Protecting Perovskite Solar Cells against Moisture-Induced Degradation with Sputtered Inorganic Barrier Layers
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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DuraMAT FY24 Annual Report: Five Results to Help America's Photovoltaic Industry
The Durable Module Materials Consortium's overarching goal is to understand photovoltaic (PV) module degradation and enable high-energy-yield modules with a 50-year lifespan. One of DuraMAT's milestones this year was to identify cases where the whole of DuraMAT really mattered and made an impact that was greater than the sum of the project results. We identified five key results that demonstrate progress toward enabling 50-year modules for a resilient PV industry: 1) Resilient PV Systems; 2) Proactive Materials Screening; 3) Understanding Wear-Out; 4) Identifying Which Cracks Matter; and 5) Software Tools and Data Resources This annual report summarizes these key results, as well as reviewing our other ongoing work in fiscal year 2024.
14 SOLAR ENERGY↗
Comparing Outdoor to Indoor Performance for Bifacial Modules Affected by Polarization-Type Potential-Induced Degradation
Bifacial photovoltaic (PV) modules have the advantage of using light reflected off of the ground to contribute to power production. Predicting the energy gain is challenging and requires complex models to do so accurately. Often, module degradation over time is neglected in models for the sake of simplicity or is underestimated. Comparing outdoor and indoor current–voltage (I–V) performance for bifacial modules is more challenging than for monofacial modules, as there are additional variables to consider such as rear albedo non-uniformity, cell mismatch, and their effects on temperature. This challenge is compounded when heterogeneous degradation modes occur, such as polarization-type potential-induced degradation (PID-p). To examine the effects of PID-p on I–V predictions using an empirical data-driven approach, 16 bifacial PERC modules are installed outdoors on racks with different albedo conditions. A subset is exposed to high-voltage biases of −1500 V or +1500 V. Outdoor data are traced at irradiance ranges of 150–250 W/m 2 , 500–600 W/m 2 , and 900–1000 W/m 2 . These curves are corrected using control module temperature, wire resistivity, and module resistance measured indoors. We examine several methods to transform indoor I–V curves to accurately, and more simply than existing methods, approximate outdoor performance for bifacial modules without and with varying levels of PID-p degradation. This way, bifacial performance modeling can be more accessible and informed by fielded, degraded modules. Distributions of percent errors between indoor and outdoor performance parameters and Mean Absolute Percent Errors (MAPEs) are used to assess method quality. Results including low-irradiance data (150–250 W/m 2 ) are discussed but are filtered for quantifying method quality as these data introduce substantial errors. The method with the most optimal tradeoff between low MAPE and analysis simplicity involves measuring the front side of a module indoors at an irradiance equal to plane-of-array irradiance plus the product of module bifaciality and albedo irradiance. This method gives MAPE values of 1–6.5% for non-degraded and 1.6–5.9% for PID-p degraded module performance.
14 SOLAR ENERGY↗
Carbon Footprint Analysis of Floating PV Systems
This report, conducted by the Dutch research organization TNO, presents the first detailed life cycle inventory (LCI) analysis of operational floating photovoltaic (FPV) systems. The study, focusing on two operational systems in Western Europe, reveals that FPV systems on small inland water bodies can be a valuable complement to ground-mounted PV systems in terms of greenhouse gas emissions reduction. If PV module degradation is limited, these systems' carbon footprint is 3-4 times lower than the EU grid mix target for 2030. The report compares two FPV systems with different floater compositions (HDPE and steel/HDPE) to hypothetical ground-mounted systems, using comprehensive background data. The findings highlight the necessity for long-term monitoring and thorough environmental assessments. Josco Kester, a scientist at TNO, underscores the potential environmental benefits of these systems, which could enhance the adoption of renewable energy technologies.
