Large‐Scale Daylight Photoluminescence: Automated Photovoltaic Module Operating Point Detection and Performance Loss Assessment by Quantitative Signal Analysis

Abstract

Daylight photoluminescence is a relatively novel imaging technique utilized in photovoltaic system inspection, using the working principle of photoluminescence with the sun as excitation source. Filtering the luminescence signal from the strong sun irradiation is its main challenge. Images acquired at two different operating points of the module, namely at open circuit and at a high current state, allow subtraction of the background radiation while maintaining the luminescence signal. A daylight photoluminescence‐ready inverter, which is able to toggle between manually selectable operating points of connected photovoltaic modules is presented in this work. Synchronization of image acquisition and operating point switching becomes particularly challenging if the camera is applied to unmanned aerial vehicles. To overcome this challenge, an algorithm is developed to identify operating point switches in a set of images taken in the field by investigating the development of image intensities. Further, by working out the detailed dependencies of the signal recorded during daylight photoluminescence, the temperature coefficient of photoluminescence intensity is derived theoretically, and its impact on quantitative inspections. The potential field application of daylight photoluminescence images to identify performance loss in photovoltaic modules is investigated by two approaches: recording the signal intensity of images over time and comparing the signal intensity of different photovoltaic modules in one image. For both approaches, their hypothetical applicability is shown experimentally.This article is protected by copyright. All rights reserved.