Drone-Based Daylight Electroluminescence Imaging of PV Modules

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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
Title of host publicationProceedings of 46th IEEE Photovoltaic Specialist Conference
PublisherIEEE
Publication date2019
Publication statusPublished - 2019
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
SeriesIEEE Journal of Photovoltaics
ISSN2156-3381

Cite this

Benatto, G. A. D. R., Mantel, C., Spataru, S. V., Santamaria Lancia, A. A., Riedel, N., Thorsteinsson, S., ... Séra, D. (2019). Drone-Based Daylight Electroluminescence Imaging of PV Modules. In Proceedings of 46th IEEE Photovoltaic Specialist Conference IEEE. IEEE Journal of Photovoltaics
Benatto, Gisele Alves dos Reis ; Mantel, Claire ; Spataru, Sergiu Viorel ; Santamaria Lancia, Adrian Alejo ; Riedel, Nicholas ; Thorsteinsson, Sune ; Poulsen, Peter ; Parikh, Harsh Rajesh ; Forchhammer, Søren ; Séra, Dezso. / Drone-Based Daylight Electroluminescence Imaging of PV Modules. Proceedings of 46th IEEE Photovoltaic Specialist Conference. IEEE, 2019. (IEEE Journal of Photovoltaics).
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title = "Drone-Based Daylight Electroluminescence Imaging of PV Modules",
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.",
author = "Benatto, {Gisele Alves dos Reis} and Claire Mantel and Spataru, {Sergiu Viorel} and {Santamaria Lancia}, {Adrian Alejo} and Nicholas Riedel and Sune Thorsteinsson and Peter Poulsen and Parikh, {Harsh Rajesh} and S{\o}ren Forchhammer and Dezso S{\'e}ra",
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Benatto, GADR, Mantel, C, Spataru, SV, Santamaria Lancia, AA, Riedel, N, Thorsteinsson, S, Poulsen, P, Parikh, HR, Forchhammer, S & Séra, D 2019, Drone-Based Daylight Electroluminescence Imaging of PV Modules. in Proceedings of 46th IEEE Photovoltaic Specialist Conference. IEEE, IEEE Journal of Photovoltaics, 46th IEEE Photovoltaic Specialists Conference, Chicago, United States, 16/06/2019.

Drone-Based Daylight Electroluminescence Imaging of PV Modules. / Benatto, Gisele Alves dos Reis; Mantel, Claire; Spataru, Sergiu Viorel; Santamaria Lancia, Adrian Alejo; Riedel, Nicholas; Thorsteinsson, Sune; Poulsen, Peter; Parikh, Harsh Rajesh; Forchhammer, Søren; Séra, Dezso.

Proceedings of 46th IEEE Photovoltaic Specialist Conference. IEEE, 2019. (IEEE Journal of Photovoltaics).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

TY - GEN

T1 - Drone-Based Daylight Electroluminescence Imaging of PV Modules

AU - Benatto, Gisele Alves dos Reis

AU - Mantel, Claire

AU - Spataru, Sergiu Viorel

AU - Santamaria Lancia, Adrian Alejo

AU - Riedel, Nicholas

AU - Thorsteinsson, Sune

AU - Poulsen, Peter

AU - Parikh, Harsh Rajesh

AU - Forchhammer, Søren

AU - Séra, Dezso

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

M3 - Article in proceedings

T3 - IEEE Journal of Photovoltaics

BT - Proceedings of 46th IEEE Photovoltaic Specialist Conference

PB - IEEE

ER -

Benatto GADR, Mantel C, Spataru SV, Santamaria Lancia AA, Riedel N, Thorsteinsson S et al. Drone-Based Daylight Electroluminescence Imaging of PV Modules. In Proceedings of 46th IEEE Photovoltaic Specialist Conference. IEEE. 2019. (IEEE Journal of Photovoltaics).