14 SOLAR ENERGY↗
Clear Sky Irradiance Year-to-Year Variations and Trends
Solar radiation data for seven SURFRAD stations for the period 1996-2018 show an increase in irradiance under clear skies over the period, but the increase was not constant and shorter periods may have even experienced decreases in irradiance. A popular implementation of a clear sky model provided modeled irradiances for comparison with the SURFRAD data under conditions screened for clear skies. The use of the clear sky model, which did not consider year-to-year variances in atmospheric turbidity, was found problematic for resolving small changes in irradiance important for determining PV system degradation over three or five years, but less problematic for a period of ten years.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Clear Sky Irradiance Year-to-Year Variations and Trends: Preprint
Solar radiation data for seven SURFRAD stations for the period 1996-2018 show an increase in irradiance under clear skies over time, with an interannual variability of the increase. A popular implementation of a clear sky model provided modeled irradiances for comparison with the SURFRAD data under conditions screened for clear skies. The use of the clear sky model, which did not consider year-to-year variances in atmospheric turbidity, was found problematic for resolving small changes in irradiance important for determining PV system degradation over three or five years, but less problematic for a period of ten years.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Albedo Data Sets for Bifacial PV Systems
Solar radiation data for seven SURFRAD stations for the period 1996-2018 show an increase in irradiance under clear skies over the period, but the increase was not constant and shorter periods may have even experienced decreases in irradiance. A popular implementation of a clear sky model provided modeled irradiances for comparison with the SURFRAD data under conditions screened for clear skies. The use of the clear sky model, which did not consider year-to-year variances in atmospheric turbidity, was found problematic for resolving small changes in irradiance important for determining PV system degradation over three or five years, but less problematic for a period of ten years.
41 EE - Solar Energy Technologies Office (EE-4S)↗
An Open-Source Python Library for Modeling LETID and LID in Silicon Solar Cells and Wafers
This poster demonstrates an (in development) open-source software library, written in python, to aid in modeling and understanding light- and elevated temperature-induced degradation (LETID) and boron-oxygen light-induced degradation (B-O LID) in silicon solar cells and wafers. We discuss the underlying equations and necessary input parameters for constructing realistic models. We demonstrate several use cases for the library, including modeling LETID progression in scenarios like indoor, accelerated tests and outdoor field deployment. We also demonstrate using the library to model B-O LID, and we demonstrate using the library to model degradation in passivated wafers, rather than solar cells.
LETID↗
Accelerating Simulation for High-Fidelity PV Inverter System Reliability Assessment with High-Performance Computing
The overall cost of photovoltaic (PV) systems has shown a downward trend during the last decade; however, PV inverter failures account for the highest cost of operation and maintenance. To address this, reliability tools with powerful computation and better accuracy are required for the lifetime prediction and degradation evaluation of PV inverters. This paper proposes an event-driven parallel computing-based simulator. The proposed simulator applies high-performance computing techniques and other accessory optimization techniques-including cluster merging, adaptive model updates, and steady-state identification-to make reliability assessments for PV inverters under given input mission profiles and operating conditions with high efficiency and high fidelity. The main idea of the simulator and its workflow are introduced. Then, a demo PV inverter system simulator is implemented, and the speedup of the total simulations of the switching model reaches 123.03 times.
high-performance computing↗
Evaluation of clear-sky and satellite-derived irradiance data for determining the degradation of photovoltaic system performance
Knowing the degradation in performance of a photovoltaic (PV) system over time is important for estimating the lifetime energy produced and the financial return. A key parameter for normalizing performance and determining degradation is the plane-of-array (POA) irradiance. Because accurate long-term POA measurements are not always readily available, three methods of providing irradiance data for determining the degradation rate of PV systems were evaluated—a method using irradiance data modeled with the Ineichen clear-sky model and monthly Linke turbidity coefficients, a method using the supplemental clear-sky irradiance data from the National Solar Radiation Data Base (NSRDB), and a method using the NSRDB solar irradiance data for both cloudy and clear-sky conditions (all-sky). The irradiance data from the three methods were evaluated using measured irradiance data from 1998 through 2018 for the seven-station SURFRAD network and for 3-, 5-, and 10-year periods that might be used for evaluating PV system performance. Only the two clear-sky methods for the 10-year periods had less uncertainty with respect to determining PV system degradation than the expected median degradation rate for PV systems of -0.5%/year to -0.6%/year. Shorter periods and the all-sky method had larger uncertainties, making their use questionable for determining the degradation rates of PV systems.
