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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development of an Unbiased Future Solar Dataset for Solar Resource Adequacy Research Over CONUS

A high-resolution, long-term solar dataset is essential for capturing the variability of solar energy resources and informing strategies to ensure grid reliability and resilience in systems with high levels of solar energy integration. This study focuses on generating unbiased, high-resolution projections of solar irradiance through a statistical downscaling framework, using Earth system model (ESM) simulations obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). The National Solar Radiation Database (NSRDB) is used to calibrate statistical downscaling models. The newly developed dataset provides solar irradiance, surface air temperature, and surface wind speed at 4-km and hourly resolutions across the contiguous United States (CONUS), based on two future scenarios (RCP4.5 and RCP8.5). This study outlines key steps in developing the high-resolution future solar dataset, including (1) regridding ESM data to a common 20-km resolution grid, (2) correcting ESM biases using the NSRDB, and (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar projections. Preliminary results indicate that downscaled projections (4-km) captured reasonable spatial patterns when compared to observations across CONUS for four variables. On average across all pixels, 4-km daily-total GHI and DNI projections showed normalized bias (nBias) less than 1% and 6% for GHI and DNI against NSRDB, respectively (nBias less than 1% and 5% for daily-average surface air temperature and surface wind speed). In terms of long-term trend for GHI and DNI, there was no strong increasing or decreasing trend (when compared to surface air temperature), but it showed a very weak decreasing trend.

14 SOLAR ENERGY↗
DOE OSTI2026

The S-PLUS Fifth Data Release: Over 4500 Square Degrees of the Southern Sky and a Multicolor View of the Hydra and Antlia Galaxy Clusters

Abstract We present the fifth data release (DR5) of the Southern Photometric Local Universe Survey (S-PLUS), covering 4592 deg 2 across 2491 fields. Observations were conducted with the T80-South, a Brazilian robotic telescope equipped with the Javalambre 12-filter system, containing five broadband and seven narrowband filters. Data products feature FITS images and extensive catalogs containing fluxes, magnitudes, and shape parameters for over 113 million detections. In addition, several value-added catalogs are provided, offering photometric redshifts (photo- zs ), object classifications, masks, and extinction coefficients. For the first time, this release includes coverage of 110 deg 2 along the Galactic disk, facilitating new research into Galactic structure and stellar populations. The release also provides full coverage of the Hydra Supercluster and numerous other nearby clusters with improved data reduction and calibration, enhancing photo- z accuracy, which is vital for large-scale structure studies. A preliminary analysis of the Hydra and Antlia galaxy clusters up to 5 × R 200 yields an updated catalog of 1706 cluster members based on both spectroscopic and high-quality photo- zs . Our photometric data shows that both clusters have a similar proportion of galaxies with an H α excess relative to their clustercentric distance, though Hydra has a higher fraction near its center. Additionally, the spatial distribution of all objects in our sample highlights a bridge connecting both clusters. We verify that S-PLUS DR5 provides a solid foundation for future scientific investigations, ranging from solar system studies to cosmology.

Vinicius Rodrigues de Lima, Erik [Universidade de ↗
DOE OSTI2025

Assessment of Climate Change Impacts on Renewable Energy Resources in Western North America

We examine a 25 km resolution climate model dataset to evaluate how regional climate change impacts solar and wind energy under a high-emission scenario. Our study considers the Western Electricity Coordinating Council (WECC) region, which covers the western United States and southwestern Canada, focusing specifically on locations with existing solar and wind infrastructure. First, we conduct a historical model comparison of solar and wind energy capacity factors to highlight model uncertainties across the study area. Using future climate projections, we then assess the seasonal patterns of solar and wind capacity factors for three timeframes: historical, mid-century, and end of century. Additionally, we estimate the frequency of solar and wind resource droughts during these periods for the entire WECC and its five operational subregions, finding that certain subregions are more susceptible to energy droughts due to limited renewable resources. Finally, we present day-ahead capacity factor forecasts to support energy storage planning and provide estimates of offshore wind energy capacity within the WECC. Our results indicate that offshore wind capacity factors are nearly twice as high as onshore values, with less seasonal variation, which suggests that offshore wind could offer a more consistent renewable energy supply in the future.

climate change↗
DOE OSTI2025

Assessing Climate Change-Induced Variability in Generation Potential and Droughts of Renewable Energy Systems in India

Solar photovoltaic (PV) and wind energy systems are crucial for decarbonizing the electricity sector and achieving climate goals. However, these systems are weather-dependent, and ignoring the potential changes in their generation levels due to climate change could compromise achieving climate targets and meeting future electricity demand. This study evaluates the impact of climate change on the generation potential of wind and solar PV systems in India for three future periods, 2030 (2021-2040), 2050 (2041-2060), and 2070 (2061-2080) compared to the baseline year 2000 (1991-2010), under three emission scenarios: SSP245, SSP370, and SSP585. Solar PV generation levels consistently decline (up to 10 %) across all regions and scenarios. Wind energy shows more pronounced variability (-20 % to 30 %). The South and Southeastern regions of India show improvements in wind potential across all scenarios and time periods. This study also investigated the projected changes in the generation droughts of both energy systems. For solar PV, drought days increase across most regions (exceeding 500 days under SSP370 across the 20-year period). In contrast, wind energy sees a reduction in drought days, especially in parts of South and Southeast India (declines exceeding 50 days across different scenarios). For both energy systems, the patterns of generation drought and generation potential are similar, and indicate that Western and Northern India may be less favorable for the future expansion of solar PV and wind energy, respectively. These results highlight the need to account for the potential impacts in future capacity planning.

