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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Solar PV

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) research platform. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence data centers and other variable loads. This dataset entry describes the behavior of a 1.25-MW proton exchange membrane MC250 electrolyzer system, manufactured by Nel Hydrogen , [1] when fed historical data generated by the 430-kW, fixed-axis solar photovoltaic (PV) array located at NLR’s Flatirons Campus. (While the electrolyzer balance of plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.) Solar PV power output data for the 2020 calendar year were categorized on a daily basis by total energy generation and standard deviation. Each day was then ranked by these metrics, and the 25th, 50th, and 100th percentiles were selected. The 75th percentile day did not exhibit sufficient variability to make for a valuable experiment. A similar process was used for the related historical wind dataset . [2] The historical days in 2020 that represented these percentiles are Dec. 19, March 29, and May 4, respectively. The entire solar day’s power profile was then fed through the MC250 electrolyzer. Due to its length, the 100th percentile day experiment was split into two parts, and the final 3 hours of the solar day were not captured. These final 3 hours contained no spikes or dips of interest and simply represented a slow decay of input solar power. Also, a single timestamp (13:13:47 on Jan. 14, 2026) was lost in the hydrogen system supervisory control and data acquisition. Finally, during the 25th percentile experiment (solar day Dec. 19, 2020) data recording was lost from 11:00:13 to 11:14:45. The roughly 15 minutes of the solar profile were rerun at the end of the experiment and spliced into this time slot during post-processing. The electrolysis system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operation of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical solar profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. For more details on the statistical analysis process, see the slide deck “Public Reference Data for Megawatt-Scale Hydrogen Electrolysis: NLR Historical Solar PV Analysis and Profile Generation” accessible with this data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single solar PV electrolysis experiment and is formatted as: {technology}_{percentile}_{scaling factor} For instance, “solarPV-430kW_25_2x.zip” reports the experiment using the 25th percentile solar data from the historical 2020 solar PV dataset, scaled to 200%. Scaling factors were applied to the generated solar PV power output files to more closely match the 1.25-MW capacity of the electrolyzer. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and solar power input. A PDF file detailing the historical solar data statistical analysis used to generate the solar profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all experiments combined into one dataset labeled "combined_solarPV_experiments.csv". [1] nelhydrogen.com/product/mc-series-electrolyser . [2] data.nlr.gov/submissions/316 .

08 HYDROGEN↗
NASA NTRS1999

Comment on "The Predicted Size of Cycle 23 Based on the Inferred three-cycle Quasiperiodicity of the Planetary Index Ap"

Recently, Ahluwalia reviewed the solar and geomagnetic data for the last 6 decades and remarked that these data "indicate the existence of a three-solar-activity-cycle quasiperiodicity in them." Furthermore, on the basis of this inferred quasiperiodicity, he asserted that cycle 23 represents the initial cycle in a new three-cycle string, implying that it "will be more modest (a la cycle 17) with an annual mean sunspot number count of 119.3 +/- 30 at the maximum", a prediction that is considerably below the consensus prediction of 160 +/- 30 by Joselin et al. and of similar predictions by others based on a variety of predictive techniques. Several major sticking points of Ahluwalia's presentation, however, must be readdressed, and these issues form the basis of this comment. First, Ahluwalia appears to have based his analysis on a data set of Ap index values that is erroneous. For example, he depicts for the interval of 1932-1997 the variation of the Ap index in terms of annual averages, contrasting them against annual averages of sunspot number (SSN), and he lists for cycles 17-23 the minimum and maximum value of each, as well as the years in which they occur and a quantity which he calls "Amplitude" (defined as the numeric difference between the maximum and minimum values). In particular, he identifies the minimum Ap index (i.e., the minimum value of the Ap index in the vicinity of sunspot cycle minimum, which usually occurs in the year following sunspot minimum and which will be called hereafter, simply, Ap min) and the year in which it occur for cycles 17 - 23 respectively.

Wilson, Robert M.↗
DOE OSTI2025

Deliverable 6.7-Final Technical Report: Development Summary and Evaluation of the Solar Uncertainty Integrator (SUNI) Software

The Data Quality and Uncertainty Integration Project was a three-year effort to address stakeholder needs for assessing solar radiation resource data quality based on existing tools for estimating radiometer measurement uncertainties and assessing post-measurement data quality. The annual research objectives for the project addressed a logical progression of effort needed to achieve the ultimate project goal of developing the Solar Uncertainty Integrator (SUNI) software. This final technical report summarizes the development process for achieving these key research objectives and addresses the outreach and code development efforts in the final year of the project to develop a new solar irradiance data uncertainty integration software package.

