Estimation of Shade Losses in Unlabeled PV Data

TL;DR

This paper introduces a novel method to estimate shade-induced power losses in unlabeled PV system data, enabling analysis of small-scale distributed solar installations using a signal decomposition framework.

Contribution

It presents the first approach to quantify shade losses from unlabeled PV data, expanding analysis capabilities to small-scale, distributed systems.

Findings

First method to estimate shade losses in unlabeled PV data

Enables analysis of small-scale distributed PV systems

Uses signal decomposition framework for hidden component estimation

Abstract

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.