add Kimber soiling model

docs/examples/plot_greensboro_kimber_soiling.py

@@ -0,0 +1,62 @@
+"""
+Kimber Soiling Model
+====================
+
+Examples of soiling using the Kimber model [1]_.
+
+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`
+"""
+
+# %%
+# This example shows basic usage of pvlib's Kimber Soiling model with
+# :py:meth:`pvlib.losses.soiling_kimber`.
+#
+# 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
+from matplotlib import pyplot as plt
+from pvlib.iotools import read_tmy3
+from pvlib.losses import soiling_kimber
+from pvlib.tests.conftest import DATA_DIR
+
+# get TMY3 data with rain
+greensboro = read_tmy3(DATA_DIR / '723170TYA.CSV', coerce_year=1990)
+# NOTE: can't use Sand Point, AK b/c Lprecipdepth is -9900, ie: missing
+greensboro_rain = greensboro[0].Lprecipdepth
+# calculate soiling with no wash dates
+THRESHOLD = 25.0
+soiling_no_wash = soiling_kimber(greensboro_rain, threshold=THRESHOLD)
+soiling_no_wash.name = 'soiling'
+# daily rain totals
+daily_rain = greensboro_rain.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()

docs/sphinx/source/api.rst

@@ -315,6 +315,7 @@ Losses
    :toctree: generated/
 
    losses.soiling_hsu
+   losses.soiling_kimber
 
 
 Other

docs/sphinx/source/whatsnew/v0.7.2.rst

@@ -8,6 +8,7 @@ Enhancements
 * TMY3 dataframe returned by :py:func:`~pvlib.iotools.read_tmy3` now contains
   the original ``Date (MM/DD/YYYY)`` and ``Time (HH:MM)`` columns that the
   indices were parsed from (:pull:`866`)
+* Add Kimber soiling model :py:func:`pvlib.losses.soiling_kimber` (:pull:`860`)
 
 Bug fixes
 ~~~~~~~~~