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We provide a methodology for estimating the losses due to shade in powergeneration data sets produced by real-world photovoltaic (PV) systems. We focusthis work on estimating shade loss from data that are unlabeled, i.e. powermeasurements with time stamps but no other information such as siteconfiguration or meteorological data. This approach enables, for the firsttime, the analysis of data generated by small scale, distributed PV systems,which do not have the data quality or richness of large, utility-scale PVsystems or research-grade installations. This work is an application of thenewly published signal decomposition (SD) framework, which provides anextensible approach for estimating hidden components in time-series data.

Estimation of Shade Losses in Unlabeled PV Data