14 SOLAR ENERGY↗
NASA NTRS1978

Utilization of independent solar flux measurements to eliminate nongeochemical variation in X-ray fluorescence data

It is shown that the direct method of solar activity correction for lunar XRF data produces XRF data with better statistics than uncorrected data. Direct measurements of the solar flux made by Solrad 10 are converted to emissions of the sun from two assumed temperature regions. These emissions are ratioed to produce emission measure ratios, sensitive indicators of shifts in solar activity. The Tucker-Koren model (1971) of the solar flux is used in the calculation of EMRs and in the calculation of theoretical lunar Si, Al, and Mg fluorescence of maria and highland soils. Al/Si(Mg/Si) ratios calculated at a 'normal' EMR of 0.030 are divided by Al/Si(Mg/Si) ratios at particular EMRs. The relationship between EMR and the quotients of this division, called 'correction factors', is well explained by empirically derived power law functions.

Clark, P. E.↗
DOE OSTI2025

Q1-2025 Solar Photovoltaic System Cost Benchmarks

The U.S. Department of Energy’s solar office and its national laboratory partners analyze cost data for U.S. solar photovoltaic systems to develop cost benchmarks to measure progress toward goals and guide research and development programs. The cost data is available in an Excel spreadsheet model that can be downloaded here.

14 SOLAR ENERGY↗
NASA NTRS1977

Operations manual: On Site Monitor (OSM), solar heating and cooling systems

The on-site monitor is a portable device which, when connected to a solar system site data acquisition subsystem; allows readouts of clock and sensor data in voltage or engineering units at instrumented solar heating and cooling sites. The unit is described and procedures for its proper operation are presented.

Source record↗
NASA NTRS1984

Solar Total Irradiance Variability Measurements by the SMM/ACRIM I Experiment

Convincing evidence of solar total irradiance variability and its relationships with solar activity was provided by the Active Cavity Radiometer Irradiance Monitor I (ACRIM I) experiment on the NASA Solar Maximum Mission (SMM). SMM/ACRIM I, the first flight experiment dedicated to the task of solar irradiance monitoring, has produced a multiyear solar total irradiance data base with + or - 0.02% or better long term precision since its launch in February, 1980. While the climatological significance of the results will not be apparent until many more years of continuous data are acquired, the discovery of variability on solar active region time scales has provided new insight into the physics of solar activity in the early years of the mission.

Willson, R. C.↗
NASA NTRS1990

The ACRIM data in the context of stellar variability

The Active Cavity Radiometer Irradiance Monitor (ACRIM) total-irradiance data from the Solar Maximum Mission have given a first comprehensive view of solar variability in the stellar sense. Five types of solar variability have been identified thus far. These have small amplitudes, less than a few tenths of one percent, and are at levels generally not yet detectable on other stars. The possible stellar analogs are interesting physically, and in particular may help us to understand solar behavior on longer time scales. The ACRIM data is described from the stellar point of view. The present state of stellar time-series photometry is discussed.

Hudson, Hugh S.↗
NASA NTRS1998

Comment on the Predicted Size of Cycle 23 Based on the Inferred Three-Cycle Quasi-Periodicity of the Planetary Index Ap

Recently, Ahluwalia [1998] reviewed the solar and geomagnetic data for the last 6 decades and remarked that these data "indicate the existence of a three-solar-activity-cycle quasi-periodicity in them." Futhermore, on the basis of this inferred quasi-periodicity, he asserted that cycle 23 represents the initial cycle in a new 3-cycle string, implying that it "will be more modest (a la cycle 17) with an annual mean sunspot number count of 119.3 +/- 30 at the maximum," a prediction that is considerably below the consensus prediction of 160 +/- 30 by Joselyn et al. [1997] and of similar predictions by others based on a variety of predictive techniques. Several major sticking points of Ahluwalia's presentation, however, must be redressed, and these issues form the basis of this comment. In particular, it is shown that Ahluwalia used inappropriate values of the Ap index in his analysis, that the inferred 3-cycle relationship which Ahluwalia claims for both Ap and SSN does not exist for the previous 6-cycle interval (prior to cycle 17) for SSN, that his inferred fit is only of marginal statistical significance (having r = 0.81), and that two alternative precursor fits (both with r = 0.96 or greater) exist which strongly suggest that R max for cycle 23 will be much larger than forecast by Ahluwalia (namely, about 168-187). Thus, caution must be exercised in accepting Ahluwalia's findings.

