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At least 145 records · Page 8

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DOE OSTI2021

Magnetic triggering — time-resolved characterisation of silicon strip modules in the presence of switching DC-DC converters

Modules for the ATLAS Inner Tracker (ITk) strip tracker include a DC-DC converter circuit glued directly to the silicon sensor which converts the 11 V supplied to the module to the 1.5 V required for the operation of the readout chips. The DC-DC converter unit, consisting of a copper solenoid and custom ASIC, is located directly above the silicon strip sensor and therefore needs to be shielded to protect the sensor from EMI noise created during the operation of the circuit. Despite dedicated shielding, consisting of an aluminium shield box with continuous solder seams encompassing the surface components and a copper layer in the PCB beneath it, module channels connected to sensor strips located beneath the converter circuit were found to show a noise increase. While the DC-DC converter unit causing the underlying EMI noise operates at a frequency of 2 MHz, module characterisation measurements for ITk strip tracker modules are typically performed asynchronously to the DC-DC switching and are therefore averaged over the full range of time bins with respect to the converter frequency. In order to investigate the time dependence of the noise injection relative to the DC-DC switching frequency, a dedicated setup to understand the time-resolved performance change in modules was developed. By using a magnetic field probe to measure the field leaking through the shield box and triggering on its rising edge, data taking could be synchronised with the DC-DC switching. This paper illustrates the concept and setup of such time-resolved performance measurements using magnetic triggering and presents results for the observed effects on signal and noise for ATLAS ITk strip modules from both laboratory and beam tests.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Motivation, benefits, and challenges for new photovoltaic material & module developments

Abstract In the last decade and longer, photovoltaic module manufacturers have experienced a rapidly growing market along with a dramatic decrease in module prices. Such cost pressures have resulted in a drive to develop and implement new module designs, which either increase performance and/or lifetime of the modules or decrease the cost to produce them. In this paper, the main motivations and benefits but also challenges for material innovations will be discussed. Many of these innovations include the use of new and novel materials in place of more conventional materials or designs. As a result, modules are being produced and sold without a long-term understanding about the performance and reliability of these new materials. This has led to unexpected new failure mechanisms occurring few years after deployment, such as potential induced degradation or backsheet cracking. None of these failure modes have been detected after the back then common single stress tests. New accelerated test approaches are based on a combination or sequence of multiple stressors that better reflect outdoor conditions. That allows for identification of new degradation modes linked to new module materials or module designs.

Oreski, G. (ORCID:0000000342239047)↗

DOE OSTI2022

Design and Implementation of Automated Characterization of T-type based Power Module for PV Inverter Reliability Assessment

Reliability of power electronics holds the key for future power and energy systems since it is essential for system integration with renewables and energy storage systems. Variation of power module characteristics over the converter’s operational lifetime is a critical indicator to assess its reliability. Device characterization consists of different steps to collect, process, and visualize results, which is usually time-consuming, especially for power modules based on a non-phase-leg configuration, such as T-type circuits, widely applied for PV inverters. To reduce the time, ensure repeatability, and guarantee consistency, an automated test bench can be helpful. This paper focuses on a T-type-based power module and proposes a unique characterization platform and corresponding automation procedure and implementation. Considering the major characterization difference between T-type power modules over the conventional phase-leg power module, first, the special consideration for static characterization is highlighted. Second, the unique dynamic characterization design associated with the T-type power module is described. Finally, the automation of the power module characterization and the test platform is presented along with results and special considerations.

Siraj, Ahmed↗

DOE OSTI2021

Multiscale Characterization of Photovoltaic Modules—Case Studies of Contact and Interconnect Degradation

