"""
Collection of classes and functions to calculate different temperatures.
"""
import pvlib
import pvdeg
[docs]
def module(
weather_df,
meta,
poa=None,
temp_model="sapm",
conf="open_rack_glass_polymer",
wind_factor=0.33,
):
"""
Calculate module surface temperature using pvlib.
Parameters
----------
weather_df : (pd.dataframe)
Data Frame with minimum requirements of 'temp_air' and 'wind_speed'
poa : pandas.DataFrame
Contains keys/columns 'poa_global', 'poa_direct', 'poa_diffuse',
'poa_sky_diffuse', 'poa_ground_diffuse'.
temp_model : str, optional
The temperature model to use, Sandia Array Performance Model 'sapm'
from pvlib by default.
conf : str, optional
The configuration of the PV module architecture and mounting
configuration.
Options:
'sapm': 'open_rack_glass_polymer' (default),
'open_rack_glass_glass', 'close_mount_glass_glass',
'insulated_back_glass_polymer'
Returns
-------
module_temperature : pandas.DataFrame
The module temperature in degrees Celsius at each time step.
"""
parameters = pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS[temp_model][conf]
if poa is None:
poa = pvdeg.spectral.poa_irradiance(weather_df, meta)
if "wind_height" not in meta.keys():
wind_speed_factor = 1
else:
if temp_model == "sapm":
wind_speed_factor = (10 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "pvsyst":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "faiman":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "faiman_rad":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "fuentes":
wind_speed_factor = (5 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "ross":
wind_speed_factor = (
10 / float(meta["wind_height"])
) ** wind_factor # I had to guess what this one was
elif temp_model == "noct_sam":
if meta["wind_height"] > 3:
wind_speed_factor = 2
else:
wind_speed_factor = (
1 # The wind speed height is managed weirdly for this one.
)
elif temp_model == "prilliman":
wind_speed_factor = (
1 # this model will take the wind speed height in and do an adjustment.
)
elif temp_model == "generic_linear":
wind_speed_factor = (10 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "GenericLinearModel":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
# this one does a linear conversion from the other models, faiman, pvsyst, noct_sam, sapm_module and generic_linear.
# An appropriate facter will need to be figured out.
else:
wind_speed_factor = 1 # this is just hear for completeness.
# TODO put in code for the other models, PVSYS, Faiman,
if temp_model == "sapm":
module_temperature = pvlib.temperature.sapm_module(
poa_global=poa["poa_global"],
temp_air=weather_df["temp_air"],
wind_speed=weather_df["wind_speed"] * wind_speed_factor,
a=parameters["a"],
b=parameters["b"],
)
else:
# TODO: add options for temperature model
print("There are other models but they haven't been implemented yet!")
return module_temperature
[docs]
def cell(
weather_df,
meta,
poa=None,
temp_model="sapm",
conf="open_rack_glass_polymer",
wind_factor=0.33,
):
"""
Calculate the PV cell temperature using PVLIB
Currently this only supports the SAPM temperature model.
Parameters:
-----------
weather_df : (pd.dataframe)
Data Frame with minimum requirements of 'temp_air' and 'wind_speed'
meta : (dict)
Weather meta-data dictionary (location info)
poa : (dataframe or series, optional)
Dataframe or series with minimum requirement of 'poa_global'
temp_model : (str, optional)
Specify which temperature model from pvlib to use. Current options:
'sapm'
conf : (str)
The configuration of the PV module architecture and mounting
configuration.
Options: 'open_rack_glass_polymer' (default), 'open_rack_glass_glass',
'close_mount_glass_glass', 'insulated_back_glass_polymer'
wind_factor : float, optional
Wind speed correction exponent to account for different wind speed measurement heights
between weather database (e.g. NSRDB) and the tempeature model (e.g. SAPM)
The NSRDB provides calculations at 2 m (i.e module height) but SAPM uses a 10 m height.
It is recommended that a power-law relationship between height and wind speed of 0.33
be used*. This results in a wind speed that is 1.7 times higher. It is acknowledged that
this can vary significantly.
R. Rabbani, M. Zeeshan, "Exploring the suitability of MERRA-2 reanalysis data for wind energy
estimation, analysis of wind characteristics and energy potential assessment for selected
sites in Pakistan", Renewable Energy 154 (2020) 1240-1251.
Return:
-------
temp_cell : pandas.DataFrame
This is the temperature of the cell in a module at every time step.[°C]
"""
if "wind_height" not in meta.keys():
wind_speed_factor = 1
else:
if temp_model == "sapm":
wind_speed_factor = (10 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "pvsyst":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "faiman":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "faiman_rad":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "fuentes":
wind_speed_factor = (5 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "ross":
wind_speed_factor = (
10 / float(meta["wind_height"])
) ** wind_factor # I had to guess what this one was
elif temp_model == "notc_sam":
if float(meta["wind_height"]) > 3:
wind_speed_factor = 2
else:
wind_speed_factor = (
1 # The wind speed height is managed weirdly for this one.
)
elif temp_model == "prilliman":
wind_speed_factor = (
1 # this model will take the wind speed height in and do an adjustment.
)
elif temp_model == "generic_linear":
wind_speed_factor = (10 / float(meta["wind_height"])) ** wind_factor
elif temp_model == "GenericLinearModel":
wind_speed_factor = (2 / float(meta["wind_height"])) ** wind_factor
# this one does a linear conversion from the other models, faiman, pvsyst, noct_sam, sapm_module and generic_linear.
# An appropriate facter will need to be figured out.
else:
wind_speed_factor = 1 # this is just here for completeness.
parameters = pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS[temp_model][conf]
if poa is None:
poa = pvdeg.spectral.poa_irradiance(weather_df, meta)
if temp_model == "sapm":
temp_cell = pvlib.temperature.sapm_cell(
poa_global=poa["poa_global"],
temp_air=weather_df["temp_air"],
wind_speed=weather_df["wind_speed"] * wind_speed_factor,
**parameters,
)
else:
# TODO: add options for temperature model
print("There are other models but they haven't been implemented yet!")
return temp_cell
