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