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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Presenting a Model to Predict Changing Snow Albedo for Improving Photovoltaic Performance Simulation

As photovoltaic (PV) deployment increases worldwide, PV systems are being installed more frequently in locations that experience snow cover. The higher albedo of snow, relative to the ground, increases the performance of PV systems in northern and high-altitude locations by reflecting more light onto the PV modules. Accurate modeling of the snow’s albedo can improve estimates of PV system production. Typical modeling of snow albedo uses a simple two-value model that sets the albedo high when snow is present, and low when snow is not present. However, snow albedo changes over time as snow settles and melts and a binary model does not account for transitional changes, which can be significant. Here, we present and validate a model for estimating snow albedo as it changes over time. The model is simple enough to only require daily snow depth and hourly average temperature data, but can be improved through the addition of site-specific factors, when available. We validate this model to quantify its ability to more accurately predict snow albedo and compare the model’s performance against satellite imagery-based methods for obtaining historical albedo data. In addition, we perform modeling using the System Advisor Model (SAM) to show the impact of changes in albedo on energy modeling for PV systems. Overall, our albedo model has a significantly improved ability to predict the solar insolation on PV modules in real time, especially on bifacial PV modules where reflected irradiance plays a larger role in energy production.

Pike, Christopher (ORCID:0000000155888033)↗
DOE OSTI2020

Optical Transmission Spectroscopy of the Terrestrial Exoplanet LHS 3844b from 13 Ground-based Transit Observations

Atmospheric studies of spectroscopically accessible terrestrial exoplanets lay the groundwork for comparative planetology between these worlds and the solar system terrestrial planets. LHS 3844b is a highly irradiated terrestrial exoplanet (R = 1.303 ± 0.022R {sub ⊕}) orbiting a mid-M dwarf 15 parsecs away. Work based on near-infrared Spitzer phase curves ruled out atmospheres with surface pressures ≥10 bars on this planet. We present 13 transit observations of LHS 3844b taken with the Magellan Clay telescope and the LDSS3C multi-object spectrograph covering 620–1020 nm. We analyze each of the 13 data sets individually using a Gaussian process regression, and present both white and spectroscopic light curves. In the combined white light curve we achieve an rms precision of 65 ppm when binning to 10 minutes. The mean white light-curve value of (R {sub p}/R {sub s}){sup 2} is 0.4170 ± 0.0046%. To construct the transmission spectrum, we split the white light curves into 20 spectrophotometric bands, each spanning 20 nm, and compute the mean values of (R {sub p}/R {sub s}){sup 2} in each band. We compare the transmission spectrum to two sets of atmospheric models. We disfavor a clear, solar composition atmosphere (μ = 2.34) with surface pressures ≥0.1 bar to 5.2σ confidence. We disfavor a clear, H{sub 2}O steam atmosphere (μ = 18) with surface pressures ≥0.1 bar to low confidence (2.9σ). Our observed transmission spectrum favors a flat line. For solar composition atmospheres with surface pressures ≥1 bar we rule out clouds with cloud-top pressures of 0.1 bar (5.3σ), but we cannot address high-altitude clouds at lower pressures. Our results add further evidence that LHS 3844b is devoid of an atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Getting their days in the sun

Although metal halide perovskite solar cells are extensively investigated in the lab their performance and degradation in real-world outdoor conditions are still poorly understood. Now, researchers propose a method to analyse field data to identify how and why the outdoor device performance changes over time.

14 SOLAR ENERGY↗
DOE OSTI2023

PV Performance Modeling - Data and Resources

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. This dataset includes seven MS-Excel sheets with instructions, notes and all necessary data (weather, irradiance, temperature, power) used for the data analysis of the blind modeling comparison. The hourly data represent six different systems from Albuquerque, NM and Roskilde, Denmark over a period of one year. These data are useful for PV performance model validation studies.

14 SOLAR ENERGY↗
DOE OSTI2021

Impact of Aerosol and Cloud on the Solar Energy Potential over the Central Gangetic Himalayan Region

