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This public dataset contains electroluminescence images of solar cells and crack annotations, which can be used for developing semantic segmentation model to detect cracks in solar modules.
The solar photovoltaic (PV) industry often experiences module damage during transportation. PV modules stacked horizontally and strapped on wooden pallets may develop failures impacting their efficiency (glass shattering, cracks, frame indentation, etc.), especially when modules are not packed by professionals. The appearance of failures during the shipment from one laboratory to another can be detrimental to research studies. In this study, we tested a reusable plastic pallet designed to ship modules vertically. Five technologies of commercial PV modules were shipped together from Arizona to Florida including: glass/glass bifacial modules (framed and frameless), glass/transparent backsheet bifacial modules and glass/white backsheet modules (framed). Each module technology has a different physical size. Some modules had pre-existing cell-cracks allowing for the study of cell-crack formation and propagation during shipment. Dark current-voltage (I-V), light I-V and electroluminescence characterization were performed before and after shipment. A datalogger was used to monitor shocks and ambient temperature throughout the shipment and identify when the modules were more susceptible to damage. The modules were tilted upon receipt and the pallet were damaged but with no shattered modules. Time series shock data provided by the datalogger were used to determine potential responsible events. Our results reveal a few new post-transportation cracks for some modules. Modules parameters before and after shipment are also compared regarding the module constructions and their position in the pallet.
Polycrystalline thin-film solar cells have reached a levelized cost of energy that is competitive with all other sources of electricity. The technology has significantly improved in recent years, with laboratory cell efficiencies for cadmium telluride (CdTe), perovskites, and copper indium gallium diselenide (CIGS) each exceeding 22 percent. Both CdTe and CIGS solar panels are now produced at the gigawatt scale. However, there are ongoing challenges, including the continued need to improve performance and stability while reducing cost. Advancing polycrystalline solar cell technology demands an in-depth understanding of efficiency, scaling, and degradation mechanisms, which requires sophisticated characterization methods. These methods will enable reseachers and manufacturers to improve future solar modules and systems. This work provides researchers with a concise overview of the status of thin-film solar cell technology and characterization. Chapters describe material systems and their properties and then provide an in-depth look at relevant characterization methods and the learning facilitated by each of these. Following an introductory chapter, the book provides systematic and thorough coverage of the following topics: trends to improve CdTe solar cell performance; Cu(In,Ga)Se2 and related materials; perovskite solar cells; photovoltaic device modelling; luminescence and thermal imaging of thin-film photovoltaic materials, devices, and modules; application of spatially resolved spectroscopy characterization techniques on Cu2ZnSnSe4 solar cells; time-resolved photoluminescence characterization of polycrystalline thin-film solar cells; fundamentals of electrical material and device spectroscopies applied to thin-film polycrystalline chalcogenide solar cells; nanometer-scale characterization of thin-film solar cells by atomic force microscopy-based electrical probes; scanning transmission electron microscopy characterization of solar cells; photoelectron spectroscopy methods in solar cell research; time-of-flight secondary-ion mass spectrometry and atom probe tomography; and solid-state nuclear magnetic resonance characterization for photovoltaic applications. The final chapter provides an overview and describes future prospects.
Individual photovoltaic (PV) module health monitoring can be a daunting task for operation and maintenance of solar farms. Modules can be inspected through luminescence, thermal imaging, and current–voltage (I–V) curve analyzes for identification of damage and power loss. I–V curves provide easily interpretable data to determine module health as they directly provide electrical performance metrics. However, in order to obtain these curves, modules must be disconnected from the array and either removed to a solar simulator or characterized in situ with corrections for module temperature, the incident solar spectrum, and intensity. Luminescence or thermal images of a module are relatively easy to acquire in situ. Electroluminescence (EL) images highlight physical defects in the modules but do not provide easily interpretable features to correlate with electrical performance. This work presents a SWin transformer network to predict I–V curves for PV modules from their corresponding EL images. The predicted I–V curves allow the accurate prediction of the maximum power point (MPP), short-circuit current I sc , and open-circuit voltage V oc with a mean error less of than 1%. Comparing single diode model (SDM) parameters extracted from the predicted curves to those extracted from the true curves, the series resistance R s demonstrates a mean error of 5.19%, and the photocurrent I a mean error of 0.197%. The shunt resistance R sh and dark current Io parameters are predicted with larger errors because of their sensitivity to small changes in the I–V curve.