The current popularity of photovoltaic (PV) systems is due in large part to their exceptional reliability and significantly lower cost than other energy sources. Studying cell and module degradation is key to promote further development in the state of the art. Fielded or accelerated aged modules exhibit different failure modes, of which metallization degradation (contacts and interconnections) is prevalent. In this work, we discuss how multiscale characterization methods can be applied to a variety of module technologies that have been field exposed and have undergone accelerated age testing. These methods include performing characterization on the module level, cell level, and finally the materials level. The observed performance losses from the module- and cell-level characterization can be correlated with materials properties to find out the root cause of degradation. We recommend an initial nondestructive characterization suite, including module- and cell-level current-voltage ( I--V ), Suns-V OC , photoluminescence and electroluminescence imaging, quantum efficiency, ultraviolet fluorescence imaging, and thermal infrared imaging. Samples are then extracted from particularly degraded regions of the module and prepared for materials characterization techniques, such as top-down and cross-sectional scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, secondary ion mass spectrometry, Raman spectroscopy, and transmission electron microscopy, allowing a deeper look into the mechanism behind the metallization degradation. This article serves as an instructional review to introduce the different multiscale characterization methods and how they can be effectively applied to perform PV degradation studies. Furthermore, we also share some of our examples and discuss the strengths, limitations, and best practices for each of the characterization techniques.

14 SOLAR ENERGY↗

DOE OSTI2024

Field Study of Nighttime Leakage Currents in Bifacial PV Modules: Correlation with Atmospheric Electric Field Data

Leakage currents measured on PV modules in the field originate from a potential difference between the modules' frame and the cells. They can be a relative indicator of Potential-Induced Degradation (PID) severity, especially when comparing the same module design in a different environment. As modules are not operating at night, no leakage current should be observed but our team has reported several events of nighttime leakage currents on bifacial PV modules. These events have been firstly observed during a thunderstorm that are characterized by strong atmospheric electrical field values. This lead us to believe that nighttime leakage currents could originate from the atmospheric electric charges. In this paper, we correlate nighttime leakage currents measured on bifacial PV modules with field mill data to identify the origin of nighttime leakage currents. Our results show that so far, no leakage currents at night occur when the atmospheric electric field is between 0 and 150–200 V/m (standard value for fair weather). As soon as the atmospheric electric field is out of this range, leakage currents are observed with or without rain involved. This suggests a transport of charged particles from the atmosphere to the modules' frame. A combination of heavy rain with strong atmospheric electric field results into high nighttime leakage currents with a magnitude up to 8 times higher than what observed during the day with -1500V applied. This is explained by an easier transport of the charged particles through the water droplets. Based on these results, leakage currents observed during the day might not be only due to the inherent potential difference between the frame and the cells depending on the atmospheric electric field activity. We believe that it should be taken into account in PID studies.

14 SOLAR ENERGY↗

DOE OSTI2023

Bifacial PV Module Energy Modeling Validation Study

The cost delta between monofacial and bifacial photovoltaic (PV) modules was decreasing in 2018 when this study was initially proposed, making bifacial modules an attractive offering. However, there were limited field studies available that could be considered utility-scale representative, and PV module manufacturers were stating large ranges for the expected energy yield improvements of bifacial technology. This generated uncertainties regarding bifacial performance gains and the actual LCOE (levelized cost of energy). There was also relatively low confidence in the industry’s energy modeling tools’ ability to accurately predict bifacial energy yield, meaning that early adopters of bifacial modules were not able to fully account for the increased energy yield in their energy and financial models. The intent of this project was to provide the solar industry with greater certainty on the energy yield gains of bifacial modules and provide higher confidence in the ability for different energy modeling software to model bifacial PV site performance. Achieving this would allow for bifacial technology to become bankable (i.e. accepted by Independent Engineers, site financiers and other PV site stakeholders), offering a step change in PV site performance that had not been seen since the widespread adoption of the single-axis tracker. Over the course of this study other economic factors including a significant tariff exemption for bifacial modules resulted in accelerated adoption of bifacial technology throughout the US utility scale solar segment. The number of early adopters increased rapidly, and with many investors accepting this module choice the question of bifacial bankability was seemingly answered faster than expected. However, PVEL’s study has still achieved significant accomplishments in demonstrating the accuracy of bifacial modeling across three different software platforms. The results of this study have shown that the mean biased error (MBE) between the field data and the predicted values from all three software platforms were aligned with a maximum MBE of 1.3% and a minimum MBE of -1.8%.