We examine the impact of atmospheric aerosols and clouds on the surface solar radiation and solar energy at Nainital, a high-altitude remote location in the central Gangetic Himalayan region (CGHR). For this purpose, we exploited the synergy of remote-sensed data in terms of ground-based AERONET Sun Photometer and satellite observations from the MODerate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat Second Generation (MSG), with radiative transfer model (RTM) simulations and 1 day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). Clouds and aerosols are one of the most common sources of solar irradiance attenuation and hence causing performance issues in the photovoltaic (PV) and concentrated solar power (CSP) plant installations. The outputs of RTM results presented with high accuracy under clear, cloudy sky and dust conditions for global horizontal (GHI) and beam horizontal irradiance (BHI). On an annual basis the total aerosol attenuation was found to be up to 105 kWh m –2 for the GHI and 266 kWh m –2 for BHI, respectively, while the cloud effect is much stronger with an attenuation of 245 and 271 kWh m –2 on GHI and BHI. The results of this study will support the Indian solar energy producers and electricity handling entities in order to quantify the energy and financial losses due to cloud and aerosol presence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Coupled Experimental and High-Temperature Discrete-Element Method Modeling Studies of Aluminosilicate Particle Handling in Concentrated Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrated solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrated solar power environments. Coupled experimental and numerical studies of aluminosilicate particles in rotary kilns and dense particle curtains were performed for bulk temperatures up to 1073 K. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Temperature, spatial, and velocity profile data were extracted from experimental runs using embedded K-type thermocouple probes and particle image velocimetry techniques. Experimental and numerical studies were compared using spatial temperature profiles, velocity fields, and shape profiles of the bulk, granular flows. Numerical models were developed using commercially available discrete element method modeling software, Aspherix®. Existing Aspherix® functionality was expanded by introducing coupled radiative exchange modeling tools. The laboratory-scale rotary kiln was developed to investigate the steady-state heat and mass transfer performance of aluminosilicate particles based on particle type, bulk handling temperature, and wall roughness. The rotational speed of the rotary kiln was varied to control the relative impact of collisional and frictional effects upon the granular flow behavior. Heat and mass transfer performance was categorized based on the Froude number and the observed flow regimes of slipping, rolling, cascading, and centrifuging. Coupled discrete element method modeling studies were used to evaluate the effects of temperature-dependent, particulate mechanical properties upon bulk flow behavior and upon the relative effects of radiative, advective, and/or conductive heat transfer. A high-temperature (< 1073 K) falling particle curtain was similarly fabricated to investigate the heat and mass transfer performance of aluminosilicate particles in particle handling situations dominated by inter-particle collisions. The impact of particle type, flow preheat temperatures (< 1073K), and bulk mass flow rates were investigated upon the particle curtain shape, temperature, and velocity profiles. Coupled discrete element method modeling studies were performed to evaluate the varying impact of temperature-dependent, particulate mechanical properties on the bulk flow behavior and the temperature profile of the particle curtain.

14 SOLAR ENERGY↗
DOE OSTI2021

Outdoor performance of a tandem InGaP/Si photovoltaic luminescent solar concentrator

Here, we report the design, fabrication and outdoor characterization of a tandem luminescent solar concentrator/Si multi-junction photovoltaic module. Our tandem LSC/Si device consists of an InGaP LSC functioning as a top cell and a passivated contact Si bottom cell. The LSC comprises of an InGaP microcell array coupled to a polymer waveguide, loaded with CdSe/CdS core-shell quantum dot luminophores. The light trapping efficiency of the LSC waveguide is enhanced by encapsulation with photoluminescence trapping mirrors consisting of dielectric multilayer thin films. We demonstrate the performance of the LSC/Si device through a series of outdoor tests under various irradiance conditions conducted at the National Renewable Energy Laboratory. We report the first outdoor testing data of an LSC/Si tandem module, displaying maintained performance across varied diffusivity conditions for the LSC component. Finally, we model the tandem module performance using a ray optic simulation-based multiphysics model and forecast a pathway for high efficiency tandem LSC/Si module performance.

14 SOLAR ENERGY↗
DOE OSTI2025

Experimental Study of a Novel Semi-Transparent Bi-Facial Agri-Voltaic System: Initial Results

Solar (photovoltaic)-agriculture practices have experienced notable progress across several countries over the past few decades, creating a field widely known as agrivoltaics. This co-location practice has proved effective for certain crops that prefer partial shade like tomatoes, lettuce, and peppers, although it is less effective for crops needing more sun. Availability of natural sunlight with a specific spectral signature is necessary for agricultural practices as many plant species require an optimum-level and quality of sunlight for photosynthesis. The goal of this work is to model and validate ground-level irradiance for a semi-transparent bifacial solar collector equipped with a custom spectral reflector. By introducing intentional gaps between opaque solar cells, we hope to allow 50% of visible light to pass through the module. Additionally, this technology could reduce the soil temperature by 2° C, improve moisture retention, and enhance yield by providing partial solar radiation. In our model, we can calculate the total solar irradiance for the plants as a function of the cell distribution, material absorption, height of the panel and time of year with a spatial resolution of 0.0625 m2. When comparing theoretical estimates to experimental measurements of photosynthetically active radiation (PAR), we find a discrepancy of 32-48%, and a discrepancy of 19-38% after correction with TMY data.

