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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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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

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)↗
DOE OSTI2020

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)↗
DOE OSTI2024

DuraMAT: Building a Consortium to Accelerate the Photovoltaic Module Reliability Learning Cycle

Durable and reliable photovoltaic (PV) modules are critical to enabling an efficient transition to sustainable energy generation. The rate at which new module designs and materials are developed and deployed currently outpaces the rate at which we can identify failure mechanisms and understand degradation rates. Increasing the service life of PV modules, and our ability to predict performance over time, requires more durable materials and designs, better durability testing, more extensive material characterization, robust modeling, and methods to cross-examine historical performance data to extract meaningful results. This is a multidisciplinary challenge that requires expertise from a broad range of fields and, therefore, benefits significantly from a collaborative approach. In this Perspective, we outline the approach taken by the Durable Module Materials Consortium (DuraMAT), present a few case studies where our approach was successful, and provide an outlook on where this approach might be applied as the PV technology landscape continues to rapidly evolve. Published by the American Physical Society 2024

14 SOLAR ENERGY↗
DOE OSTI2021

Temperature Coefficients of Perovskite Photovoltaics for Energy Yield Calculations

Temperature coefficients for maximum power (TPCE), open circuit voltage (VOC), and short circuit current (JSC) are standard specifications included in data sheets for any commercially available photovoltaic module. To date, there has been little work on determining the TPCE for perovskite photovoltaics (PV). We fabricate perovskite solar cells with a TPCE of -0.08 rel %/°C and then disentangle the temperature-dependent effects of the perovskite absorber, contact layers, and interfaces by comparing different device architectures and using drift-diffusion modeling. A main factor contributing to the small TPCE of perovskites is their low intrinsic carrier concentrations with respect to Si and GaAs, which can be explained by its wider band gap. In this work, we demonstrate that the unique increase in Eg with increasing temperatures seen for perovskites results in a reduction in JSC but positively influences VOC. The current limiting factors for the TPCE in perovskite PV are identified to originate from interfacial effects.

14 SOLAR ENERGY↗
DOE OSTI2023

Model-Free Probabilistic Forecasting of Nodal Voltages in Distribution Systems

As the penetration of distributed energy resources (DERs) into distribution systems increases, so does the interest in forecasting relevant system variables to help mitigate the associated challenges. One such challenge is the more frequent occurrence of excessive voltages in distribution systems with higher shares of DERs. Accurate and reliable estimates together with forecasts of system states (i.e., nodal voltages) will therefore play a key role in improving the utilization of these variable and uncertain sources while mitigating potential operational risks. Whilst recent literature has explored machine learning (ML) methods for voltage estimation and their extrapolation for a short-time period into the future, few have taken uncertainty quantification into account, and these methods have not yet been translated into operations. This paper discusses the advantages offered by probabilistic voltage forecasts and proposes a non-parametric Bayesian method suitable for forecasting nodal voltages at short-term time horizons while accounting for uncertainties in load and distributed photovoltaic (PV) generation. We demonstrate the value of the proposed Gaussian process (GP) model for a case study using historical forecasts and observation data.

distribution system↗
DOE OSTI2020

Quantitative Prediction of Perovskite Stability Using Accelerated Testing and Machine Learning

PV technologies based on hybrid perovskites offer the potential for reducing solar cell costs, but they are particularly vulnerable to degradation by environmental factors such as moisture, oxygen, and illumination. Commercialization will require not only stable materials and device architectures but also accelerated testing protocols and models that can predict degradation from the accelerated testing data. Here, we report results from in situ photoluminescence (PL) and photoconductivity (PC) measurements during perovskite degradation with simultaneous optical transmittance (Tr) measurements or reflected dark field (DF) imaging. From PL, PC, Tr, and DF, we determine (respectively) the steady-state quasi-Fermi level splitting, the mean effective carrier diffusion length, the extent of conversion of perovskite to higher bandgap degradation products, and the extent of scattering from domains with different orientation or composition, all as a function of time during degradation. Simultaneous measurement of PL-PC-Tr or PL-PC-DF on perovskite absorbers in an environmental chamber over a wide range of humidity, oxygen, temperature, and illumination levels yields a rich data set. We use machine learning to develop a model that accurately predicts (within 10%) the time for the diffusion length to decrease to 85% of its initial value. The model takes the environmental conditions and the first few measurements from the PL-PC-Tr or PL-PC-DF experiment as input. Thus, the model provides a framework to interpret the results of accelerated testing of absorber materials. One of the dominant features in the model of degradation for CH 3 NH 3 PbI 3 is the initial rate at which transmittance increase. For devices with opaque contacts, the pixel-averaged rate of change of the intensity in dark-field images can be used in place of transmittance. Results are also presented on full PV devices with in-situ current-voltage (JV) measurements. Here, the data from simultaneous PL-DF-JV under environmental stresses reveal intimate connection between degradation and shunts and provide a framework to extend accelerated testing to devices. Further, the presentation reveals underlying universal behavior in degradation pathways over a broad range of environmental stresses and perovskite compositions.

