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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Numerical Validation of an Algorithm for Combined Soiling and Degradation Analysis of Photovoltaic Systems

We describe and demonstrate an open-source algorithm for simultaneously quantifying degradation and soiling of photovoltaic (PV) systems from energy-production time series data. The new analysis is based on year-on-year degradation rate analysis combined with stochastic rate and recovery soiling analysis. The algorithm is designed to fit into the workflow provided by RdTools, a Python module maintained by NREL and collaboratively developed with the community, which provides a framework and functions for degradation and loss-factor analysis of PV field data. We demonstrate the method on numerically simulated PV data sets and show that it reduces the root-mean-square error of the P50 degradation rate estimate when soiling is present.

14 SOLAR ENERGY↗
DOE OSTI2021

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗
DOE OSTI2024

Experimental Considerations for Estimating Degradation in PV Modules

Carefully controlled laboratory experiments and measurements can enable the determination of acceleration factors suitable for extrapolation to durability and performance of a fielded PV module. Ideally, a single mechanism can be identified with appropriate acceleration factors for extrapolation to the field. However, even with a single mechanism, the inherent uncertainty in these factors leads to uncertainty in the extrapolation which is greater the higher the acceleration factor. This course will explain how because of the wide range of acceleration factors for a given degradation mode, utilizing acceleration factors greater than about 10x will typically lead to unacceptable uncertainty in the results. Therefore, if even just a rank ordering of materials is desired, acceleration factors must be minimized which requires a good general understanding of the scale of the different acceleration factors for the degradation mode of interest. In this tutorial we will discuss what the different purposes are for many of the accelerated stress tests used today. E.g., what is a qualification test, a highly accelerated stress test, a rank ordering test, or a service life prediction test. We will discuss how one can understand the relationship between test results and expected field performance. A single accelerated stress test condition cannot duplicate outdoor exposure for all possible degradation pathways; therefore, one must use targeted evaluation of material properties at different stress levels to determine the relevant acceleration factors and fit it to a model. We will also discuss how to interpret the results of experiments understanding what is relevant/not relevant, or not e valuated in a test. There are many common error people make in their test interpretations because they push the stress levels to be too harsh. This creates biases and can mask the relevant failure modes and mechanisms or will erroneously lead one to over design materials against things that aren't relevant. Several case studies will be presented to illustrate appropriate interpretation of accelerated stress testing results.

degradation↗
DOE OSTI2025

PV Fleet Performance Data Initiative Final Technical Report (FTR)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. This project will leverage data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Please see our list of public reports at https://www.nrel.gov/pv/fleet-performance-data-initiative.html. Objective 1: Support the global PV industry with scalable, robust data analysis tools that reduce the uncertainty of PV system performance and loss calculation. Objective 2: Reduce perceived risk arising from degradation rate, soiling loss, and system availability by publishing detailed statistics on U.S. fleet performance. Objective 3: Highlight factors leading to system underperformance including module type, climate, mounting configuration, etc. Objective 4: Enable continued high system performance in modern PV systems, as turnover and advances in technology bring new suppliers and high-efficiency modules into the market.

14 SOLAR ENERGY↗
DOE OSTI2023

De-Risking Large-Scale PV Systems Through Data Analytics

Large-scale photovoltaic system performance analysis is being conducted within the US Department of Energy's-sponsored PV Fleet Performance Data Initiative. This collaboration with commercial PV system owners collects and evaluates PV field performance data, and provides reports on aggregated results. Drawing on over 2200 sites across the US and over 24,000 separate PV inverters we have collected in excess of 8.3 gigawatts (GW) of performance data, representing 6-7% of the entire US installed PV capacity. A mixture of utility-scale and large commercial systems are represented, averaging 4.1 megawatts (MW) in size and 5 years in age. Initial results show average system degradation rates at -0.75% / year, which is slightly higher than historically reported module-level values of -0.5%/year. We also found that the availability of systems averaged 97.7%, which is lower than the typical 99% uptime assumed by many project economic forecasts. Given these results, we compared monthly performance with expected production values, based on satellite weather data and a simple PVWatts performance model. We found that systems were performing within 10% of monthly expectation over 90% of the time, with a fleet average vs expected monthly value of 0.994. We also evaluated the impact of extreme weather events on system performance, and found a range of short-term and longer-term performance effects ranging from grid outage, system downtime, module damage and accelerated long-term degradation rate.