14 SOLAR ENERGY↗
The "PVLib" of Degradation: PVDeg
The Photovoltaic (PV) industry constantly aims for lower costs through higher-efficiency cells, improved module designs, and improvements in durability. This leads to the use of new materials, designs, and manufacturing processes, and not always with a sufficient amount of durability testing. To help drive down costs there is a desire to create modules that will last for up to 50 years of service life. To accomplish this, every degradation mode and mechanism must be identified and either eliminated or otherwise mitigated. This involves the extrapolation of laboratory results to the field conditions. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. While the basic equations used to model degradation are sometimes very simple, the full analysis involves calculations are cumbersome but ubiquitous for many degradation processes. A simplified, modeling framework to accomplish these repetitive processes will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this talk, we will describe our progress creating the open-source tool PVDeg. This tool can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. PVDeg simplifies many of the common foundational computational operations for obtaining meteorological data and using it to generate a model of the PV deployment. This prediction tool repository also contains various degradation models as well as a library of material parameters suitable for estimating the durability assessment of materials and components. We use an integration pipeline approach that allows us to leverage weather data from the National Solar Radiation Database, and other weather sources, to perform geospatial degradation analysis in the US and worldwide. We hope to become a repository that can be used for weathering and degradation analysis for various applications beyond the PV industry. During the talk, we will provide the PVPMC attendees the opportunity to interact with the tool via a Google Collab tutorial they can run on their phones or laptops.
durability↗
Machine Learning-Driven Reliability Estimation of PV Inverters Considering Alert-Ambient Variability
Weather-induced spatio-temporal degradation limits outdoor PV inverter lifetime and reliability, necessitating advanced data analysis. This study employs a top-down, data-driven approach utilizing multiple machine learning (ML) algorithms to estimate inverter reliability in a 1.4 MW PV power plant, considering factors such as irradiance, humidity, temperature, time of day, and weather conditions. An extensive alert dataset from 17 identical inverters, including alert types, propagation, and frequency, reveals significant correlations with environmental factors and inverter output power, enabling the construction of a performance reliability model. Dual-stage supervised-ML models are evaluated for accuracy, with the ‘classification-regression’ model by an artificial neural network (ANN) tested on the averaged “Alert-Ambient” dataset, which is outperformed by ‘clustering-regression’ models using random forest (RF) and K-Nearest Neighbors (KNN) on individual inverter datasets. K-means clustering applies principal component analysis to reduce dimensions, achieving improved accuracy beyond the 80% achieved by ANN on the averaged dataset. Second-stage regression estimates inverter reliability with a mean square error of 0.0195 on the averaged dataset and as low as 0.002 on individual inverter datasets using RF. Furthermore, these findings highlight the method's suitability for estimating PV inverter output reliability under ambient conditions, essential for digital twin development and related applications.
14 SOLAR ENERGY↗
Signal Processing on PV Time-Series Data: Robust Degradation Analysis Without Physical Models
Not Available
14 SOLAR ENERGY↗
Energy in the Balance: PV Reliability to Power the Energy Transition
We present an analysis of the effects of reliability on our ability to achieve the energy transition deployment targets. We examine three end of life modes as captured in the PV ICE tool; degradation, failures, and project lifetime. Recommendations are made for improving PV reliability for achieving energy energy transition.
circularity↗
Electrochemical mechanisms of leakage‐current in photovoltaic modules
Abstract This paper analyzes the mechanisms and pathways for leakage current flow observed in Si photovoltaic modules subjected to high temperature and humidity and a large voltage bias with respect to ground. The current inside of the frame is in the form of electron motion, but in the glass and polymer, it is in at least a large part attributable to the movement of ions. When the mode of current flow changes from electronic to ionic conduction, electrochemical reactions will take place at the interface. This can include reactions that produce volatile chemical species like H 2 , CO x , and O 2 , along with ionic species such as OH − and H 3 O + . Here, we see evidence of the importance of different charge carriers with different diffusion rates and the influence of electrochemical processes involved. The application of negative voltage to the cell circuit affects the resistivity of glass producing surfaces with poor conductivity but with some increases in the electrochemical potential producing complicated interactions that are important when the voltage is changed. In the polymer, there is the development of a space charge region and a chemical gradient providing two oppositional forces to current flow, which when released create a complicated discharge process. Here, we give a basic understanding of the charge/discharge of PV cells highlighting how the specific mechanisms are important in understanding some of the degradation processes in PV modules. We find that there is evidence of multiple significant charge carrier species with different diffusion time scales. The glass/polymer interface forms a depleted region of higher resistance after prolonged exposure to current. Charge also builds up at the polymer to cell antireflective coating interface and mostly flows to the gridlines to experience electrochemical reactions. These complexities result in non‐linear behavior where the apparent resistivities of the different layers change during charge/discharging processes, making the modeling of the current flow extremely difficult.
