Drone-Based Daylight Electroluminescence Imaging of PV Modules

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Abstract

Electroluminescence (EL) imaging is a PV module characterization technique, which provides high accuracy in detecting defects and faults such as cracks, broken cells interconnections, shunts, among many others; furthermore, the EL technique is used extensively due to a high level of detail and direct relationship to injected carrier density. However, this technique is commonly practiced only indoors – or outdoors from dusk to dawn – because the crystalline silicon luminescence signal is several orders of magnitude lower than sunlight. This limits the potential of such a powerful technique to be used in utility scale inspections, and therefore the interest in the development of electrical biasing tools to make outdoor EL imaging truly fast and efficient. With the focus of quickly acquiring EL images in daylight, we present in this article a drone-based system capable of acquiring EL images at a framerate of 120 frames per second. In a single second during high irradiance conditions, this system can capture enough EL and background image pairs to create an EL PV module image that has sufficient diagnostic information to identify faults associated with power loss. The final EL images shown in this work reached representative quality SNRAVG of 4.6, obtained with algorithms developed in previous works. These drone-based EL images were acquired with global horizontal solar irradiance close to one sun in the plane of the array.
Original languageEnglish
JournalIEEE Journal of Photovoltaics
Volume10
Issue number3
Pages (from-to)872 - 877
ISSN2156-3381
DOIs
Publication statusPublished - 2020
Event46th IEEE Photovoltaic Specialists Conference - Chicago, United States
Duration: 16 Jun 201921 Jun 2019
Conference number: 46

Conference

Conference46th IEEE Photovoltaic Specialists Conference
Number46
CountryUnited States
CityChicago
Period16/06/201921/06/2019

Keywords

  • Electroluminescence
  • Imaging
  • Photovoltaic cells
  • Crystalline Silicon PV
  • Characterization of Defects in PV

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