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Davis, Kristopher O.

Publications and source records attributed to Davis, Kristopher O..

Photon management in silicon photovoltaic cells: A critical review

With the practical efficiency of the silicon photovoltaic (PV) cell approaching its theoretical limit, pushing conversion efficiencies even higher now relies on reducing every type of power loss that can occur within the device. Limiting optical losses is therefore critical and requires effective management of incident photons in terms of how they interact with the device. Ultimately, photon management within a PV cell means engineering the device and constituent materials to maximize photon absorption within the active semiconductor and therefore reduce the number of photons lost through other means, most notably reflection and parasitic absorption. There have been great advancements in the front and the rear side photon management techniques in recent years. This review aims to discuss these advancements and compare the various approaches, not only in terms of increases in photogenerated current, but also their compatibility with different PV cell architectures and potential trade-offs, like increased surface recombination or scalability for high-volume manufacturing. In this review, a comprehensive discussion of a wide variety of the front and the rear side photon management structures are presented with suggestions to improve the already achieved performance further. Here, this review is unique because it not only presents the recent development in photon management techniques, but also offers through analysis of these techniques and pathways to improve further.

14 SOLAR ENERGY↗

Degradation-related defect level in weathered silicon heterojunction modules characterized by deep level transient spectroscopy

Commercial silicon heterojunction photovoltaic modules, known as amorphous-silicon-based heterojunction with intrinsic thin-film layer (HIT) modules, show average degradation after 10 years in the field. HIT modules weathered outdoors in Colorado and Florida display mostly uniform decreases in intensity when mapped with photoluminescence (PL) imaging compared to a control module. Flash-table-based current-voltage curves show that degradation is dominated by voltage loss. Samples are cored from each of the modules, and deep level transient spectroscopy (DLTS) detects three electron-trap defect states in all modules with activation energies of electron emission from the defects of 0.07, 0.16, and 0.50 eV. DLTS measurements on the weathered modules show an additional deep-level, electron-trap defect state with an activation energy of 0.51 eV and a trap density of approximately 10 12 cm –3 . The capture rate is measured using varying short filling pulse times, and the resulting capture cross section is estimated to be 1.1x10 –16 cm 2 . The development of the weathering-related defect level correlates to decreases in carrier lifetime, PL intensity, and module voltage. Various depths of the space charge region are probed with increments in applied reverse bias and filling-pulse bias. Furthermore, this DLTS depth profiling shows a trend of trap density increasing with less applied reverse bias, suggesting that the weathering-related defect increases carrier recombination toward the interface between the bulk silicon wafer and the junction-forming amorphous-silicon passivation layers.

14 SOLAR ENERGY↗

Field studies of PERC and Al-BSF PV module performance loss using power and I-V timeseries

We have studied the degradation of both full-sized modules and minimodules with PERC and Al-BSF cell variations in fields while considering packaging strategies. We demonstrate the implementations of data-driven tools to analyze large numbers of modules and volumes of timeseries data to obtain the performance loss and degradation pathways. This data analysis pipeline enables quantitative comparison and ranking of module variations, as well as mapping and deeper understanding of degradation mechanisms. The best performing module is a half-cell PERC, which shows a performance loss rate ( PLR ) of −0.27 ± 0.12% per annum (%/ a ) after initial losses have stabilized. Minimodule studies showed inconsistent performance rankings due to significant power loss contributions via series resistance, however, recombination losses remained stable. Overall, PERC cell variations outperform or are not distinguishable from Al-BSF cell variations.

Curran, Alan J.↗

Degradation of Monocrystalline Silicon Photovoltaic Modules From a 10-Year-Old Rooftop System in Florida

A system of 180 monocrystalline aluminum back-surface field modules were installed in Cocoa, Florida, for 10 years. In total, 156 modules are characterized and compared to 3 controls. Power degradation rates vary between – 0.14% to – 3.22% per year, with median and average rates of –0.92% and –1.05% per year, respectively. The losses are primarily resistive with minor optical and recombination loss contributions. Electroluminescence imaging shows a characteristic pattern, which is shown to be resistive in nature when compared to photoluminescence. Resistive losses are due to corrosion of the rear contact Ag/solder interface and, to a much lesser degree, gridline Ag oxidation. Moisture ingress through the backsheet is likely responsible for mediating corrosion. Optical losses are due mostly to a combination of antireflection coating degradation, minor encapsulant browning, and delamination. Minor front contact corrosion may contribute to recombination. Furthermore, this study expands upon previous work on this vintage of the module by examining a large sample set, comprehensive characterization including techniques not previously used on these modules, and a comparison between two other systems of different climates.

14 SOLAR ENERGY↗

Impact of acetic acid exposure on metal contact degradation of different crystalline silicon solar cell technologies

Degradation due to acetic acid in photovoltaic (PV) modules has been a commonly observed phenomenon for both damp-heat exposure and outdoor operations. Acetic acid is a degradation byproduct of ethylene-vinyl acetate (EVA), a common module encapsulant. To address this issue, robust metallization pastes and cell technologies are being developed. However, it is important to assess how these technologies perform in an acetic acid environment and withstand degradation before they are implemented in the solar market. In this work, we investigate the impact of acetic acid exposure on four different cell groups: monofacial passivated emitter and rear contact (PERC) cells with advanced telluride-based front contact pastes, bifacial PERC cells with novel aluminum rear contact pastes, bifacial tunnel oxide passivated contacts (TOPCon) cells, and silicon heterojunction (SHJ) cells. These cells were exposed to acetic acid for different time increments. The recombination losses were characterized by Suns-VOC, and multi-variate regression analysis of intensity-dependent photoluminescence (PL) images with Griddler AI. Resistive losses were tracked with the transmission line method (TLM). Samples showing severe performance degradation were selected for further materials characterization to understand the root cause. Top-down and cross-sectional scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS) were performed to investigate the change in materials properties. Our study shows that the front contacts of the bifacial TOPCon cells and monofacial PERC cells were significantly affected by acetic acid exposure. Here, the SHJ cells were found to be the most stable.

