# Source code for pvlib.snow

```
"""
The ``snow`` module contains functions that model module snow cover and the
associated effects on PV module output
"""
import numpy as np
import pandas as pd
from pvlib.tools import sind
def _time_delta_in_hours(times):
delta = times.to_series().diff()
return delta.dt.total_seconds().div(3600)
[docs]def fully_covered_nrel(snowfall, threshold_snowfall=1.):
'''
Calculates the timesteps when the row's slant height is fully covered
by snow.
Parameters
----------
snowfall : Series
Accumulated snowfall in each time period [cm]
threshold_snowfall : float, default 1.0
Hourly snowfall above which snow coverage is set to the row's slant
height. [cm/hr]
Returns
----------
boolean: Series
True where the snowfall exceeds the defined threshold to fully cover
the panel.
Notes
-----
Implements the model described in [1]_ with minor improvements in [2]_.
References
----------
.. [1] Marion, B.; Schaefer, R.; Caine, H.; Sanchez, G. (2013).
"Measured and modeled photovoltaic system energy losses from snow for
Colorado and Wisconsin locations." Solar Energy 97; pp.112-121.
.. [2] Ryberg, D; Freeman, J. "Integration, Validation, and Application
of a PV Snow Coverage Model in SAM" (2017) NREL Technical Report
NREL/TP-6A20-68705
'''
timestep = _time_delta_in_hours(snowfall.index)
hourly_snow_rate = snowfall / timestep
# if we can infer a time frequency, use first snowfall value
# otherwise the first snowfall value is ignored
freq = pd.infer_freq(snowfall.index)
if freq is not None:
timedelta = pd.tseries.frequencies.to_offset(freq) / pd.Timedelta('1h')
hourly_snow_rate.iloc[0] = snowfall[0] / timedelta
else: # can't infer frequency from index
hourly_snow_rate[0] = 0 # replaces NaN
return hourly_snow_rate > threshold_snowfall
[docs]def coverage_nrel(snowfall, poa_irradiance, temp_air, surface_tilt,
initial_coverage=0, threshold_snowfall=1.,
can_slide_coefficient=-80., slide_amount_coefficient=0.197):
'''
Calculates the fraction of the slant height of a row of modules covered by
snow at every time step.
Implements the model described in [1]_ with minor improvements in [2]_,
with the change that the output is in fraction of the row's slant height
rather than in tenths of the row slant height. As described in [1]_, model
validation focused on fixed tilt systems.
Parameters
----------
snowfall : Series
Accumulated snowfall within each time period. [cm]
poa_irradiance : Series
Total in-plane irradiance [W/m^2]
temp_air : Series
Ambient air temperature [C]
surface_tilt : numeric
Tilt of module's from horizontal, e.g. surface facing up = 0,
surface facing horizon = 90. [degrees]
initial_coverage : float, default 0
Fraction of row's slant height that is covered with snow at the
beginning of the simulation. [unitless]
threshold_snowfall : float, default 1.0
Hourly snowfall above which snow coverage is set to the row's slant
height. [cm/hr]
can_slide_coefficient : float, default -80.
Coefficient to determine if snow can slide given irradiance and air
temperature. [W/(m^2 C)]
slide_amount_coefficient : float, default 0.197
Coefficient to determine fraction of snow that slides off in one hour.
[unitless]
Returns
-------
snow_coverage : Series
The fraction of the slant height of a row of modules that is covered
by snow at each time step.
Notes
-----
In [1]_, `can_slide_coefficient` is termed `m`, and the value of
`slide_amount_coefficient` is given in tenths of a module's slant height.
References
----------
.. [1] Marion, B.; Schaefer, R.; Caine, H.; Sanchez, G. (2013).
"Measured and modeled photovoltaic system energy losses from snow for
Colorado and Wisconsin locations." Solar Energy 97; pp.112-121.
.. [2] Ryberg, D; Freeman, J. (2017). "Integration, Validation, and
Application of a PV Snow Coverage Model in SAM" NREL Technical Report
NREL/TP-6A20-68705
'''
# find times with new snowfall
new_snowfall = fully_covered_nrel(snowfall, threshold_snowfall)
# set up output Series
snow_coverage = pd.Series(np.nan, index=poa_irradiance.index)
# determine amount that snow can slide in each timestep
can_slide = temp_air > poa_irradiance / can_slide_coefficient
slide_amt = slide_amount_coefficient * sind(surface_tilt) * \
_time_delta_in_hours(poa_irradiance.index)
slide_amt[~can_slide] = 0.
# don't slide during snow events
slide_amt[new_snowfall] = 0.
# don't slide in the interval preceding the snowfall data
slide_amt.iloc[0] = 0
# build time series of cumulative slide amounts
sliding_period_ID = new_snowfall.cumsum()
cumulative_sliding = slide_amt.groupby(sliding_period_ID).cumsum()
# set up time series of snow coverage without any sliding applied
snow_coverage[new_snowfall] = 1.0
if np.isnan(snow_coverage.iloc[0]):
snow_coverage.iloc[0] = initial_coverage
snow_coverage.ffill(inplace=True)
snow_coverage -= cumulative_sliding
# clean up periods where row is completely uncovered
return snow_coverage.clip(lower=0)
[docs]def dc_loss_nrel(snow_coverage, num_strings):
'''
Calculates the fraction of DC capacity lost due to snow coverage.
DC capacity loss assumes that if a string is partially covered by snow,
the string's capacity is lost; see [1]_, Eq. 11.8.
Module orientation is accounted for by specifying the number of cell
strings in parallel along the slant height.
For example, a typical 60-cell module has 3 parallel strings, each
comprising 20 cells in series, with the cells arranged in 6 columns of 10
cells each. For a row consisting of single modules, if the module is
mounted in portrait orientation, i.e., the row slant height is along a
column of 10 cells, there is 1 string in parallel along the row slant
height, so `num_strings=1`. In contrast, if the module is mounted in
landscape orientation with the row slant height comprising 6 cells, there
are 3 parallel strings along the row slant height, so `num_strings=3`.
Parameters
----------
snow_coverage : numeric
The fraction of row slant height covered by snow at each time step.
num_strings: int
The number of parallel-connected strings along a row slant height.
Returns
-------
loss : numeric
fraction of DC capacity loss due to snow coverage at each time step.
References
----------
.. [1] Gilman, P. et al., (2018). "SAM Photovoltaic Model Technical
Reference Update", NREL Technical Report NREL/TP-6A20-67399.
Available at https://www.nrel.gov/docs/fy18osti/67399.pdf
'''
return np.ceil(snow_coverage * num_strings) / num_strings
```