14 SOLAR ENERGY↗
DOE OSTI2024

Distributed Wind Monitoring Best Practices

Accessible performance and operational data have been identified as a key enabler for distributed wind energy industry advancement. While utility-scale wind turbines benefit from reliable and continuous supervisory control and data acquisition (SCADA)-based monitoring platforms, monitoring of the U.S. fleet of distributed wind (DW) turbines has been more inconsistent, unreliable, and sometime difficult to access. Without fleet monitoring data, the industry will never understand and thus work to improve turbine under-performance and reliability issues. For the DW industry to scale up, attract investors, and boost credibility, fleetwide monitoring must be robust and reliable, select data must be made accessible to stakeholders, and the data must be in a format useful to users. To help move the industry toward a more standardized, accessible stream of monitoring data, this distributed wind monitoring best practices report attempts to cover topics including key monitoring channels, hardware, communication strategies, and accessibility. Strategic engagement with DW original equipment manufacturers (OEMs), service providers, lab and university researchers, testing organization, certification bodies, end users and solar photovoltaic (PV) monitoring experts has enabled a better understanding of the current state-of-the-art of monitoring and aided in articulating this set of best practices that will guide OEMs toward harmonized monitoring strategies, aimed at a future goal of achieving accessible performance and operational data for the entire fleet of U.S. distributed wind turbines.

17 WIND ENERGY↗
DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.8% and 1.2% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.8% and 2.7% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2020

Robust and resilient coordination of feeders with uncertain distributed energy resources: from real-time control to long-term planning

To enable flexible demand and ensure reliable and economical operation of distribution systems, we present a novel hierarchical scheme that actively coordinates responsive behind-the-meter grid resources, including distributed energy resources (DERs), to reliably manage each unbalanced distribution feeder and exploits the available flexibility to economically optimize the entire network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

14 SOLAR ENERGY↗
DOE OSTI2020

BACKFLIP Project: Determination of BACKsheet Material Properties: A Comparison of Market-Benchmark Technologies to Novel Non-Fluoro-Based Co-Extruded Backsheet Materials and Their Correlation and Impact on PV Module Degradation Rates

Quantifying degradation rate of backsheets will help procuring materials for 30+ years. Today most backsheets on the market have a laminated PET core; polyolefin materials may provide better properties for backsheets (barrier to water, mechanical properties through UV and hydrolytic environments, etc.). End-of-life regulations may require fluorine-free backsheet products in future global markets. Parametrized equation predicting the service life of backsheets, and validated by both lab and outdoor extensive testing. Technical and commercial confidence to the entire value chain: from backsheet and module manufacturers to the downstream community (IPP, banks, developers) that materials of higher quality can help reduce finance costs, therefore driving down LCOE. A fast track PV module market adaptation for novel high-quality materials, such as co-extruded polyolefin-core backsheets, by obtaining unbiased durability data.

14 SOLAR ENERGY↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections: Preprint

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.6\% and 1.1\% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.4\% and 2.5\% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2020

Puerto Rico Solar-for-All: LMI PV Rooftop Technical Potential and Solar Savings Potential

The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level. Each dataset is broken out by income group, defined by the Area Median Income (AMI), by tenure, and by building type. The underlying LiDAR data used the estimation were collected in 2015-2017 and the American Community Survey (ACS) data are from 2011-2015. This Puerto Rico Solar-For-All dataset is intended to extend the SEEDSII Solar-For-All estimates for the US 50-states ( https://www.nlr.gov/docs/fy18osti/70901.pdf ) for the territory of Puerto Rico using updated methods. Please see the data documentation for details.