analysis↗
DOE OSTI2023

Extreme Weather Events and PV Systems Impact

The impact of extreme weather events on PV performance was studied by comparing the National Oceanic and Atmospheric Administration database on severe weather with the National Renewable Energy Laboratory's (NREL) PV Fleet database on continuous PV performance. We identified 170 systems that were immediately impacted by weather events. These severe weather events lead to a median loss of only 1 % of annual production. However, flooding and high wind events were found to have an extremely long tail extending to 60 % loss, showing that these discrete events can pose a substantial risk to PV systems. Besides the short-term impact of lost production due to outages, we also found a statistically significant increased performance loss rate (PLR) for high wind events above 90 kilometer/hour, by comparing PLR before and after these events. Similarly, hail events caused higher PLR for hail sizes of and above 25 mm indicating that more stringent hail testing for PV modules is required. In addition, very high snow loads may also cause increased PLRs, but more data are required to better quantify the impact. These findings illustrate the substantial risk extreme weather events pose short-and long-term to fielded PV installations.

extreme weather↗
DOE OSTI2023

Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$

Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current-voltage characteristic (I-V curve), the acquisition of which involves specific measurement devices and costly methods. Thus, I-V curves of the PV system level are often not available. Here this paper proposes a methodology (PVPRO) to estimate these I-V curve parameters using only operation (string-level DC voltage and current) and weather data (irradiance and temperature). PVPRO first performs multi-stage data pre-processing to remove noisy data. Next, the time-series DC data are used to fit an equivalent circuit single-diode model (SDM) to estimate the circuit parameters by minimizing the differences between the measured and estimated values. In this way, the time evolutions of the SDM parameters are obtained. We evaluate PVPRO on synthetic datasets and find an excellent estimation of both SDM and the key I-V parameters (e.g., open-circuit voltage, short-circuit current, maximum power, etc.) with an average relative error of 0.55%. The performance, especially the extracted degradation rate of parameters, is robust to various measurement noises and the presence of faults. In addition, PVPRO is applied to a 271 kW PV field system. The relative error between the real and estimated operation voltage and current is less than 1%, suggesting that degradation trends are well captured. PVPRO represents a promising open-source tool to extract the time-series degradation trends of key PV parameters from routine operation data.

14 SOLAR ENERGY↗
DOE OSTI2022

Onymous early‐life performance degradation analysis of recent photovoltaic module technologies

Abstract The cost of photovoltaic (PV) modules has declined by 85% since 2010. To achieve this reduction, manufacturers altered module designs and bill of materials; changes that could affect module durability and reliability. To determine if these changes have affected module durability, we measured the performance degradation of 834 fielded PV modules representing 13 module types from 7 manufacturers in 3 climates over 5 years. Degradation rates ( Rd ) are highly nonlinear over time, and seasonal variations are present in some module types. Mean and median degradation rate values of −0.62%/year and −0.58%/year, respectively, are consistent with rates measured for older modules. Of the 23 systems studied, 6 have degradation rates that will exceed the warranty limits in the future, whereas 13 systems demonstrate the potential of achieving lifetimes beyond 30 years, assuming Rd trends have stabilized.

14 SOLAR ENERGY↗
DOE OSTI2020

Reproducing the 'Framing' by a Sequential Stress Test

The 'Framing' (local discoloration along cell edges) was induced by a simple sequential accelerated stress test (consisting of hygrothermal- and UV-stressors) applied to the PV modules with high OTR (oxygen transmission rate) backsheet, irrespective of the inclusion of UV-absorber in poly(ethylene-co-vinyl acetate) (EVA) encapsulant. UV-fluorescence imaging of the PV modules suggests that the spatially-inhomogeneous degradation of EVA material under UV-irradiating conditions is correlated to this 'Framing' indicating an underlying common mechanism. These findings would contribute to the development of test procedures to broadly mimic the actual failures observed in fielded PV.