Hathaway, David H.↗
NASA NTRS2006

Model Calculations of Solar Spectral Irradiance in the 3.7 Micron Band for Earth Remote Sensing Applications

Since the launch of the first Advanced Very High Resolution Radiometer (AVHRR) instrument aboard TIROS-N, measurements in the 3.7 micron atmospheric window have been exploited for use in cloud detection and screening, cloud thermodynamic phase and surface snow/ice discrimination, and quantitative cloud particle size retrievals. The utility of the band has led to the incorporation of similar channels on a number of existing satellite imagers and future operational imagers. Daytime observations in the band include both reflected solar and thermal emission energy. Since 3.7 micron channels are calibrated to a radiance scale (via onboard blackbodies), knowledge of the top-of-atmosphere solar irradiance in the spectral region is required to infer reflectance. Despite the ubiquity of 3.7 micron channels, absolute solar spectral irradiance data comes from either a single measurement campaign (Thekaekara et al. 1969) or synthetic spectra. In this study, we compare historical 3.7 micron band spectral irradiance data sets with the recent semi-empirical solar model of the quiet-Sun by Fontenla et al. (2006). The model has expected uncertainties of about 2 % in the 3.7 pm spectral region. We find that channel-averaged spectral irradiances using the observations reported by Thekaekara et al. are 3.2-4.1% greater than those derived from the Fontenla et al. model for MODIS and AVHRR instrument bandpasses; the Kurucz spectrum (1995) as included in the MODTRAN4 distribution, gives channel-averaged irradiances 1.2-1.5 % smaller than the Fontenla model. For the MODIS instrument, these solar irradiance uncertainties result in cloud microphysical retrievals uncertainties comparable with other fundamental reflectance error sources.

Platnick, Steven↗
DOE OSTI2020

Sustainability, Feasibility, and Economics of a Fuel Cell-Powered Data Center

Data centers, used for cloud computing or data storage, consume huge amounts of power and are increasing rapidly in number, and consequently, this increase in power consumption has raised concerns with green and sustainable energy supplies to minimize carbon emissions. Significant renewable power can be a carbon-free energy source to reduce the carbon footprint of a data center; however, direct integration of wind and solar power with data center causes concern of the power quality for uninterrupted power supply to computer servers. The reliable power supply can be accomplished by using power produced from fuel cells fueled by hydrogen. If fed with hydrogen derived from renewable sources, fuel cells will realize carbon-free data centers. This presentation shows various renewable-integration scenarios to meet reliable and sustainable power requirements for a data center.

25 ENERGY STORAGE↗
NASA NTRS1991

High-resolution observations of the solar granulation

Digitally-enhanced high-resolution images from space and ground observatories have yielded data on the solar granulation which show it to be a more complex combination of phenomena than previously suspected. These new data have been used to detect large-scale horizontal flows over the solar surface through direct measurements of granule proper motions. The results thus obtained may have important implications for the heating of the solar chromosphere and corona. The observed intensity pattern on the surface of the sun is noted to be due not only to granulation, but the superposition of different types of waves as well. All such phenomena are modified in the presence of magnetic fields, becoming smaller and of reduced contrast.

Topka, K. P.↗
NASA NTRS1978

Indoor and outdoor tests of a liquid solar collector

Two reports describe thermal-performance data obtained on double-covered liquid solar collector. One report describes data obtained during outdoor testing and the other describes indoor test data obtained by using Marshall Space Flight Center solar simulator. Indoor data were taken to verify performance of solar simulator.

Losey, R.↗
NASA NTRS1978

Solar energy storage via liquid filled cans - Test data and analysis

This paper describes the design of a solar thermal storage test facility with water-filled metal cans as heat storage medium and also presents some preliminary tests results and analysis. This combination of solid and liquid mediums shows unique heat transfer and heat contents characteristics and will be well suited for use with solar air systems for space and hot water heating. The trends of the test results acquired thus far are representative of the test bed characteristics while operating in the various modes.

Saha, H.↗
NASA NTRS1985

Solar cell calibration facility validation of balloon flight data: A comparison of shuttle and balloon flight results

The Solar Cell Calibration Facility (SCCF) experiment was designed and built to evaluate the effect of the Earth's upper atmosphere on the calibration of solar cell standards. During execution of the experiment, a collection of carefully selected solar cells was flown on the shuttle, and reflown on a high-altitude balloon, then their outputs were compared. After correction to standard temperature and intensity values of 28 C and an Earth-Sun distance of 1 AU, the solar cell outputs during the two flights were found to be identical. The conclusion is therefore that the high-altitude balloon flights are very good vehicles for calibrating solar cells for use as space flight reference standards.