Temperature and solar irradiance are among the most relevant parameters that affect the energy yield of photovoltaic cells and modules. A rise in the module temperature leads to a significant decrease in the open circuit voltage and a small increase in the short circuit current. Here we use a new tool to determine temperature coefficients as well as to assess power rating of multi c-Si, mono c-Si, CdTe, and CIGS-based PV modules in controlled indoor conditions per IEC 60891 and IEC 61853-1. We use the tool to explore how nonuniformities in module temperature affect the accuracy of the temperature coefficients.
A vanadium dioxide (VO 2 ) based solid-to-solid phased changing material has been attracting great interest in smart window applications. However, achieving high solar modulation and high transparency simultaneously in visible light is the major challenge for the practical application of this smart material. To resolve this issue, in this paper, a smart film composed of a VO 2 nanoparticle matrix and a patterned VO 2 film is presented. Furthermore, numerical modeling and electromagnetic simulation are carried out to characterize the performance in terms of solar modulation and luminous transmittance, and a parametric study is carried out to optimize the proposed smart window film. Compared with the VO 2 nanoparticle matrix, the proposed structure can obtain 23% solar modulation and 57% luminous transmittance but with a much thinner thickness, which will significantly reduce the cost and fabrication complexity and extend the environment stability.
The accumulation of soiling on photovoltaic modules and on the mirrors of concentrating solar power systems causes non-negligible energy losses with economic consequences. These challenges can be mitigated, or even prevented, through appropriate actions if the magnitude of soiling is known. Particle counting analysis is a common procedure to characterize soiling, as it can be easily performed on micrographs of glass coupons or solar devices that have been exposed to the environment. Particle counting does not, however, yield invariant results across institutions. The particle size distribution analysis is affected by the operator of the image analysis software and the methodology utilized. The results of a round-robin study are presented in this work to explore and elucidate the uncertainty related to particle counting and its effect on the characterization of the soiling of glass surfaces used in solar energy conversion systems. An international group of soiling experts analyzed the same 8 micrographs using the same open-source ImageJ software package. The variation in the particle analyses results were investigated to identify specimen characteristics with the lowest coefficient of variation (CV) and the least uncertainty among the various operators. The mean particle diameter showed the lowest CV among the investigated characteristics, whereas the number of particles exhibited the largest CV. Additional parameters, such as the fractional area coverage by particles and parameters related to the distribution's shape yielded intermediate CV values. These results can provide insights on the magnitude inter-lab variability and uncertainty for optical and microscope-based soiling monitoring and characterization.
Shading and daylighting systems affect cooling, heating, and lighting energy use by modulating solar radiation through the building façade. Characterizing shading systems holistically and accurately helps designers and engineers evaluate shading systems to achieve energy and non-energy performance goals. These complex fenestration systems can be modeled using Bidirectional Scattering Distribution Functions (BSDF), which map incident radiation to hemispherical distributions of outgoing radiation. Data-driven, tabulated BSDFs are derived from interpolated goniophotometer measured data, then sampled during the raytracing calculation. A peak extraction (PE) algorithm was developed to circumvent limits in BSDF angular resolution, where the specular peak is extracted during simulation by evaluating the BSDF in the through direction and surrounding region. The objective of this study was to validate this measurement and modeling workflow using field monitored data from a full scale testbed with eleven installed fabrics of different weaves, openness factors, and colors and assess the accuracy of the workflow under different adaptation and contrast conditions. Test conditions were limited to clear sky conditions with the sun in the field of view. Results showed that, for tensor tree datasets, vertical illuminance, solar luminance (2.5° apex), and daylight glare probability (DGP) were predicted to within a mean bias error (MBE) error of -456 lx (-12.3%), -3.46e5 (-38.4%), and -0.042 (-7.8%) when full PE occurred. With a binary classification of glare/ no glare, DGP was predicted accurately with a true positive rate of 0.98 and true negative rate of 1.0 using tensor tree data and less accurately with Klems BSDF data, particularly for cases of no glare. The workflow may be of insufficient accuracy to distinguish borderline performance between fabrics using the four-point glare scale, particularly under low adaptation, high contrast daylit conditions. Errors were due to reductions in peak shape and intensity across the BSDF interpolation and data reduction workflow. Future work is needed to better preserve measurement fidelity during interpolation and sampling, which in turn will improve PE performance.