14 SOLAR ENERGY↗

Characterization of Contact Degradation in Crystalline Silicon Photovoltaic Modules (Final Technical Report)

In this project, the aim was to develop highly-automated metrology methods that can provide more insights into degradation and failure, while still relying on the types of measurements the PV industry and RD communities are comfortable with (e.g., I – V and EL). In particular, our focus was to develop techniques to better understand contact and interconnect degradation in crystalline silicon (c-Si) PV modules and apply those techniques to conventional and emerging c-Si cell architectures and cell interconnection technologies.

14 SOLAR ENERGY↗

Electroluminescence Analysis and Grading of Hail Damaged Solar Panels

We analyzed more than 4000 electroluminescence images of hail damaged solar panels from a cluster of houses in Texas. We enhanced the images for ease of analysis and classified the defects within each solar cell into categories of glass breakage, installer damage, inactive substrings, crack severity, interconnect wire problems, and whether the damage was likely caused by hail. From these statistics, we quantified each panel into five levels of hail damage for insurance claims, and four levels of overall quality for potential resale pricing. Here, we share here some statistics regarding the defects with the hope that the data is useful to others attempting to predict the invisible damage to systems based just on the easily observable glass breakage statistics.

14 SOLAR ENERGY↗

Cell dark current–voltage from non-calibrated module electroluminescence image analysis

Here, we present a fast, accurate, and reliable method of obtaining cell dark current–voltage (I–V) curves from module electroluminescence (EL) images without requiring calibration or correction. For a pristine module, EL-derived dark I–V are compared to directly probed data for a variety of changing imaging parameters: camera sensor, lens, filter, aperture width, exposure time (level of sensor saturation), number of images used, and various combinations of these. Pristine modules and those experiencing different modes and degrees of degradation are examined. A recent study of modules using five different cell technologies demonstrates the practicality of our “EL sweep” technique for performance and degradation studies.

14 SOLAR ENERGY↗

Degradation of Edge-Defined Film-Fed Silicon Glass–Glass Modules on Florida Rooftop After 22 Years

Thin silicon (< 100 μm) adoption can provide significantly lower cost. Kerfless technologies provide thin wafers while preventing material from being wasted. Understanding how this family of processing influences module reliability is important. A set of four edge-defined film-fed growth (EFG) silicon modules from a ten-module system in Florida is measured after 22 years of exposure. Power loss rates of 0.58–0.78% year -1 are measured for three modules, while a rate of 1.32% is measured for a module with severe delamination and corrosion. Short-circuit current degrades between 10.7% and 13.1% for all modules. Further, the losses are primarily optical and recombination based; however, series and shunt resistance effects play a non-negligible role. Pre-existing recombination losses exist but are exacerbated via degradation. Optical losses in short-circuit current are due in part to encapsulant yellowing. Electroluminescence (EL) images display the effects of processing on bulk quality by clearly showing lines of alternating brightness along the wafer length. To the authors’ knowledge, this is the first article displaying suns–V OC data, effective lifetime versus excess carrier density data, and module EL images for EFG silicon-based modules.

36 MATERIALS SCIENCE↗

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Many of these power plants have spatiotemporal coherence that can be utilized for improving model accuracy. We have demonstrated in this paper the FAIRification of spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. Going further, we have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. To solve the issue of data missingness, we propose the use of St-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗

Diffraction and thermal effect of a Bessel-Gaussian laser for Ag nanoparticle deposition

Nanoparticles are known to sinter at much lower temperatures than the corresponding bulk or micro size particles. A laser-assisted sintering process is considered in this study to sinter Ag nanoparticles by dispensing Ag paste onto an indium tin oxide-coated Si substrate. The Gaussian beam of a CO 2 laser source is propagated through axicon and biconvex lenses, and the resulting hollow beam is focused on the Ag paste with a hollow parabolic mirror. A Bessel-Gaussian irradiance distribution is obtained at the focal plane of the parabolic mirror due to the interference of the hollow laser cone. The Fresnel diffraction approximation is considered to determine the phasor of the laser and an analytical approach is implemented to calculate the irradiance distribution of the Bessel-Gaussian beam. This irradiance distribution is utilized as a heat source in a heat conduction model and the temperature distribution is analyzed for thin Ag films formed during the laser sintering of Ag nanoparticles. An analytical expression is obtained for the temperature distribution by solving the heat conduction equation using Fourier transform for finite media. The widths of the deposited Ag lines are predicted from the temperature profiles and the model predictions compare well with the experimental results. The isotherms are found to be geometrically noncongruent with convex and concave tips depending on the locally maximum and minimum irradiances of the Bessel-Gaussian beam, respectively. The convex and concave tips, however, appear in the same isotherm for sufficiently high substrate speed relative to the laser beam.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Microdroplet Electrospray Localized Laser Printing and Sintering of Nanoparticles for Passivating, Carrier-Selective Contacts (Final Technical Report)

In this project, the team used a nanoparticle electrospray laser deposition (NELD) process developed at the University of Central Florida (UCF) to address current limitations of passivating, carrier-selective contact technologies for crystalline silicon (c-Si) photovoltaic (PV) cells. The NELD process was used to print low bulk line resistivity Ag contacts directly onto transparent conductive oxides (TCOs), like indium tin oxide (ITO), for hydrogenated amorphous silicon (a-Si:H) based c-Si heterojunction (SHJ) cells without any subsequent contact firing step needed.

14 SOLAR ENERGY↗

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