Anspaugh, B. E.↗
NASA NTRSDate not supplied

Advances in Modeling Solar System Internet Structures and their Data Flows

With an ever-increasing presence in space, there is also an increasing burden on existing communications infrastructure. We are heading towards an inflection point where the traditional approach of scheduled, single-path communications for space will no longer be viable. One answer is Delay Tolerant Networking (DTN), which takes the once disparate system of point-to-point links and unifies them in a networked architecture, thereby making communications more scalable. However, much work remains for discovering and harnessing the underlying theory of DTN. For example, in the terrestrial setting the interplay between routing domains is well-understood, however this is not the case in DTNs. In this paper, we build up the fundamental foundations of DTN, with an emphasis on modeling time varying networks and data flows across them, with examples of cross-domain routing in a DTN. A lofty goal of DTN is to enable the so-called Solar System Internet (SSI), which implies a standardized and robust suite of protocols. These protocols include routing across disconnected networks using store, carry, and forward mechanisms, which is necessary due to the disconnections, delays, and mobility intrinsic to space networks. Due to these factors, each of which generalize traditional networking, there is a deep and rich theory of DTNs. Here we build off of past successes to broaden this theory while striving to keep actionable results a goal for future implementations and operations. The approach includes modeling the unicast, broadcast, and multicast communications using the language of hypergraphs, which capture the geometric properties of such networked communications algebraically. Also inherent to these networks is their time-varying nature, particularly given mobility, and hence we also cultivate modeling techniques that respect this time dependence. This leads us to develop models using tools from category theory and algebraic geometry, which provide a language well-suited to describing synchronization and optimization over such networks. We also introduce and study a novel generalization of curvature applicable to time-evolving networks, which provides quantitative controls on diffusion processes on the network. Because an interplanetary network would feature links with propagation delays the preclude discovery (feedback) mechanisms, they will always feature a scheduled component. However, it is beneficial to support discovery where possible. While DTNs do not yet have strong definitions for their analogues of autonomous systems or network areas, we show how to join dynamic and schedule-based routing domains, using the language of sheaves, which marks progress towards such definitions. We conclude with a discussion of the progress made, as well as suggestions for future work.

Delay Tolerant Networking↗
NASA NTRS2011

Time-Distance Helioseismology Data-Analysis Pipeline for Helioseismic and Magnetic Imager Onboard Solar Dynamics Observatory (SDO-HMI) and Its Initial Results

The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) provides continuous full-disk observations of solar oscillations. We develop a data-analysis pipeline based on the time-distance helioseismology method to measure acoustic travel times using HMI Doppler-shift observations, and infer solar interior properties by inverting these measurements. The pipeline is used for routine production of near-real-time full-disk maps of subsurface wave-speed perturbations and horizontal flow velocities for depths ranging from 0 to 20 Mm, every eight hours. In addition, Carrington synoptic maps for the subsurface properties are made from these full-disk maps. The pipeline can also be used for selected target areas and time periods. We explain details of the pipeline organization and procedures, including processing of the HMI Doppler observations, measurements of the travel times, inversions, and constructions of the full-disk and synoptic maps. Some initial results from the pipeline, including full-disk flow maps, sunspot subsurface flow fields, and the interior rotation and meridional flow speeds, are presented.

Sun: helioseismology↗
DOE OSTI2022

Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series: Preprint

PV power and irradiance sensor-based measurements are prone to error, resulting in issues such as abrupt time series data shifts. These shifts, which are usually unintentional, may be caused by software or hardware configuration changes on a PV system, and do not reflect an actual change in overall system performance. Locating these shifts and segmenting the associated time series aids in more accurate future PV analysis. In this research, an offline changepoint detection (CPD) algorithm that automatically detects these abrupt data shifts in sensor-based time series is introduced. Data shift periods in 101 daily PV power and irradiance time series were labeled manually by two solar experts. These data streams represent sensor-based measurements, and display a variety of data shift behaviors. A changepoint detection algorithm was tuned using the 101 labeled data streams, with each model configuration's ability to detect labeled changepoints benchmarked using metrics such as F1-score, recall, and Rand Index. Best performing models on seasonality-corrected data streams include the Pruned Exact Linear (PELT) method, the Binary Segmentation method, and the Bottom-Up method, all scoring an average F1-score of 0.76 or greater at detecting labeled changepoints within a 30-day window for the labeled data sets. To promote further research in this space, we are releasing the labeled data shift sets on U.S. Department of Energy's (DOE) DuraMAT Data Hub, and the associated algorithm in the Python PVAnalytics package.

changepoint detection↗