def test_kimber_initial_soil(greensboro_rain, expected_kimber_initial_soil):
"""Test Kimber soiling model with initial soiling"""
# a year with no rain
norain = pd.Series(0, index=greensboro_rain.index)
# calculate soiling with no rain
norain = kimber(norain, initial_soiling=0.1)
# test no rain, soiling reaches maximum
assert np.allclose(norain.values, expected_kimber_initial_soil)
def test_kimber_nowash(greensboro_rain, expected_kimber_nowash):
"""Test Kimber soiling model with no manual washes"""
# Greensboro typical expected annual rainfall is 8345mm
assert greensboro_rain.sum() == 8345
# calculate soiling with no wash dates
nowash = kimber(greensboro_rain)
# test no washes
assert np.allclose(nowash.values, expected_kimber_nowash['soiling'].values)
def test_kimber_manwash(greensboro_rain, expected_kimber_manwash):
"""Test Kimber soiling model with a manual wash"""
# a manual wash date
manwash = [datetime.date(1990, 2, 15), ]
# calculate soiling with manual wash
manwash = kimber(greensboro_rain, manual_wash_dates=manwash)
# test manual wash
assert np.allclose(
manwash.values,
expected_kimber_manwash['soiling'].values)
import pathlib
from matplotlib import pyplot as plt
from pvlib.iotools import read_tmy3
from pvlib.soiling import kimber
import pvlib
# get full path to the data directory
DATA_DIR = pathlib.Path(pvlib.__file__).parent / 'data'
# get TMY3 data with rain
greensboro, _ = read_tmy3(DATA_DIR / '723170TYA.CSV', coerce_year=1990)
# get the rain data
greensboro_rain = greensboro.Lprecipdepth
# calculate soiling with no wash dates and cleaning threshold of 25-mm of rain
THRESHOLD = 25.0
soiling_no_wash = kimber(greensboro_rain, cleaning_threshold=THRESHOLD)
soiling_no_wash.name = 'soiling'
# daily rain totals
daily_rain = greensboro_rain.iloc[:-1].resample('D').sum()
plt.plot(
daily_rain.index.to_pydatetime(), daily_rain.values/25.4,
soiling_no_wash.index.to_pydatetime(), soiling_no_wash.values*100.0)
plt.hlines(
THRESHOLD/25.4, xmin=datetime(1990, 1, 1), xmax=datetime(1990, 12, 31),
linestyles='--')
plt.grid()
plt.title(
f'Kimber Soiling Model, dashed line shows threshold ({THRESHOLD}[mm])')
plt.xlabel('timestamp')
plt.ylabel('soiling build-up fraction [%] and daily rainfall [inches]')
plt.legend(['daily rainfall [in]', 'soiling [%]'])