This project is motivated by the need to develop a materials engineering solution to reduce solar module degradation caused by cell cracks. The cell-crack-induced power loss is a long-term degradation mechanism and one of the main causes of solar panel field failures. Cell cracks can occur during module fabrication, transportation, installation, and long-term operation due to thermomechanical stressors. Our team’s internal estimation – based on the national weather pattern, frequency of severe weather, and 39- GW asset survey by Heliolytics – reveals that the cell-crack-induced module degradation translates to lost revenues >$17B over an average 5-year period for solar farm owners and to reduced reliability (<25 years panel lifetime) for solar energy consumers. In response to this challenge, the prime recipient offers a metal matrix composite (MMC) silver paste that is tailor-engineered for screen-printing gridlines and busbars, which serve as the electrical contacts on solar cells. We formulate our MMC paste by adding low-cost (∼0.02¢/WDC for research grade), surface-engineered carbon nanotubes to commercially available silver paste. The MMC paste offers a drop-in, cost-effective solution to cell cracks for solar cell and module manufacturers. The main goal of this project was to conduct field-relevant, module-level analysis and qualification of MMC metallization.
Electroluminescence (EL) imaging is a powerful tool used to identify defects in photovoltaic solar cells. Typically, this type of characterization is performed in the dark using a current injection that equals short-circuit current measured at standard test conditions (STC). Restricting imaging to such a temperature range limits the information obtained about the module and cells. However, it is not trivial to develop a tool that would allow for EL imaging to be performed under a wider range of temperatures. Here we demonstrate an in situ EL imaging capability developed within an environmental chamber that allows for control of sample temperatures between –40 and 90 °C. Additionally, we demonstrate EL imaging of 4-cell mini-modules (MiMo) under front-side mechanical loading. A Raspberry Pi-connected camera with short-pass filter removed is used for EL imaging. The camera is low-cost with a small form-factor, appropriate for use in a harsh, enclosed environment. The camera is installed within a thermally isolating housing mounted within the environmental chamber. Three example cases are given for MiMos that exhibit various forms of degradation including solder fatigue and cell cracking. It is shown that by measuring at conditions above and below STC, different behaviors may be identified. In some cases, restricting characterization to STC may lead to a failure to detect damage existing in the sample.
In this project, we aim to develop Modulation Photothermal Radiometry (MPR), which is an attractive non-contact tool to evaluate thermophysical properties of high-temperature solids and HTFs that are otherwise time-consuming and difficult to measure and for in-situ testing of these properties. Therefore, the main objective of the project is the development and application of MPR to characterize high temperature thermophysical properties of heat transfer fluids (HTFs) and the solids (tubing and solar absorbing coating) in various components and sub-systems used in CSP plants. The measurements will be first demonstrated on a wide range of materials at UCSD and then the tool will be transferred to other facilities within the Gen3 CSP portfolio.
This award aims to increase the lifetime of c-Si modules by lowering the power degradation rate to the goal of 0.2 %/year, while also increasing the harvested irradiance per module using bifacial cells to achieve the 2030 SunShot goal of $0.03/kWh. Increasing the durability and lifetime of modules requires improved module packaging material choices and module architectures to exploit new cell improvements. Bifacial PERC cells (with backside aluminum fingers) are becoming a primary PV technology due to their decreased rear surface recombination and increased light absorption compared to traditional monofacial Al-BSF cells. Bifacial modules with double glass architectures have been deployed to capture the rear-side irradiance thereby increasing the light captured. The choice of a double glass (DG) or glass/backsheet (GB) module leads to two very different chemical (e.g., O 2 , H 2 O) and mechanical environments (e.g., mechanical stress levels) inside the PV module that impact the cell’s operational conditions. The recipient will fabricate 4-cell DG and GB minimodules with various module architectures or constructions (mono- & bifacial cells, transparent & white encapsulants), and conduct stepwise accelerated exposures and characterization.
