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At least 217 records · Page 12

Susceptibility to polarization type potential induced degradation in commercial bifacial p-PERC PV modules

Potential induced degradation (PID) is a reliability issue affecting photovoltaic (PV) modules, mainly when PV strings operate under high voltages in hot/humid conditions. Polarization-type PID (PID-p) has been known to decrease module performance quickly. PID-p can be reduced or recovered under the light in some cases, but this effect, as expected, would be less pronounced on the rear side of bifacial PV modules receiving lower irradiance. As bifacial PV modules are projected to dominate the PV market within the next 10 years, it is crucial to understand the PID-p issue in bifacial modules better. In this study, we performed indoor PID testing to induce PID-p on 14 commercial bifacial p-PERC modules with three different module constructions from three manufacturers. Here, four rounds (+ve and –ve polarities for front and rear sides) of PID testing are done at 25°C, 54% relative humidity (RH) for 168 h using the aluminum foil method. Each module side (front cell side and back cell side) is tested individually under both negative and positive voltage bias. The results show that the highest degradation of 32% in maximum power (Pmax) at standard test conditions (1000 W/m 2 ) and 51% at low irradiance (200 W/m 2 ) has been observed in some cases. Recovery under sunlight is also done, and outcomes show a near-complete recovery in Pmax. This study presents an extensive experimental methodology and a detailed analysis to systematically and simultaneously/sequentially evaluate multiple construction types of bifacial modules to the PID-p susceptibility and recovery.

14 SOLAR ENERGY↗

U.S. Solar System Decommissioning Policies

In the United States, cumulative installed utility-scale solar photovoltaic (PV) capacity reached more than 60 gigawatts (GW)dc at the end of 2020. Federal and state renewable energy and net-zero emissions policies will continue to drive solar development in the United States with installed utility-scale PV projected to quadruple (240 GWdc) by 2030. Although more than 75% of all U.S. installed utility-scale PV came online in the last 5 years, federal, state, and local governments are planning for system decommissioning. Our research found that as of April 2021, one federal agency, the Bureau of Land Management (BLM), and 15 U.S. states have solar decommissioning policies in place. North Carolina is also in the process of drafting solar decommissioning regulations, and at least 4 states (Maine, Pennsylvania, West Virginia, Texas) proposed solar decommissioning bills in the 2021 legislative session. This presentation looks at U.S. federal and state solar decommissioning policies who they apply to, when they apply, the requirements/responsibilities, and what the impacts are.

circular economy↗

Root Cause Analysis of AC Overcurrent in July 2020 San Fernando Disturbance

On July 7 2020, approximately 1,000 MW reduction in solar photovoltaic (PV) output was experienced by the bulk power system in Southern California after a three-phase fault. Disturbance analysis indicates that instantaneous AC current caused inverter tripping. The projection of the root cause of AC overcurrent from the NERC report is that inverter current control is not tight. This letter provides a quantitative analysis on ac overcurrent and addresses the following questions: (i) what type of current controls may lead to ac overcurrent; and (ii) how controller parameters and grid strength influence ac overcurrent. Here, the letter provides frequency-domain analysis and time-domain simulation results of a grid-integrated inverter to illustrate the effect of control parameters and grid strength on ac overcurrent.

14 SOLAR ENERGY↗

Understanding PV Polymer Backsheet Degradation through X-Ray Scattering

Understanding how photovoltaic (PV) module backsheet polymers age and degrade in response to environmental stresses is important for designing polymers that can maintain their structural integrity after decades of outdoor use. X-ray scattering is a powerful technique for exploring backsheet polymer structure at the angstrom- (wide-angle, WAXS) and nanometer- (small-angle, SAXS) length-scales. We present the use of SAXS and WAXS to study pristine and aged polymer backsheets. The structural insight from these techniques can be used to compare the degradation induced by accelerated testing with the degradation seen in field-aged PV materials.