14 SOLAR ENERGY↗
DOE OSTI2022

Failure diagnosis and trend‐based performance losses routines for the detection and classification of incidents in large‐scale photovoltaic systems

Abstract Fault detection and classification in photovoltaic (PV) systems through real‐time monitoring is a fundamental task that ensures quality of operation and significantly improves the performance and reliability of operating systems. Different statistical and comparative approaches have already been proposed in the literature for fault detection; however, accurate classification of fault and loss incidents based on PV performance time series remains a key challenge. Failure diagnosis and trend‐based performance loss routines were developed in this work for detecting PV underperformance and accurately identifying the different fault types and loss mechanisms. The proposed routines focus mainly on the differentiation of failures (e.g., inverter faults) from irreversible (e.g., degradation) and reversible (e.g., snow and soiling) performance loss factors based on statistical analysis. The proposed routines were benchmarked using historical inverter data obtained from a 1.8 MWp PV power plant. The results demonstrated the effectiveness of the routines for detecting failures and loss mechanisms and the capability of the pipeline for distinguishing underperformance issues using anomaly detection and change‐point (CP) models. Finally, a CP model was used to extract significant changes in time series data, to detect soiling and cleaning events and to estimate both the performance loss and degradation rates of fielded PV systems.

14 SOLAR ENERGY↗
DOE OSTI2023

Accelerated Aging of PV Cables - The Development of Methods Towards Combined-Accelerated Stress Testing

PV cables allow the collection and distribution of electricity from modules to the energy grid. Durable cabling allows continuous operation of PV installations. Cables with a life less than that of the modules must be replaced - reducing electricity generation and adding to the system operating expense. We have examined the durability of a variety of representative cable samples using artificial UV weathering (IEC TS 62788-7-2) and combined accelerated stress testing (C-AST). Jackets in this study include PV-rated (polyolefin), building wire (PVC/PA), and multi-conductor (rubber, as in PV trackers), with some examples of black and red cables. Characterizations at read points include appearance (camera and optical microscope), surface roughness (linear profilometry), instrumented indentation, surface morphology (SEM), chemical composition (EDS), thermal decomposition (TGA), phase transition (DSC), crystalline structure (WAXS), and polymer chemical structure (FTIR). Complimentary examinations confirm damage to the external and interior layer(s) of less durable samples, including changes in morphology (e.g., cracking), chemistry (e.g., oxidation), structure, and mechanical performance (e.g., through-thickness modulus and hardness). The results may be generally compared to other examples from the field (PV installations) or after accelerated testing (IEC 61215). The methods in this study are presently being applied in a follow-on C-AST study, incorporating both dynamic and kinematic fixtures.

balance of systems↗
DOE OSTI2022

Measuring and Modeling Bifacial Technologies

Measuring and modeling bifacial technologies is of interest for new system design, capacity testing, and performance evaluation. The bifacial PV field at NREL has been gathering data for different bifacial technologies and sensors for the last 2.5 years, making it possible to compare bifacial performance with monofacial counterparts, as well as experimental demonstrations of best locations to place sensors to match modeled and perceived irradiance non-uniformity on the rear of the bifacial modules. This presentation summarizes performance, degradation, sensor position for module edge effects and the impact of row edge effects, and the roadmap for NREL bifacial modeling tools.

bifacial PV↗
DOE OSTI2025

Forecast for a growth-rate measurement using peculiar velocities from LSST supernovae

We investigate whether the cosmic growth-rate parameter fσ 8 can be measured using peculiar velocities (PVs) derived from type Ia supernovae (SNe Ia) in the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST). We produced simulations of different SN types using a realistic LSST observing strategy that incorporated noise, a photometric detection from the difference-image analysis (DIA) pipeline, and a PV field modeled from the Uchuu universe machine simulations. We tested three different observational scenarios that ranged from ideal conditions with spectroscopic host galaxy redshifts and spectroscopic SN typing to realistic photometric typing that resulted in a contamination with non-Ia SNe. Using a maximum likelihood technique, we showed that the LSST can measure fσ 8 with a precision of 10% in the redshift range 0.02 < z < 0.14 for our most realistic scenario. In three tomographic bins, the LSST will be able to constrain the growth-rate parameter with errors below 18% up to redshift z = 0.14. We also tested the contamination effect on the maximum likelihood method and found that for a contamination fraction below ∼2%, we recovered unbiased measurements. The results of this analysis highlight that the LSST SN sample is expected to complement traditional redshift-space distortion measurements at high redshift. This will provide a novel avenue for testing general relativity and different dark energy models.

