Infrared Thermography for the Detection and Characterization of Photovoltaic Defects: Comparison between Illumination and Dark Conditions

Abstract

Newly installed renewable power capacity has been increasing incredibly in recent years. For example, in 2018, 181 GW were installed worldwide. In this scenario, in which photovoltaic (PV) energy plays a leading role, it is essential for main players involved in PV plants to be able to identify the failure modes in PV modules in order to reduce investment risk, to focus their maintenance efforts on preventing those failures and to improve longevity and performance of PV plants. Among the different systems for defects detection, conventional infrared thermography (IRT) is the fastest and least expensive technique. It can be applied in illumination and in dark conditions, both indoor and outdoor. These two methods can provide complementary results for the same kind of defects, which is analyzed and characterized in this research. Novel investigation in PV systems propose the use of a power inverter with bidirectional power flow capability for PV plants maintenance, which extremely facilitates the electroluminescence (EL) inspections, as well as the outdoor IRT in the fourth quadrant.

Using UAV to Detect Solar Module Fault Conditions of a Solar Power Farm with IR and Visual Image Analysis

“…Alsafasfeh, M., et al [2] yes yes Hwang, M.-H., et al [4] yes bypass diode Libra, M., et al [8] yes yes Niccolai, A., et al [9] yes digital map Vieira, R.G., et al [10] yes bypass diode Navid, Q., et al [11] yes Henry, C., et al [12] yes yes Pierdicca, R., et al [13] yes yes deep learning Jeong, H., et al [14] yes yes diagnosis Boulhidja, S., et al [15] yes Tsanakas, J.A., et al [16] yes yes Tsanakas, J.A., et al [17] yes Gallardo-Saavedra, S., et al [18] yes Ballestín-Fuertes, J., et al [19] EL 1 Herraiz, Á.H., et al [20] yes yes Fernández, A., et al [21] yes yes 1 Electroluminescence Technique.…”

Photovoltaic Panels Classification Using Isolated and Transfer Learned Deep Neural Models Using Infrared Thermographic Images

“…Generally, all defects are treated as faults in the system. However, defects such as bird drops, shadows, dust accommodation, etc., reduce the PV output by localised heating of the PV cell (hotspot formation) due to the operation in the reverse region and dissipating healthy cell current due to series connection [ 1 , 14 , 19 ]. If such issues remain undetected and persist on the PV surface, these issues result in permanent failure/faults of PV panels [ 20 ].…”

“…In addition, only a few defects are identifiable through naked eye/visual inspection, such as corrosion, burned and broken cells, bubbles, etc. [ 19 ]. Therefore, a fast, low-storage, and accurate identification system will ensure the safe operation of the PV system during its lifetime by the timely identification of hotspots/defects/faults in the PV system during its normal operation [ 22 ].…”

“…To prolong the performance of PV panels, an accurate and efficient approach to identify and classify PV panels because of defects is inevitable [ 1 , 11 ]. Generally, PV system health and defects are identified using two broad approaches: through electrical signal (voltage and current characteristics of PV panels) [ 16 , 17 , 18 ] and non-invasive image-based approaches, such as electroluminescence (EL) images [ 23 ], infrared (IR) thermography of PV panels [ 1 , 8 , 11 , 12 , 19 ], fluorescence images [ 24 ], photoluminescence images [ 25 ] etc. However, IR thermography of PV panels is widely used in the literature due to its speed, low cost, large-scale outdoor applications, user friendliness, and accuracy [ 8 , 11 , 12 , 19 ].…”

Defects Impact on PV System GHG Mitigation Potential and Climate Change

“…Some PV issues can be seen through the naked eye such as broken cells, burned cells, corrosion, etc. [16]. However, extensive analysis on PV panels condition/health monitoring for hotspots formation due to environmental issues is very much important specifically in large scale PV systems.…”