14 SOLAR ENERGY↗

OPET Hardware (Open PV Electrical Tool Hardware) [SWR-25-42]

OPET (Open-source Photovoltaic Electrical Tool) is used for performance measurements of solar photovoltaic (PV) devices in the field under natural sunlight or in the lab under artificial light. Its primary use is in research and development of solar cells and modules, specifically in reliability and durability research of PV devices. Some features and functions include: -IV curve measurements with linear or cosine distributed measurement points -PV device active loading at open circuit voltage (Voc), short circuit current (Isc) and maximum power point (Pmp) -Bias power supply to overcome series resistance in contact wires for Isc measurements and loading -PV voltage input in five ranges from 1V to 100V -PV current input ranges -Low current version, six current ranges from 1.1mA to 340mA -High current version, six current ranges from 50mA to 15A -IO ports for I2C and SPI temperature sensor Arduino extension boards -Integrated fan control This repository contains everything relating to the hardware of the OPET device. If you are looking for the firmware or software repositories, links are below: https://github.com/NREL/opet-firmware https://github.com/NREL/opet-control

McDanold, Byron [National Renewable Energy Laborat↗

Quantifying Optical Loss of High-Voltage Degradation Modes in PV Modules Using Spectral Analysis [Slides]

The direct current bias for photovoltaic (PV) modules interconnected in series-strings may include both high voltage negative ("HV-") and positive ("HV+") polarity with respect to the electrical ground. Multiple degradation modes, resulting in quantifiable optical loss, were found to occur during HV-/HV+ sequential stress, including: corrosion of the external glass surface, encapsulant delamination (at its interfaces with the glass and the PV cell), internal haze formation (resulting from a chemical interaction between the glass and the encapsulant), corrosion and migration of the gridlines, and corrosion of the silicon nitride (SixNy) antireflective coating on the cell. The effects of these separate modes were examined using monolithic (e.g., glass or PV cell) and laminated-coupon (glass/encapsulant/glass or glass/encapsulant/cell/encapsulant/backsheet) specimens. Characterizations during and after unbiased accelerated testing at 85 degrees C/85% relative humidity included: spectrophotometry, optical microscopy, electron microscopy, and ellipsometry. For some module components (i.e., the glass and the SixNy coating), the optical performance was determined through iterative analysis of empirical measurements. Concentrating on just their spectral effect, a novel model was then developed to estimate the transfer of light to the PV cell and the return of light from the PV module with simultaneous degradation mechanisms, which was compared to a mini-module previously subjected to HV-/HV+ stress. The model suggests one-third of the current loss observed for the mini-module can be attributed to the optical degradation of the packaging materials. The dominant degradation modes include encapsulant delamination and corrosion of the SixNy coating. Recommendations are given so that the optical model may be improved relative to accelerated testing and validated relative to field aging.

14 SOLAR ENERGY↗

Library of Advanced Models of large-scale PV (LAMP) (Final Technical Report)

A suite of dynamic models of photovoltaic (PV) systems is developed in this project to accurately capture PV system dynamics during different contingencies. The following models are included: (i) quasi-dynamic, (ii) high-fidelity electromagnetic transient (EMT), (iii) advanced, and (iv) baseline. The models have the flexibility to consider different control functionalities at different controller levels. The study’s requirements determine the type of model needed. For example, high-fidelity EMT models are recommended for contingency studies. Advanced models are recommended for online or real-time implementations with resource constraints, whereas quasi-dynamic models are useful for studying the impact of weather variations.

14 SOLAR ENERGY↗

Arrhenius Analysis of the Degradation Modes in Emerging Photovoltaic Backsheets

With increasingly large-scale deployments of photovoltaic (PV) modules to meet global energy demands, interest in better establishing modules' lifespans is growing. We report on the performance of co-extruded polyolefin- (PO)-based backsheets as environmentally friendly alternatives to fluoropolymer-reinforced polyethylene-terephthalate (PET)-based backsheets using three hygrometric accelerated test conditions. After completing cumulative 4000 hours of aging, we analyzed data from electrical performance (I-V), surface roughness (gloss), and appearance (L, a*, b* color) characterizations to quantify degradation rates, quantify the corresponding activation energy, and cross-correlate between the characteristics examined, thereby providing insights into the relationship between physical characteristics and operating performance.