14 SOLAR ENERGY↗

DOE OSTI2024

Development of POTATO for 2S Module Grading for the CMS Phase-2 Outer Tracker Upgrade

Due to the High Luminosity-Large Hadron Collider (HL-LHC) upgrade, several detectors of the Compact Muon Solenoid (CMS) will need to be upgraded, specifically the new Outer Tracker detector that will be composed of 13,200 silicon modules. The Outer Tracker features two types of modules; the PS (pixel-strip) and the 2S (strip-strip) modules. With a large influx of production of modules, extensive testing is required to ensure they fulfill the performance requirements. This research introduces POTATO (Phase-II Outer Tracker Analyzer of Test Outputs), a specialized software developed in C++ to analyze, grade, and store results in a centralized database since module data will be collected from various international production facilities. The implementation of POTATO will facilitate the selection of the best performing modules for the Outer Tracker upgrade. This paper is focused on the implementation of the analysis of 2S Module results within POTATO.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

CFD modeling of high-flux plate-and-frame membrane modules for industrial carbon capture

In this work, we study the application of membrane-based separation systems for carbon capture, considering plate-and-frame membrane modules. The successful deployment of membrane CO2 capture system relies on high-performing membranes as well as effective membrane modules that can fully exploit the developed membranes. A plate-and-frame membrane module is especially attractive for CO2 capture from industrial flue gas due to its lower pressure drop compared to its counterparts such as spiral wound modules and hollow fiber modules. To design better plate-and-frame modules, we investigate their basic unit - a single membrane stack through a combination of computational modeling and experimental investigations. The modeling approach is based on Computational Fluid Dynamics (CFD) to represent a multiphysics problem, including the fluid flow and diffusion processes within a membrane module. We use experimental data collected under different operating conditions to validate the CFD model. Numerical results suggest a good agreement between experiments and model outputs for the CO2 recovery, CO2 mole fraction in the retentate and permeate, and stage-cut. The CFD model is able to predict accurately the flow behavior, providing valuable insights on the effects of fluid dynamics on mass transfer of CO2. We also carry out a sensitivity analysis to identify the effect of key parameters on the CO2 recovery and the CO2 purity of the outlet streams.

Dosso, Cheick↗

DOE OSTI2026

Investigation and Diagnosis of Faulty Data Channels in CMS Outer Tracker Module Testing

The High-Luminosity Large Hadron Collider (HL-LHC) is currently undergoing upgrades to improve its luminosity. In parallel, this requires an upgrade to the Compact Muon Solenoid (CMS)’s Outer Tracker, consisting of Pixel-Strip (PS) and Strip-Strip (2S) modules that can accurately track the path of charged particles originating from the collisions. It follows that such complex modules call for extensive testing, requiring a sophisticated Data Acquisition (DAQ) system that can perform specific tests to assess their performance. In addition, errors caused by the hardware of a given testing station, and its associated data channel, need to be accurately identified to guarantee proper testing of modules. We have developed a software extension to the Phase-II Outer Tracker Analyzer of Test Outputs (POTATO), which is a specialized software designed to analyze and grade all of the module tests through a centralized database. This extension categorizes and analyzes module test results by its station and data channel. Its analysis can be used to identify trends in grading that indicate issues in these channels’ grading process rather than in the individual modules. This poster shows our methodology and results for identifying faulty data channels. Using this extension, we can quickly diagnose and address problems in our DAQ system, ensuring proper evaluation corrections for each module.

Chen, Angus [Fermilab]↗

DOE OSTI2026

Investigation and Diagnosis of Faulty Data Channels in CMS Outer Tracker Module Testing