14 SOLAR ENERGY↗
Translating Material-Level Characterization of Carbon-Nanotube-Reinforced Composite Gridlines to Module-Level Degradation
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.
carbon nanotubes↗
Investigating the Crosslinking, Degradation, and Adhesion Behavior of Photovoltaic Encapsulants Under Thermal Accelerated Aging
Degradation of photovoltaic (PV) module encapsulant characteristics that lead to mechanical embrittlement and delamination remains a cause of failure in solar installations. A multiscale reliability model connecting the encapsulant mechanical and fracture properties to the degraded molecular structure and interfacial bonding to adjacent solar cell and glass substrates was previously published. The model, developed primarily for poly(ethylene-co-vinyl acetate) acetate (EVA) encapsulants, remains to be experimentally validated. Determining the degradation and crosslinking kinetics of alternative encapsulants, such as polyolefin elastomer (POE) and EVA/POE/EVA composites (EPE), can generalize the model. In this work, we subject fully cured EVA, POE, and EPE encapsulants to accelerated thermal aging to determine how high temperatures impact reaction kinetics. An increase in gel content (crosslinking) and decrease in crystallinity of the encapsulants under hot-aerobic (90 degrees C, 22% RH) and hot-anaerobic (90 degrees C, sealed in N 2 air) aging were observed, even in the absence of UV and crosslinking initiators. Fourier transform infrared spectroscopy (FTIR)-attenuated total reflectance analysis showed insignificant encapsulant degradation, demonstrating the critical role of UV and moisture in accelerating degradation. Adhesion testing performed on coupon-level specimens (cell/encapsulant/glass laminates) showed decreases in adhesion energy, Gc , from 5000 h of hot-dry (90 degrees C, ~1% RH) and hot-humid (90 degrees C, 60% RH) aging. POE coupons demonstrated the best stability, followed by EPE then EVA. For EVA and POE, hot-humid aged coupons experienced a larger decrease in Gc due to enhanced hydrolytic degradation. Hot-dry aging condition demonstrated that thermal degradation of the interface could be significant even if the encapsulant experiences negligible degradation in the absence of UV and elevated humidity.
accelerated aging↗
Determining the Crosslinking and Degradation Reaction Kinetics in Photovoltaic Encapsulants Using Accelerated Aging: Preprint
Degradation of photovoltaic (PV) module encapsulant mechanical characteristics that lead to embrittlement and delamination remains a cause of failure in solar installations. A multiscale reliability model based on detailed molecular degradation reaction kinetics was previously published, connecting the encapsulant mechanical properties (elastic modulus, yield strength, and adhesion energy) to the degraded molecular structure and interfacial bond density to adjacent solar cell and glass substrates. The model, developed primarily for poly(ethylene-co-vinyl acetate) (EVA) encapsulants, remains to be experimentally validated. Determining the degradation and crosslinking kinetics of alternative encapsulants, such as polyolefin elastomer (POE) and EVA/POE/EVA composites (EPE), can further generalize the model. Importantly, the activation energy for crosslinking of fully cured PV encapsulant products from temperature or UV is presently unknown or unavailable. In this work, we subject EVA, POE, and EPE encapsulants to a set of accelerated aging conditions, varying the temperature, UV intensity, and relative humidity. We use DSC, FTIR, and Soxhlet extraction (gel content) to characterize the encapsulants' changing molecular structure. This allows for determination of the photochemical degradation and crosslinking kinetics of the encapsulants. Preliminary results show an increase in gel content (crosslinking) and a decrease in crystallinity of EVA, POE, and EPE encapsulants under hot-aerobic (90 deg C, 22% RH) and hot-anaerobic (90oC, sealed in N2 air) accelerated aging, even in the absence of UV and crosslinking initiating agents. For a least squares regression with an assumed first-order crosslinking kinetics, the crosslinking rate parameters were computed for the three encapsulants under hot-aerobic and hot-anaerobic aging conditions. FTIR analysis showed insignificant encapsulant degradation for hot-aerobic and hot-anaerobic aging, demonstrating the critical role of UV and moisture in accelerating degradation. Aging conditions with UV exposure and elevated humidity are presently in progress.
adhesion↗