The Kimber soiling model is a simple model of predicting a time series of soiling ratio values based on an assumed linear soiling accumulation rate and the timing of rainfall and other cleaning events.
The model’s soiling rate represents the rate of performance loss accumulation rather than some physical rate involving particulate mass or volume. It is assumed to be determined in advance, typically via empirical extraction from measured PV performance data. The model’s authors estimated soiling accumulation rates of 0.1–0.3 %/day at locations in the southwest United States.
Rainfall above a minimum threshold constitutes a cleaning event that resets the accumulated soiling ratio to 1.0. The model also includes a grace period where no soiling occurs in the period following rainfall cleaning events.
An example soiling ratio time series from the Kimber model, assuming a soiling accumulation rate of 0.2%/day, a 14-day grace period, and a cleaning threshold of 3 mm, is shown below:
Where the soiling ratio and daily rainfall are shown in orange and blue color, respectively.
The Kimber soiling model is implemented in pvlib-python with pvlib.soiling.kimber.
References
[1] A. Kimber, L. Mitchell, S. Nogradi, and H. Wenger, “The Effect of Soiling on Large Grid-Connected Photovoltaic Systems in California and the Southwest Region of the United States,” 2006 IEEE 4th World Conference on Photovoltaic Energy Conference. 2006. doi: 10.1109/wcpec.2006.279690.