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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Scientist-in-the-Loop Data Analytics Framework for Intelligent Simulation Model Tuning and Validation

This project developed a scientist-in-the-loop data analytics framework for intelligent simulation model tuning and validation, targeting the Weather Research and Forecasting (WRF) model and its solar energy variant, WRF-Solar-BNL. Domain experts, such as climate scientists, depend on large-scale numerical simulations for knowledge discovery and decision-making, yet the complexity of parameter tuning and the disconnect between automated optimization and domain expertise pose significant challenges. We extended an interactive visual analytics framework that enables domain experts to observe and intervene in the computational steering process by identifying disagreements between the simulation model, surrogate model, and the expert’s domain knowledge. Using Bayesian Optimization with Gaussian Process Regression as the surrogate model, our system allows users to probe parameter relationships, analyze correlation patterns, and adjust tuning parameters in real time. We developed use cases for solar irradiance forecasting through sustained collaboration with Brookhaven National Laboratory, resolving critical model configuration challenges and achieving meaningful reductions in prediction error. The project supported one PhD student, one MS student, and eight undergraduate students across three Data Science Capstone projects, resulting in one master’s thesis.

Dasgupta, Aritra [New Jersey Institute of Technolo↗
DOE OSTI2023

A Gridded Solar Irradiance Ensemble Prediction System Based on WRF-Solar EPS and the Analog Ensemble

The WRF-Solar Ensemble Prediction System (WRF-Solar EPS) and a calibration method, the analog ensemble (AnEn), are used to generate calibrated gridded ensemble forecasts of solar irradiance over the contiguous United States (CONUS). Global horizontal irradiance (GHI) and direct normal irradiance (DNI) retrievals, based on geostationary satellites from the National Solar Radiation Database (NSRDB) are used for both calibrating and verifying the day-ahead GHI and DNI predictions (GDIP). A 10-member ensemble of WRF-Solar EPS is run in a re-forecast mode to generate day-ahead GDIP for three years. The AnEn is used to calibrate GDIP at each grid point independently using the NSRDB as the “ground truth”. Performance evaluations of deterministic and probabilistic attributes are carried out over the whole CONUS. The results demonstrate that using the AnEn calibrated ensemble forecast from WRF-Solar EPS contributes to improving the overall quality of the GHI predictions with respect to an AnEn calibrated system based only on the deterministic run of WRF-Solar. In fact, the calibrated WRF-Solar EPS’s mean exhibits a lower bias and RMSE than the calibrated deterministic WRF-Solar. Moreover, using the ensemble mean and spread as predictors for the AnEn allows a more effective calibration than using variables only from the deterministic runs. Finally, it has been shown that the recently introduced algorithm of correction for rare events is of paramount importance to obtain the lowest values of GHI from the calibrated ensemble (WRF-Solar EPS AnEn), qualitatively consistent with those observed from the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2024

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

13 HYDRO ENERGY↗
DOE OSTI2020

Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM 2.5 , often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m 2 g –1 observed average) and light-scattering enhancement factor (ƒ(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm –3 in the model vs. observed average of 1.5 g cm –3 ) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

On neutrons from the sun

A survey of all the experiments carried out over the past decade to verify theoretical predictions for the observation of solar neutrons is presented and discussed. The conclusions drawn from this discussion are: (1) the Solar Probe Mission is important in order to discover the low energy neutrons of solar origin; (2) this discovery is likely to carry very useful information about the nature, the locale, the lifetime and the mode of operation of the acceleration processes in the solar atmosphere; and (3) this information will lead to a rapid development of the science of solar meteorology and the more rapid forecasting of solar activity, on a long-term basis.

Ahluwalia, H. S.↗
NASA NTRS1994

Quasi-stereoscopic imaging of the solar X-ray corona

The first published three-dimensional images of the solar X-ray corona obtained by means of solar rotational parallax, are presented in stereographic form. Image pairs approximately 12 hours apart during times of stable coronal conditions were selected from the digitized images obtained with the Skylab X-ray Spectrographic Telescope. The image resolution limit is approximately 10 arc sec. Many coronal structures not visible in the separate images are clearly observed when the image pairs are viewed stereoscopically. This method gives a preview of the potential resources for solar research and forecasting of solar-geomagnetic interactions that could be provided by stereoscopic observations of the Sun using a small group of spacecraft. The method is also applicable to other X-ray, ultraviolet, or other wavebands in which the corona has extended, transparent structure.

Batchelor, David↗
NASA NTRS2020

Understanding and Improving Model Representation of Aerosol Optical Properties for a Chinese Haze Event Measured During KORUS-AQ

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM2.5, often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m2 g−1 observed average) and light-scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm−3 in the model vs. observed average of 1.5 g cm−3) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation.