A solar module is often exposed to a variety of intensity and uniformity illumination conditions throughout a day. In the field, objects or dirt can block light from hitting the module creating a partial shading event. When a partial shading event occurs the module power point tracking system will typically push the shaded cells into reverse bias in order to avoid the current loss from the other series connected illuminated cells. When perovskite solar cells are operated in reverse bias, electrochemical reactions can occur, leading to both reversible and irreversible performance losses. Excess holes generated by reverse bias cause and push the oxidation reaction of halide ions from the lattice to neutral halogen interstitial. Small interstitial halogen atoms can diffuse across the device and potentially move from the perovskite layer and into the transport layers, shifting the fermi levels in the devices. In this investigation we utilize cross-sectional kelvin probe atomic force microscopy to map the band energetics of perovskite solar cells during reverse bias. We observe a 150 meV decrease in the work function of the C 60 . This leads to a decrease of 150 mV and 4 mA/cm 2 in V oc and in J sc respectively. Finally, we discuss methods to prevent this irreversible degradation after a perovskite device is held under reverse bias.
Cell cracks in PV modules caused by poor handling during shipping and installation as well as from extreme weather events can lead to gradual or immediate power degradation. To directly address cell-crack-induced degradation, we have formulated a carbon nanotube additive for commercial screen printed silver pastes. We have shown in previous work that these metal matrix composites have little to no effect on the cell's efficiency while enhancing the metallization's fracture toughness and electrical gap-bridging capability. In this work, we focus on translating materials level characterization techniques to module level degradation. We found that we get conflicting results from two different methods of measuring the metallization's ability to electrically bridge gaps in cracked solar cells. Mini-module stress testing is currently underway to determine which materials characterization correlates well with the min-module degradation characteristics.
Antireflective coatings (ARCs) are used on the vast majority of solar photovoltaic (PV) modules to increase power production. However, ARC longevity can vary from less than 1 to over 15 years depending on coating quality and deployment conditions. A technique that can quantify ARC degradation nondestructively on commercial modules would be useful both for in-field diagnostics and accelerated aging tests. In this article, we demonstrate that accurate measurements of ARC spectral reflectance can be performed using a modified commercially available integrating-sphere probe. The measurement is fast, accurate, nondestructive, and can be performed outdoors in full-sun conditions. We develop an interferometric model that estimates coating porosity, thickness, and fractional area coverage from the measured reflectance spectrum for a uniform single-layer coating. We demonstrate the measurement outdoors on an active PV installation, identify the presence of an ARC, and estimate the properties of the coating.
Here, we report the design, fabrication and outdoor characterization of a tandem luminescent solar concentrator/Si multi-junction photovoltaic module. Our tandem LSC/Si device consists of an InGaP LSC functioning as a top cell and a passivated contact Si bottom cell. The LSC comprises of an InGaP microcell array coupled to a polymer waveguide, loaded with CdSe/CdS core-shell quantum dot luminophores. The light trapping efficiency of the LSC waveguide is enhanced by encapsulation with photoluminescence trapping mirrors consisting of dielectric multilayer thin films. We demonstrate the performance of the LSC/Si device through a series of outdoor tests under various irradiance conditions conducted at the National Renewable Energy Laboratory. We report the first outdoor testing data of an LSC/Si tandem module, displaying maintained performance across varied diffusivity conditions for the LSC component. Finally, we model the tandem module performance using a ray optic simulation-based multiphysics model and forecast a pathway for high efficiency tandem LSC/Si module performance.
The development of perovskite solar cells (PSCs) has ushered in a new era of solar technology, characterized by its exceptional efficiency and cost-effective production. However, the soft and fragile nature of perovskites makes module encapsulation challenging. Polyolefin elastomers (POEs) have been reported to be promising encapsulants for perovskite modules. However, little research exists on identifying criteria among different types of POEs as encapsulants. Here, two POEs with different morphologies were compared as encapsulants. The first POE crystallizes during encapsulation (crystal content ∼40%), and the resulting shrinkage or warpage leads to delamination, causing minimodule failure. In contrast, perovskite minimodules encapsulated with a mostly amorphous POE exhibited better reliability and reproducibility. The best perovskite minimodules passed the thermal cycling test for 240 cycles between −40 and 85 °C and the damp heat test for 1419 h, according to the IEC 61215 standard. This study highlights the importance of the morphology of encapsulants in achieving high-quality encapsulation. Published by the American Physical Society 2024
This work is to be conducted in support of the American Made Challenges Solar Prize. The intent is to connect competitor teams with national laboratories that can help accelerate the development of innovative solutions and products. Teams who have won the Set! and Go! Contests are eligible to utilize vouchers at national laboratories to advance their ideas. Laboratory and field characterization of the electrical response of modules containing Configurable Current Cells (C3) under non-optimal conditions such as shading.