14 SOLAR ENERGY↗
DOE OSTI2026

Data for "Gold-Induced Chemical Perturbations in CdTe-Based Photovoltaic Cells"

Back contacting p-type CdTe has been identified as one of the major areas of loss in CdTe photovoltaic (PV) power conversion efficiency (PCE). In research settings, Au is a common contact material due to its ease of use and decent performance. This work provides a detailed investigation into using gold for back contacting As-doped, CdCl2 treated, polycrystalline CdTe that has been exposed to air after absorber processing, another routine practice. First, X-ray photoemission spectroscopy (XPS) is used to determine the native oxide to be 1.6 nm of CdTeO3 using a combination of angle-resolved XPS and the cadmium modified Auger parameter. During gold metallization of CdTe, oxygen and oxidized tellurium are eliminated from the thin CdTeO3 native oxide. The fate of the released oxygen and possibly cadmium and tellurium are not known, but these reaction byproducts can enter the absorber bulk or grain boundaries, stay at the interface, or dissolve in the Au. Interfacial hole barriers between CdTe and Au are measured for samples with and without the native oxide present prior to metallization. Results show that the thin CdTeO3 alleviates the downward band bending by 40 meV from 470 meV to 430 meV even though it is consumed during interface formation. The implications of these chemical reactions on the device are assessed through photoluminescence (PL) spectroscopy which shows losses in internal open circuit voltage (iVoc) from 820 meV to 795 meV, carrier lifetime from 123 ns to 45 ns, and PL quantum yield from 2.9x10-5 to 1.2x10-5. Modeling time-resolved PL lifetimes demonstrates the back surface recombination velocity due to metallization reduces minority carrier lifetimes. These results identify the native oxide and show that it plays an important role in mediating downward band bending along with how the back interface reaction can negatively impact device-scale parameters and reduce PV PCE.

14 SOLAR ENERGY↗
DOE OSTI2021

Coordinated Inverter Control to Increase Dynamic PV Hosting Capacity: A Real-Time Optimal Power Flow Approach

High penetrations of distributed photovoltaics (PV) could cause adverse grid impacts, such as voltage violations. The recent development in inverter technologies provides the opportunity to develop control systems to realize effective PV governance and thus to improve dynamic PV hosting capacity for distribution grids. In this paper, a novel distributed energy resource management system (DERMS) solution is proposed by adopting the real-time optimal power flow (OPF) approach for coordinated control of the distributed PV inverters. The proposed approach eliminates the dependence on load knowledge via measurement feedback correction, and it can be implemented in real time. One challenge is that the technique is sensitive to the data availability and integrity of voltage measurements. Therefore, a decentralized DERMS approach is developed by leveraging the concepts of state estimation. The framework and the effectiveness of the solution approach are numerically demonstrated on a real distribution feeder in Southern California.

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling diurnal and annual ethylene generation from solar-driven electrochemical CO 2 reduction devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards reducing carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimentally-determined CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. Here we simulated gaseous diurnal product outputs with and without the effects of ambient temperature. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne per year at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

14 SOLAR ENERGY↗
DOE OSTI2026

PV Durability at Scale: Assessing Bifacial and TOPCon Field Performance

Recent field performance results of TOPCon and PERC Bifacial modules are presented based on small-scale deployments at NLR, and a selection of 3rd-party residential data. Bifacial PERC degradation rates are a median of -1 % / yr with bifacial TOPCon modules at a similar rate of -1.1 %/yr over the first couple of years. Comparable PERC Monofacial modules have a degradation rate of -0.5%/yr. Some TOPCon modules exhibited an indoor dark metastability effect which requires recovery by light soaking or UV exposure prior to IV curve measurement. Further monitoring is needed to confirm the long-term stability of TOPCon modules.

14 SOLAR ENERGY↗
DOE OSTI2021

R&D to Ensure a Scientific Basis for Qualification Tests and Standards (Final Report: FY19-FY22)

This is the final technical report for the FY19-FY21 research program "R&D to Ensure a Scientific Basis for Qualification Tests and Standards." This research was performed because project return on investment in a photovoltaic (PV) system depends increasingly on maintaining high energy yields, and the system lifetime is a major factor in levelized cost of electricity (LCOE). Thus, the rate of PV deployment and the success of these assets depends upon reliable long-term power generation. This program advances PV module reliability of commercial products through identification of reliability needs, characterization that provides scientific understanding of targeted degradation mechanisms, and translation of those data into practical and predictive test protocols and standards. This report describes program scope, results, milestones, and accomplishments over the three-year period of performance.

14 SOLAR ENERGY↗