Abstract
Analyses of performance loss rates in photovoltaic (PV) systems are not yet standardized, and are typically carried out by a linear regression of the evolution of a certain performance metric (e.g., performance ratio, yield, etc.) over time. In this article, we propose a novel methodology of advanced PV system performance loss rate modeling applying a self-regulated multistep algorithm. The developed algorithm automatically detects the number and positions of breakpoints in nonlinear performance time series and divides the performance trend into an adequate number of linear segments. Instead of calculating one linear performance loss rate, given in percentage per year, as is common practice, multiple linear performance loss values are determined, depending on the trend of the time series and subsequently the number of breakpoints. The algorithm is fully automated. We have applied our methodology on data of an experimental PV installation in Bolzano/Italy, which consists of 26 different PV systems. The overall linear performance loss rate of the facility’s crystalline silicon systems is between − 0.5 and − 1.3%/year, whereas the thin-film PV systems experience values between − 0.6 and − 2.4%/year. Based on our results, the algorithm appears to be stable and accurate. The methodology is to be used as a fast and automated check of PV systems in operation to detect anomalies affecting performance (in an early stage). By building up a large database of detected issues in the field this algorithm will enable us to better understand the performance evolution of different PV system types in varying climates.