McGraw, Duncan (ORCID:0000000256388118)↗
DOE OSTI2020

The Case for Custom TMY's: Examples Using the NSRDB

A typical meteorological year (TMY) data set essentially represents an hourly compilation of median months constructed using multi-year datasets. Although TMY data sets are generated from irradiance data in the horizontal plane, they are used in photovoltaic (PV) modeling for systems inclined to various angles. This paper demonstrates that a POA TMY (plane of array TMY) generated by selecting median months from a multi-year POA irradiance timeseries dataset produces significantly different results than a POA TMY generated by transposing a TMY dataset constructed from horizontal data. In some months the differences can be more than 3%. These results point to the need for generating TMY's using POA irradiance timeseries representing the orientation at which PV panels will be deployed.

14 SOLAR ENERGY↗
DOE OSTI2024

Hourly dynamic line ratings for existing transmission across the contiguous United States (preliminary results) [Slides]

The thermal rating of a transmission line depends on the rate at which heat generated by current flow through the line can be dissipated into the environment by convective and radiative cooling, keeping the conductor below a maximum operating temperature. Static or seasonal line ratings assume nearly-worst-case weather conditions (high ambient air temperature, high solar irradiance, and low wind speed), resulting in a low risk of "overrating" a line (i.e., allowing more current to flow than the line is designed for) but a high fraction of time when the line is "underrated" (i.e., able to flow more current while staying below the maximum temperature). Dynamic transmission line ratings (DLR) use real-time measurements of weather conditions, line sag, or line temperature to determine the thermal rating of transmission lines at hourly or higher time resolution, allowing for increased ratings during some (cold, windy, and/or dark) periods and correcting for overrating during other (hot, calm, and/or sunny) periods. Many studies have explored the benefits of DLR, but typically for small collections of transmission lines under a limited sample of weather conditions, leaving open the question of how widely applicable the benefits of DLR might be over diverse geographies and weather conditions. Here, we combine geospatial data on tens of thousands of transmission line routes across the contiguous United States with high-resolution hourly historical weather data for 2007-2013 to estimate the impact of DLR and other weather-adjusted rating systems. We compare static and dynamic line ratings to intermediate ratings adjusted by ambient temperature, day/night irradiance, clear-sky irradiance, and/or measured irradiance, illustrating the benefits of incorporating progressively more detailed weather data into the calculated line ratings. Moving from nighttime-adjusted ratings to clear-sky-adjusted ratings provides more benefit than moving from clear-sky-adjusted ratings to measured-irradiance-adjusted ratings. Depending on the assumed static windspeed for irradiance-adjusted-ratings, DLR either corrects for overrated hours or provides substantially increased ratings in the majority of hours on the majority of lines.

14 SOLAR ENERGY↗
DOE OSTI2022

The WRF-Solar Ensemble Prediction System: Development, Test, and Validation

Providing reliable probabilistic solar radiation information is needed to improve management of the uncertainty and variability of solar generation. Thus, guidance on how to develop skillful and accurate ensemble forecasts is essential and it will ultimately contribute to integration of high amounts of solar energy on the grid. A team from the National Renewable Energy Laboratory and the National Center for Atmospheric Research had been collaborating to develop the WRF-Solar ensemble prediction system (WRF-Solar EPS) in the past three years to produce probabilistic solar irradiance forecasts and better predict solar energy by quantifying forecast uncertainty. The WRF-Solar EPS basically generates ensemble members for solar irradiance based on stochastic perturbations to provide intraday and day-ahead probabilistic forecasts. This study will present main research steps in developing the WRF-Solar EPS including: (a) tangent linear analysis for identifying key input variables of six WRF-Solar modules significantly related to predicting of cloud and solar irradiance, (b) combining stochastic perturbation technique with the WRF-Solar model, and (c) ensemble calibration method to decrease error and uncertainty of ensemble-based solar forecasts. The capability of WRF-Solar EPS is now updated to the most recent version of standard WRF model. This presentation will summarize comprehensive results from the evaluation of forecasts against the National Solar Radiation Data Base as well as ground-measured observations. Moreover, we will introduce the user's guide for WRF-Solar EPS (e.g., parameters to configure stochastic perturbations) and future extension of this research.

