Kimber Soiling Model

Examples of soiling using the Kimber model.

This example shows basic usage of pvlib’s Kimber Soiling model 1 with pvlib.soiling.kimber().

References

1

“The Effect of Soiling on Large Grid-Connected Photovoltaic Systems in California and the Southwest Region of the United States,” Adrianne Kimber, et al., IEEE 4th World Conference on Photovoltaic Energy Conference, 2006, DOI: 10.1109/WCPEC.2006.279690

The Kimber Soiling model assumes that soiling builds up at a constant rate until cleaned either manually or by rain. The rain must reach a threshold to clean the panels. When rains exceeds the threshold, it’s assumed the earth is damp for a grace period before it begins to soil again. There is a maximum soiling build up that cannot be exceeded even if there’s no rain or manual cleaning.

Threshold

The example shown here demonstrates how the threshold affects soiling. Because soiling depends on rainfall, loading weather data is always the first step.

from datetime import datetime
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 [%]'])
plt.tight_layout()

plt.show()
Kimber Soiling Model, dashed line shows threshold (25.0[mm])

Total running time of the script: ( 0 minutes 0.374 seconds)

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