BackFLIP↗

Arrhenius Analysis of the Degradation Modes in BackFLIP Study of Emerging Photovoltaic Backsheets: Preprint

With increasingly large-scale deployments of photovoltaic (PV) modules to meet global energy demands, interest in better establishing module lifespans is growing. We report on the performance of co-extruded polyolefin- (PO) based backsheets as environmentally friendly alternatives to fluoropolymer-reinforced polyethylene-terephthalate- (PET)-based backsheets using three hygrometric accelerated test conditions. After completing 4000 cumulative hours of aging, we analyzed data from electrical performance (I-V), surface roughness (gloss), and appearance (L, a*, b* color) characterizations are analyzed to quantify degradation rates, quantify the corresponding activation energy, and cross-correlate between the characteristics examined, thereby providing insights into the relationship between physical characteristics and operating performance.

BackFLIP↗

Comparative Analysis of Hotspot Stress Endurance in Pristine and Thermal Cycled Prestressed Glass–Glass Photovoltaic Modules

Hotspots pose a significant long-term reliability challenge in photovoltaic (PV) modules that can have a detrimental impact on the efficiency, safety, and financial viability of a PV system. This paper aims to evaluate the endurance of hotspot stress in pristine and prestressed glass–glass (GG) modules. The accelerated prestressing was conducted for 600 thermal cycles (TC600) to represent decades of field exposure. GG modules are quickly becoming an alternative to the traditional glass–backsheet (GB) modules that have been the industry standard. Unlike other conventional studies that subject only pristine modules to hotspot stress, this paper evaluates the performance of an accelerated/simulated field-aged GG module (using TC600) and a pristine GG module. Pre- and post-characterizations were performed before and after each test to determine changes in electrical performance and observe any defects in GG modules. During the hotspot test, an approximately 200 °C maximum cell temperature was observed with a cell shading of 25% (the worst-case shading ratio). After the hotspot test, electroluminescence imaging indicated that most cells in the prestressed GG module exhibited severe damage whereas no significant defects were evident in the pristine GG module where the prestressed GG module degraded 8.2% and the pristine GG module degraded 1.5% in maximum power. These findings are critical for the industry, considering that GG bifacial modules will dominate the market.

14 SOLAR ENERGY↗

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↗

Photovoltaic device innovation for a solar future

Photovoltaics (PV), also known as solar cells, are now found everywhere - in utility plants; on roofs of homes and commercial buildings; on platforms at sea; in agricultural fields; on vehicles, buildings, drones, and backpacks; and, in their longest running application, providing power in space. Continuous device innovation has led to increased efficiency and improved reliability for multiple PV technologies. Confronted with an urgent need to deploy PV at multiterawatt (TW) scale over the next two decades to mitigate greenhouse gas emissions, PV device innovation takes on new urgency and impact. This perspective reviews recent progress in device design and performance for PV technologies that are currently in commercial production at greater than 1 GW/year or enabling significant space-based power generation - Si, CdTe, CIGS, and multijunction III-V - and looks ahead to the next 5 years. In conclusion, we also identify device-related topics requiring cross-cutting research and innovation.

14 SOLAR ENERGY↗

Feature review of photovoltaic modeling software utilizing blind performance assessment

While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.

14 SOLAR ENERGY↗

Failure Mode and Effects Analysis (FMEA) for Photovoltaic Inverter

Photovoltaic (PV) inverters are critical yet vulnerable components in modern energy systems, often acting as reliability bottlenecks that increase the levelized cost of energy (LCOE). To address this, this paper presents a comprehensive Failure Mode and Effects Analysis (FMEA) tailored for PV inverters. Leveraging field data and literature, we identify failure-prone components, such as capacitors,, and relays, and prioritize their risks based on quantitative Risk Priority Numbers (RPNs). The analysis reveals that surge-induced MOV short circuits, capacitor degradation, and environmental cooling fan failures dominate the risk profile. These findings provide a targeted framework for reliability improvement, guiding future efforts in predictive diagnostics, design optimization, and accelerated life testing strategies.