Chen, Angus [Fermilab]↗

DOE OSTI2023

The MOOSE fluid properties module

The fluid properties module in MOOSE~\cite{lindsay2022moose} serves a variety of fluid simulation applications based on MOOSE, including the MOOSE Navier Stokes module~\cite{moose_ns}, Pronghorn~\cite{pgh}, the MOOSE thermal hydraulics module, SAM~\cite{sam}, RELAP-7~\cite{relap7}, Sockeye~\cite{sockeye}, Pronghorn-subchannel~\cite{subchannel} and the MOOSE porous flow module~\cite{porous}. These applications are used to solve coarse mesh multi-dimensional thermal-hydraulics~\cite{pgh}, 1D systems analysis~\cite{sam,relap7} in nuclear reactor analysis, heat pipe modeling~\cite{sockeye} and porous flow simulations~\cite{porous} for underground gas storage and water seepage. The use of consistent fluid properties across fluid flow applications facilitates coupled flow simulations~\cite{anl_sam_pgh,osti_1889653}. Each application has historically driven the implementation of several fluid properties, which were later extended to be compatible with other applications. The unique diversity of applications of the module, due to its presence in MOOSE, has driven its expansion to new fluids, such as advanced nuclear reactor coolants and, more recently, arbitrary functions or tables-based property definitions, as detailed in section~\ref{content}, as well as numerous thermophysical properties and variable sets, as detailed in subsection~\ref{sec:prop}. The need for different discretizations of flow equations based on the compressibility of the fluid has motivated support for both primitive (pressure- and temperature-based) and conservative (internal energy- and specific volume-based) flow variables in the module. Thermodynamic relations are used to convert between these two formulations, as needed. The module serves a dual purpose of providing fluid properties for direct use in flow simulations and facilitating the implementation of user-specific fluid properties. Contributions of new properties for existing fluids or new fluids are strongly encouraged.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Engineering Perovskite Precursor Inks for Scalable Production of High‐Efficiency Perovskite Photovoltaic Modules

Abstract Blade coating of perovskite solar cells (PSCs) and modules has progressed considerably toward the industrial production of perovskite photovoltaics. Developing stable perovskite precursors is critical for achieving uniform coating over large areas. Here, the engineering of a perovskite precursor solution consisting of 2‐methoxyethanol (2‐Me) and 1,3‐dimethyl‐imidazolidinone (DMI) with superior intermediate phase stability that enables scalable production of efficient perovskite solar modules is reported. With this perovskite precursor solution, uniform and pinhole‐less perovskite film is deposited over a large area of > 100 cm 2 and higher‐efficiency PSCs and modules are obtained. The best‐performing unit cell and module with n‐i‐p configuration reach power conversion efficiencies of 23.4% and 20.1%, respectively. Additionally, a series of non‐destructive metrology methods, such as spectroscopic ellipsometry, hyperspectral photoluminescence, electroluminescence, and laser beam‐induced current mapping, are employed to assess and guide the development the blade‐coated perovskite modules. This results show that rational engineering of precursor inks for blade coating is promising for the scalable production of efficient perovskite solar modules.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗

DOE OSTI2022

Analysis of electrically conductive adhesives in shingled solar modules by X-ray imaging techniques

The failure mechanisms of electrically conductive adhesives (ECAs) in solar modules are difficult to study since the ECA layer is not easily accessible within the module package. In this work, we present two complementary imaging modalities—X-ray radiography and X-ray microcomputed tomography (XCT)—that reveal important morphological features of the ECA within a shingled module. X-ray radiography uses single X-ray projections to provide fast and non-destructive imaging of the shingled interconnection, illuminating the alignment of the ECA relative to the busbars, the size and shape of the ECA, and the presence of voids within it. Through X-ray radiography, we observed, for example, that the average void coverage area of ECA segments reduced from 36.7% to 4.4% when an ECA was cured for 60 s prior to module lamination. XCT is a three-dimensional imaging technique that can identify regions in which the ECA makes electrical contact to busbars on cells and regions in which the ECA has cracked, among other features. XCT can also be used to image the individual metal particles within ECA, from which the metal volume fraction of an ECA was found here to be 70.4%. This is a quantity that is not often reported by ECA manufacturers but is important to ensure isotropic conduction. As X-ray projections can be performed non-destructively on full modules, the technique may be used to pinpoint ECA failures in accelerated degradation testing. XCT is complementary and is suited to forensic analysis of failing modules.