day-ahead forecast↗
DOE OSTI2024

Ocean surface radiation measurement best practices

Ocean surface radiation measurement best practices have been developed as a first step to support the interoperability of radiation measurements across multiple ocean platforms and between land and ocean networks. This document describes the consensus by a working group of radiation measurement experts from land, ocean, and aircraft communities. The scope was limited to broadband shortwave (solar) and longwave (terrestrial infrared) surface irradiance measurements for quantification of the surface radiation budget. Best practices for spectral measurements for biological purposes like photosynthetically active radiation and ocean color are only mentioned briefly to motivate future interactions between the physical surface flux and biological radiation measurement communities. Topics discussed in these best practices include instrument selection, handling of sensors and installation, data quality monitoring, data processing, and calibration. It is recognized that platform and resource limitations may prohibit incorporating all best practices into all measurements and that spatial coverage is also an important motivator for expanding current networks. Thus, one of the key recommendations is to perform interoperability experiments that can help quantify the uncertainty of different practices and lay the groundwork for a multi-tiered global network with a mix of high-accuracy reference stations and lower-cost platforms and practices that can fill in spatial gaps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Photovoltaic Data Acquisition (PVDAQ) Public Datasets

The NREL PVDAQ is a large-scale time-series database containing system metadata and performance data from a variety of experimental PV sites and commercial public PV sites. The datasets are used to perform on-going performance and degradation analysis. Some of the sets can exhibit common elements that effect PV performance (e.g. soiling). The dataset consists of a series of files devoted to each of the systems and an associated set of metadata information that explains details about the system hardware and the site geo-location. Some system datasets also include environmental sensors that cover irradiance, temperatures, wind speeds, and precipitation at the site.

Array↗
DOE OSTI2021

A Method for Estimating Time-Series PV Production Loss From Solar Tracking Failures

Solar tracking system failures can dramatically reduce photovoltaic (PV) system energy output through suboptimal irradiance capture and self-shading loss. Detecting tracker failures is not always straightforward; unlike other common PV system failures like inverter outages and blown fuses which take portions of a system completely offline, tracker failures only partially reduce output power and can go unnoticed as a result. Additionally, tracker failures can take one of several forms, each with their own loss characteristics. Here we present two methods of detecting tracker failure events from time-series production data and a method for estimating the associated production loss. Compared with existing detection methods, the proposed power-based detection method showed 0-17% reductions in Type I error rate depending on weather conditions. Here, the loss model estimated production loss with low error (mean bias error = -2.3 %, root-mean-squared error = 6%) in a rudimentary validation.

14 SOLAR ENERGY↗
DOE OSTI2020

Global normal spectral irradiance in Albuquerque: a one-year open dataset for PV research

This report describes the creation process and final content of a spectral irradiance dataset for Albuquerque NM. The spectral irradiance measurements were made using a dual-axis tracker; therefore, they represent global normal irradiance. The dataset combines spectroradiometer and weather measurements from a two-year period into a continuous calendar year. The data files are accompanied by extensive metadata as well as example calculations and graphs to demonstrate the potential uses of this database.

14 SOLAR ENERGY↗
DOE OSTI2024

Equating Reference Cell and Broadband Pyranometer Data

An adjustment algorithm has been developed for broadband Class-A pyranometers, to modify the pyranometer data such that it more closely matches that of silicon-based reference cells. The adjustment algorithm uses modeled clear-sky spectral data as one of its inputs. The adjustment also uses a reference cell angle of incidence modifier. A comparison between the pyranometer and the reference cells is performed with and without the adjustment applied. The adjustment aligns the pyranometer and reference cell data to within +-2 % under clear skies when the zenith angle is less than 70 degrees .

incident angle modifier↗
DOE OSTI2026

PV Systems Modelling with Python

PVSC tutorial demonstrating how to download irradiance data and sun position for a specific location, determine the orientation of a single-axis tracker system, calculate Plane of Array irradiance, and estimate the power output of a PV system.

14 SOLAR ENERGY↗
DOE OSTI2020

Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing

A main challenge towards ensuring large-scale and seamless integration of photovoltaic systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high photovoltaic shares. The scope of this paper is to address this issue by presenting a unified methodology for hourly-averaged day-ahead photovoltaic power forecasts with improved accuracy, based on data-driven machine learning techniques and statistical post-processing. More specifically, the proposed forecasting methodology framework comprised of a data quality stage, data-driven power output machine learning model development (artificial neural networks), weather clustering assessment (K-means clustering), post-processing output optimisation (linear regressive correction method) and the final performance accuracy evaluation. The results showed that the application of linear regression coefficients to the forecasted outputs of the developed day-ahead photovoltaic power production neural network improved the performance accuracy by further correcting solar irradiance forecasting biases. The resulting optimised model provided a mean absolute percentage error of 4.7% when applied to historical system datasets. Finally, the model was validated both, at a hot as well as a cold semi-arid climatic location, and the obtained results demonstrated close agreement by yielding forecasting accuracies of mean absolute percentage error of 4.7% and 6.3%, respectively. Finally, the validation analysis provides evidence that the proposed model exhibits high performance in both forecasting accuracy and stability.

42 ENGINEERING↗