Rosselli, D↗
DOE OSTI2020

Irradiance on the upper and lower modules of a two-high bifacial tracking system

We examine the illumination incident to each of the modules in a two-high bifacial tracking photovoltaic system. Experiments and simulations indicate that the upper module receives more diffuse sunlight, whereas either the upper or lower module can receive more direct sunlight depending on the configuration and conditions. We use a view-factor model to illustrate how the fraction of illumination received by the upper and lower modules depends on albedo, the sun’s position in the sky, module tilt, and the fraction of direct sunlight. We also use ray tracing to illustrate how edge effects can significantly change the amount of sunlight reaching the upper and lower modules; these results underscore the complications of using measurements from small test facilities to predict the behavior of large PV fields.

McIntosh, Keith↗
DOE OSTI2020

Reliability Analysis of Field-aged Glass/Glass PV Modules: Influence of Different Encapsulant Types

This paper presents a preliminary reliability analysis of field-aged glass/glass (G/G) PV modules. Several characterization tests were performed on more than 60 modules with two different encapsulant types (EVA and ionomer) exposed in hot-dry Arizona (AZ) climate over 10-35 years. The common degradation mode observed in both encapsulant types was the delamination of encapsulant along with encapsulant browning (EVA only), glass cracking (EVA only), and metallic corrosion over junction box area (ionomer only). The EVA encapsulated G/G modules showed the higher median power degradation rate at 0.91-1.99%/yr whereas modules with ionomer showed the lower at 0.21%/yr.

photovoltaic, failures, field exposed, glass/glass↗
DOE OSTI2024

Deep Learning-Based Failure Prognostic Model for PV Inverter Using Field Measurements

Here, this study presents a novel approach for the precise monitoring and prognosis of photovoltaic (PV) inverter status, which is crucial for the proactive maintenance of PV systems. It addresses the gaps in traditional model-based methods, which tend to neglect the overall reliability of inverters, and the limitations of data-driven approaches that largely depend on simulated data. This research presents a robust solution applicable to real-world scenarios. The proposed data-driven model for PV inverter failure prognosis employs actual inverter measurements, integrating various operational and weather-related factors based on domain knowledge. This approach effectively represents inverter stressors and operational status. Utilizing an Enhanced Siamese Convolutional Neural Network (ESCNN), the model merges operational data with domain knowledge features, redefining the prognosis challenge as a classification task. Furthermore, the paper discusses an ESCNN-based real-time inverter failure monitoring method developed on the well-trained model. The proposed models are rigorously trained and tested with real inverter data and a novel filtering method is included to address accidental failures in practical scenarios. The results validate the model's efficacy, and the directions for future research are also outlined.

42 ENGINEERING↗
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 OSTI2022

Field Experience Detecting PV Underperformance in Real Time Using Existing Instrumentation

Maintenance at large-scale photovoltaic plants employs a mix of preventative and corrective maintenance practices. Large outages, such as an inverter tripping offline, are often easy to detect. More subtle sub-inverter faults and failures can accumulate and go unnoticed for months or years. A software-based fault detection method has been developed to analyze commonly measured data from large-scale PV plants for more timely detection of subtle underperformance. The method has been demonstrated on eight datasets from large-scale plants with high accuracy of detection. Results are validated using aerial infrared scanning. String outages are detected with a true positive rate of 73 percent and tracker issues are detected with a true positive rate of 88 percent. The developed method can be uniformly applied to photovoltaic plants across a range of scales and configurations to assess performance, quickly detect underperformance, and determine the source and location of failures. The results inform and improve operations and maintenance at PV plants, ultimately aiding in improved affordability, reliability, availability, and resiliency of solar electricity.

14 SOLAR ENERGY↗