Drone-Based Daylight Electroluminescence Imaging of PV Modules
| Autor: | Nicholas Riedel, Soren Forchhammer, Dezso Sera, Claire Mantel, Adrian Alejo Santamaria Lancia, Sergiu Spataru, Peter Behrensdorff Poulsen, Gisele Alves dos Reis Benatto, Harsh Parikh, Sune Thorsteinsson |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
Photovoltaic cells Photovoltaic system Characterization of Defects in PV Condensed Matter Physics Frame rate Solar irradiance Signal Imaging Electronic Optical and Magnetic Materials Electroluminescence Electronic engineering Daylight SDG 7 - Affordable and Clean Energy Crystalline silicon Electrical and Electronic Engineering Focus (optics) Crystalline Silicon PV Level of detail |
| Zdroj: | Benatto, G A D R, Mantel, C, Spataru, S V, Santamaria Lancia, A A, Riedel, N, Thorsteinsson, S, Poulsen, P, Parikh, H R, Forchhammer, S & Séra, D 2020, ' Drone-Based Daylight Electroluminescence Imaging of PV Modules ', IEEE Journal of Photovoltaics, vol. 10, no. 3, pp. 872-877 . https://doi.org/10.1109/JPHOTOV.2020.2978068 |
| ISSN: | 2156-3403 2156-3381 |
| DOI: | 10.1109/jphotov.2020.2978068 |
| Popis: | Electroluminescence (EL) imaging is a photovoltaic (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 frame rate 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. |
| Databáze: | OpenAIRE |
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