Pablo E. Saide↗
DOE OSTI2024

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2024

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
NASA NTRS2019

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

The dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extend from the interior to the corona and from fast turbulent motions to global magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across layers of the solar interior and atmosphere, which contribute to coronal heating and eruptive dynamics. For modeling global-scale activity, we use a data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitations on prediction accuracy, and we present the EnKF predictions of the upcoming Solar Cycle (25) based on both the sunspot number series and observed magnetic fields and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting solar activity.

Kitiashvili, I. N.↗
DOE OSTI2022

Machine Learning Derived Dynamic Operating Reserve Requirements in High-Renewable Power Systems

Accurately forecasting wind and solar power output poses challenges for deeply decarbonized electricity systems. Grid operators must commit resources to provide reserves to ensure reliable operations in the face of forecast errors, a process which can increase fuel consumption and emissions. We apply neural network-based machine learning to expand the usefulness of median point forecast data by creating probabilistic distributions of short-term uncertainty in demand, wind, and solar forecasts that adapt to prevailing grid conditions. Machine learning derived estimates of forecast errors compare favorably to estimates based on incumbent methods. Reserves derived from machine learning are usually smaller than values derived using incumbent methods, which enables fuel savings during most hours. Machine learning reserves are generally larger than incumbent reserves during times of higher forecast error, potentially improving system reliability. Performance is tested using multi-stage production simulation modeling of the California Independent System Operator (CAISO) system. Machine learning reserves provide production cost and greenhouse gas (GHG) emission reductions of approximately 0.3% relative to historical 2019 requirements. Savings in the 2030 timeframe are highly dependent on battery storage capacity. At lower levels of battery capacity, savings of 0.4% from machine learning reserves are shown. Significant quantities of battery storage are expected to be added to meet California's resource adequacy needs and GHG reduction targets. Addition of these batteries saturate reserve needs and results in minimal within-hour balancing costs in 2030.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

A review of short-term flare forecasting activities at Toyokawa

Short-term forecasting of solar activity conducted at Toyokawa is briefly reviewed. The forecasts are based on microwave observations of the slowly varying component of solar radiation associated with active regions. It was found that for proton flares which take place in intense active regions, it is possible to predict their occurrence with certain accuracy, but for a certain class of proton flares which occur in a small active region or which are associated with an active region, which evolves very rapidly, or for whose which occur behind the limb, it is almost impossible to forecast their occurrence.

Enome, S.↗
NASA NTRS1999

A Survey and Synthesis of Solar Cycle Prediction Techniques

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g. regression and curve-fitting, work well as solar activity approaches maximum and provide a complete description of future activity, while others, e.g. geomagnetic precursors, work well near solar minimum but only provide an estimate of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This Combined Precursor Method gives a smoothed sunspot number maximum of 154+/-21 at the 95% level of confidence for the next cycle maximum. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the next complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between previous activity levels and this function. This Combined Solar Cycle Activity Forecast gives, as of January 1999, a smoothed sunspot maximum of 146+/-20 at the 95% level of confidence for the next cycle maximum. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity which occurs many years later in the lower latitudes.

Hathaway, David H.↗
DOE OSTI2023

The Impact of Circumsolar Diffuse Radiation on the Numerical Computation and Forecasting of DNI

Weather Research and Forecasting model with solar extensions (WRF-Solar) uses the Fast All-sky Radiation Model for Solar applications (FARMS) to predict solar radiation from the forecasted atmospheric gases, aerosols, and clouds. The Beer-Bouguer-Lambert law utilized by FARMS as well as other radiative transfer models assumes Direct Normal Irradiance (DNI) is a narrow beam only covering the sun disk. This assumption is interpreted differently in solar observations by pyrheliometers where the circumsolar diffuse radiation is accounted. This study precisely computes circumsolar diffuse radiation in all-sky conditions using a radiative transfer model based on a parameterization of precomputed cloud transmittance and reflectance. The model is implemented in WRF-Solar to provide day-ahead DNI forecast in the north America. The computation and forecasting of DNI is compared with the Beer-Bouguer-Lambert law to understand the impact of circumsolar diffuse radiation.

aerosols↗
DOE OSTI2023

A Performance Forecasting Framework for Concentrating Solar Power Systems

This presentation will summarize a methodology used to characterize the uncertainty in performance of a contrived CSP project. As well as develop a case study in which we backcast the projected and actual annual performance of an existing plant. Finally will highlight the importance of several assumptions and the use of time series inputs in obtaining realistic estimates.

concentrating solar power↗