties of the ``system``. Allowed strategies include 'flat',
'south_at_latitude_tilt'. Ignored for SingleAxisTracker systems.
transposition_model : str, default 'haydavies'
Passed to system.get_irradiance.
solar_position_method : str, default 'nrel_numpy'
Passed to solarposition.get_solarposition.
airmass_model : str, default 'kastenyoung1989'
Passed to atmosphere.relativeairmass.
altitude : None or float, default None
If None, computed from pressure. Assumed to be 0 m
if pressure is also None.
pressure : None or float, default None
If None, computed from altitude. Assumed to be 101325 Pa
if altitude is also None.
**kwargs
Arbitrary keyword arguments.
See code for details.
Returns
-------
output : (dc, ac)
Tuple of DC power (with SAPM parameters) (DataFrame) and AC
power (Series).
"""
# use surface_tilt and surface_azimuth if provided,
# otherwise set them using the orientation_strategy
if surface_tilt is not None and surface_azimuth is not None:
pass
elif orientation_strategy is not None:
surface_tilt, surface_azimuth = \
get_orientation(orientation_strategy, latitude=latitude)
else:
raise ValueError('orientation_strategy or surface_tilt and '
'surface_azimuth must be provided')
if altitude is None and pressure is None:
altitude = 0.
pressure = 101325.
elif altitude is None:
altitude = atmosphere.pres2alt(pressure)
elif pressure is None:
pressure = atmosphere.alt2pres(altitude)
solar_position = solarposition.get_solarposition(
times,
latitude,
longitude,
altitude=altitude,
pressure=pressure,
method=solar_position_method,
**kwargs)
# possible error with using apparent zenith with some models
airmass = atmosphere.get_relative_airmass(
solar_position['apparent_zenith'], model=airmass_model)
airmass = atmosphere.get_absolute_airmass(airmass, pressure)
dni_extra = pvlib.irradiance.get_extra_radiation(solar_position.index)
aoi = pvlib.irradiance.aoi(surface_tilt, surface_azimuth,
solar_position['apparent_zenith'],
solar_position['azimuth'])
if irradiance is None:
linke_turbidity = clearsky.lookup_linke_turbidity(
solar_position.index, latitude, longitude)
irradiance = clearsky.ineichen(solar_position['apparent_zenith'],
airmass,
linke_turbidity,
altitude=altitude,
dni_extra=dni_extra)
total_irrad = pvlib.irradiance.get_total_irradiance(
surface_tilt,
surface_azimuth,
solar_position['apparent_zenith'],
solar_position['azimuth'],
irradiance['dni'],
irradiance['ghi'],
irradiance['dhi'],
model=transposition_model,
dni_extra=dni_extra)
if weather is None:
weather = {'wind_speed': 0, 'temp_air': 20}
cell_temperature = temperature.sapm_cell(
total_irrad['poa_global'], weather['temp_air'], weather['wind_speed'],
temperature_model_parameters['a'], temperature_model_parameters['b'],
temperature_model_parameters['deltaT'])
effective_irradiance = pvsystem.sapm_effective_irradiance(
total_irrad['poa_direct'], total_irrad['poa_diffuse'], airmass, aoi,
module_parameters)
dc = pvsystem.sapm(effective_irradiance, cell_temperature,
module_parameters)
ac = inverter.sandia(dc['v_mp'], dc['p_mp'], inverter_parameters)
return dc, ac
def forecast_ac_power(dc_out, invertermodel):
p_ac = inverter.sandia(dc_out.v_mp, dc_out.p_mp, invertermodel)
return p_ac
