Endogenous soiling rate determination and detection of cleaning events in utility scale PV plants

Abstract

As the deployment rate of PV power plants continuesto soar, the need for robust, scalable methods for performanceanalytics increases. In this paper, we demonstrate the usefulness ofone approach for quantifying soiling rates in utility-scale PV powerplants endogenously, i.e., directly from the production data. Thetemperature corrected performance ratio, normalized to a cleanstate, is used to derive the soiling ratio (SR). Cleaning events, causedby either rain or manual cleaning, are automatically detected bypositive shifts in the running median of the SR time series. Soilingrates are then estimated by the rate of change of the SR betweenthe cleaning events, which is determined by linear regression. Themethod is validated on data from three utility-scale PV powerplants in the Middle East, yielding soiling rates that are in therange 0%–0.18%/day at least 50% of the time, with a median of 0.1%/day.