14 SOLAR ENERGY↗

Availability and Performance Loss Factors for U.S. PV Fleet Systems

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data and publish aggregated, anonymized results. This report is an update of our previous publications, specifically a FY 2021 performance index publication and a FY 2022 fleet degradation analysis. In this analysis, we have increased our data participants and system totals by around 10% to 8.5 GW and 24,000 separate inverter data channels. Four major analysis topics are considered in this report: Performance Index (PI) trends, PV system availability, soiling losses, and PV system degradation. Performance Index and inverter availability are assessed on a larger set of data from our FY 2021 report: 1,128 systems compared with 200 systems from before. The increased number of systems is due to an improved data quality methodology, as well as introducing new systems to the analysis. Overall results are similar to previously published values - overall inverter availability is low in the first six months of system performance before reaching steady-state by the end of the first year. Excluding this six-month startup period, system-level aggregated data shows a median (P50) system availability of 0.99 and a lower 10th percentile (P90) value of 0.95 (Figure ES-1). A dependence on system size is also demonstrated, with worse inverter availability results for larger PV systems. Causes of this effect are under investigation, but may be impacted by inverter size, which also show lower availability for larger inverter sizes. This report also investigates PI, correcting for degradation, soiling, snow, and availability. Following these corrections, the median system PI over its entire lifetime is 0.95. PI values reported here are approximately 3% lower than what we presented in our previous FY 2021 report. Soiling loss is assessed in a comprehensive way for the first time in this report. Results are presented using the COmbined Degradation and Soiling (CODS) method, as implemented in RdTools (v3.0.0a4). Soiling values are presented for 255 systems, which indicated irradiance-weighted soiling loss greater than 1%. The values have been published in an updated NREL soiling map at nrel.gov/pv/soiling.html. Finally, we investigated system degradation using three different data analysis techniques: conventional RdTools (year-on-year (YOY)), CODS, and Performance Loss Rate (PLR) analysis. Overall degradation results are consistent with our previous publications. Rerunning conventional RdTools on our updated fleet shows that some data partners have systematically fallen below the median system degradation rate (change over time) of -0.75 %/year. A comparison with PLR analysis, which looks at change in annual PI over time, shows that median system degradation is consistent with -0.5% to -0.75% per year change. However, at the P90 value, system degradation is substantially faster. These two results are consistent and indicate that resulting degradation statistics depend to a great degree on the population of PV systems making up the analysis cohort and whether soiling impacts the systems. The use of CODS for degradation analysis provides a different method for degradation assessment, which explicitly excludes the impact of recoverable soiling on degradation analysis. Excluding soiling effects yields an annual system degradation around -0.5% per year on average. This indicates that a portion of system performance loss may be attributed to periodic soiling that is not fully recovered. This report provides PV system owners/operators with background and methods to analyze PV system performance, give guidance for expected cohort performance, and performance loss values for use in pro-forma financial models, which guide new-build system design and bankability reports.

14 SOLAR ENERGY↗

PV System Availability from Commercial and Utility-Scale Systems [Slides]

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data, and publish aggregated, anonymized results. An assessment of system availability is conducted on 1128 systems which passed our data quality checks, and include cumulative energy meter data. Overall inverter availability is low in the first 6 months of system performance before reaching steady-state by the end of the first year. System-level aggregated data shows a median (P50) system availability of 0.99, and a lower P90 value of 0.95. A dependence on system size is also identified, with worse inverter availability results for larger PV systems. Potential causes of this effect are under investigation.

14 SOLAR ENERGY↗

Multi-Timescale Integrated Dynamic and Scheduling Model (MIDAS-Solar)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power system operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power systems steady-state and dynamic performance. This project helps meet and exceed the Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for electric grid planning and operation. This will be accomplished by developing temporally comprehensive, closed-loop simulation models that seamlessly simulate power systems operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). Both a multi-timescale grid model and an integrated PV model will be developed in this project to accurately study the impacts of PV variability and uncertainty on system reliability at multiple timescales. Using quasi-dynamic simulation methods and data-driven security assessment (DSA) criteria will allow the dynamic characteristics of PV to be fed forward into longer-timescale scheduling models for a complete understanding of the effect of short-term PV dynamics on bulk systems operations (e.g., reserve scheduling and deployment). Upon completion of the proposed model, this project will help operators accurately assess system reliability by deploying energy and reserve scheduling under critical contingency conditions and studying interactions among all types of essential reliability services provided by modern PV power plants.

14 SOLAR ENERGY↗