14 SOLAR ENERGY↗

DOE OSTI2022

Automated defect identification in electroluminescence images of solar modules

Solar photovoltaic (PV) modules are susceptible to manufacturing defects, mishandling problems or extreme weather events that can limit energy production or cause early device failure. Trained professionals use electroluminescence (EL) images to identify defects in modules, however, field surveys or inline image acquisition can generate millions of EL images, which are infeasible to analyze by rote inspection. Here, we develop a rapid automatic computer vision pipeline (~0.5 seconds/module) to analyze EL images and identify defects including cracks, intra-cell defects, oxygen-induced defects, and solder disconnections. Defect identification is achieved with a machine learning model (Random Forest, ResNet models and YOLO) trained on 762 manually-labeled EL images of PV modules. We compare model performance on an imbalanced real-world validation set containing 134 EL images and determine that ResNet18 and YOLO are the optimal models; we next evaluated these models on a dedicated testing set (129 module images) with resulting macro F1 scores of 0.83 (ResNet18) and 0.78 (YOLO). Using a field EL survey of a PV power plant damaged in a vegetation fire, we analyze 18,954 EL images (2.4 million cells) and inspect the spatial distribution of defects on the solar modules. The results find increased frequency of ‘crack’, ‘solder’ and ‘intra-cell’ defects on the edges of the solar module closest to the ground after fire. We also find an abnormal increase of striation rings on cells which were assumed to be caused mainly in fabrication process. Our methods are published as open-source software. It can also be used to identify other kinds of defects or process different types of solar cells with minor modification on models by transfer learning.

14 SOLAR ENERGY↗

DOE OSTI2021

Packaging of an 8-kV Silicon Carbide Diode Module with Double-Side Cooling and Sintered-Silver Joints

Packaging innovations are needed for medium-voltage wide bandgap power semiconductor modules to enable their adaptation in grid applications. A unique challenge for packaging medium-voltage power modules is managing the trade-off between insulation demand and heat dissipation. The focus of this work was on developing a packaging innovation that improves the module heat dissipation and offers more flexibility to its insulation design. Two strategies were explored for the packaging of an 8-kV SiC diode rectifier module:(1) double-side cooling and (2) sintered-silver bonding. Double-side cooling was realized by using short metal posts rather than long and thin wire bonds for device interconnection, forming a low-profile package with devices sandwiched between two insulated metal substrates. Sintered-silver bonding enabled the devices to function reliably at over 250 °C. Simulations of the packaged module showed a low interconnect inductance of 2.67 nH and a 50% less heat transfer coefficient required to cool the chips. Prototypes of the module were fabricated, and preliminary electrical testing results validated the package design.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2021

Representative Modules for Accelerated Thermal Cycling and Static Load Testing

In this work, we explore the influence of module size on the rate of interconnect solder bond thermomechanical fatigue (TMF) damage and the probability of cell fracture. For the solder bond TMF damage evaluation, structural mechanics models of crystalline silicon PV models are created to solve with the Finite Element Method. For the probability of cell fracture evaluation, Weibull analysis and weakest link theory are employed to resolve the probability of crystalline silicon PV cell fracture when measured as bare cells and when stressed in reduced- and full-sized modules. Results conclusively demonstrate that the rate of solder bond TMF damage is independent of module size, interconnect location across the cell and cell location across the module and that smaller, representative, modules must be loaded to a much higher level than their parent full-sized modules to achieve an equivalent driving force for cell fracture.

accelerated testing↗

DOE OSTI2022

Fast External Quantum Efficiency Measurements of Photovoltaic Modules

The external quantum efficiency (EQE) or associated spectral response is widely used to evaluate the performance of photovoltaics, light emitting diodes, photodetectors, photodiodes, semiconductor lasers, laser-induced refrigeration of solids etc. For photovoltaic (PV) devices, The EQE is used to determine the spectral mismatch correction that is used to convert a performance measurement from a non-ideal simulator spectrum to a standard spectrum in PV device calibrations. Moreover, EQE can provide important insight into the physics of a PV device. For instance, the EQE shape can be used to infer mechanisms limiting the performance of the device. However, EQE measurements of full-size PV modules remain a challenge in the PV community due to rare availability of reliable module QE measurement tools worldwide and the size and complexity of module architecture that comprises several cells connected in strings (series or/and parallel). Here, we use a customized nondestructive tool made of high-power light emitting diodes to perform high-throughput EQE measurements on PV modules. Circuit simulations show that the measurement system can safely be used to measure both crystalline silicon and thin film-based PV modules with series connected cells without the risk of damage through reverse bias. In addition, EQE mapping combined with electroluminescence show a strong correlation and provide a way to determine both spatial non-uniformity of the spectral response and defects/degradation effects across the module.

PV module↗