14 SOLAR ENERGY↗
DOE OSTI2024

Renewable-battery hybrid power plants in congested electricity markets: Implications for plant configuration

Examining coupled renewable-battery power plants (“hybrids”) in congested areas provides insights into a future of increased wind and solar penetration. Our study focuses on two types of congested regions, Variable Renewable Energy (VRE)-rich Areas and Load Centers, and explores likely plant configuration choices for developers and transmission network planners. Here, this paper examines how hybrid value, comprising energy and capacity value, varies by plant configuration and congested region type considering factors such as storage duration, battery degradation, and ability to charge from the grid. We select plant locations from across the seven main U.S. independent system operators (ISOs). Hybrid value for each configuration is computed based on profit-maximizing plant operation given perfect foresight, according to observed wholesale power market real time prices from 2018 to 2021. In VRE-rich Areas, the median increase in energy value from extending storage duration from one to 4h is 29.4% for solar and 26.8% for wind, assuming low battery degradation costs and storage sized to 100% of the plant's nameplate generation capacity. Increasing storage duration beyond 4h does not substantially increase its value from energy markets, even in VRE-rich Areas. We find that solar hybrids reach a 90% capacity credit with 4h of storage, while wind hybrids require 8h of storage, based on the capacity factor of each hybrid during the top 100 net load hours.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Solar and Storage Integration in the U.S. Southeast: Implications for Resource Adequacy

Resource adequacy concerns may be very different in electricity systems that have higher levels of solar and storage, requiring changes to existing planning models. This study explores a novel approach to evaluating resource adequacy under future scenarios with higher solar and storage in the Southeast U.S. It uses NREL’s Probabilistic Resource Adequacy Suite (PRAS), a collection of probabilistic resource adequacy modeling tools, and compares results when interacting PRAS and a portfolio planning tool with a more traditional modeling approach. The results suggest that traditional models perform reasonably well with lower levels of solar PV, but at higher levels of solar probabilistic tools better capture the changes in resource adequacy concerns—such as winter energy availability—associated with higher solar systems. This is the final study in the Preparing Southeast Markets for Reliable and Affordable Integration of Solar into Operations and Planning project. Two prior reports can be found at: Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations. https://emp.lbl.gov/publications/solar-and-storage-integration Solar and Wind Forecast Error Reserve Sharing in a Multi-Utility Region. https://eta-publications.lbl.gov/sites/default/files/2024-11/multiutility_fe_reserve_sharing_final.pdf

14 SOLAR ENERGY↗
DOE OSTI2024

In-depth analysis of solar models with high-metallicity abundances and updated opacity tables

Context. As a result of the high-quality constraints available for the Sun, we are able to carry out detailed combined analyses using neutrino, spectroscopic, and helioseismic observations. These studies lay the ground for future improvements of the key physical components of solar and stellar models because ingredients such as the equation of state, the radiative opacities, or the prescriptions for macroscopic transport processes of chemicals are then used to study other stars in the Universe. Aims. We study the existing degeneracies in solar models using the recent high-metallicity spectroscopic abundances by comparing them to helioseismic and neutrino data and discuss the effect on their properties of changes in the micro and macro physical ingredients. Methods. We carried out a detailed study of solar models computed with a high-metallicity composition from the literature based on averaged 3D models that were claimed to resolve the solar modelling problem. We compared these models to helioseismic and neutrino constraints. Results. The properties of the solar models are significantly affected by the use of the recent OPLIB opacity tables and the inclusion of macroscopic transport. The properties of the standard solar models computed using the OPAL opacities are similar to those for which the OP opacities were used. We show that a modification of the temperature gradient just below the base of the convective zone is required to remove the discrepancies in solar models, particularly in the presence of macroscopic mixing. This can be simulated by a localised increase in the opacity of a few percent. Conclusions. We conclude that the existing degeneracies and issues in solar modelling are not removed by using an increase in the solar metallicity, in contradiction to what has been suggested in the recent literature. Therefore, standard solar models cannot be used as an argument for a high-metallicity composition. While further work is required to improve solar models, we note that direct helioseismic inversions indicate a low metallicity in the convective envelope, in agreement with spectroscopic analyses based on full 3D models.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Impacts of Climate Change on the Generation Potential of Solar and Wind Energy Systems in India

Low-carbon energy sources like wind and solar are essential for decarbonizing the electricity sector. In addition, the cost of electricity generated from these sources has plummeted over the last decade. Therefore, these energy sources are poised to take a significant share of the total installed capacity soon. However, they are susceptible to the impacts of climate change as their generation potential depends on the weather conditions. Estimating the installed capacity requirements of solar and wind energy to decarbonize the power sector without accounting for these possible changes in generation potential could lead to missing out on the set climate goals and meeting future electricity demand. This study evaluates the effect of climate change on the generation potential of wind and solar energy systems in India for two future periods, 2050 and 2070, under two climate scenarios or Shared Socioeconomic Pathway (SSP): SSP245 and SSP585. Almost all regions show a decrease, and most regions show a significant decline (>5%) in the generation potential of solar Photovoltaic (PV) as compared to 2010 levels under both climate scenarios and future periods. The changes in the generation potential of wind energy are more significant (>10%), and the majority of regions show a decline in generation potential. Southwestern and central regions show an increase in wind generation potential for 2070 as compared to 2050 levels under the SSP245 scenario and the SSP585 scenario, respectively.

climate change↗
DOE OSTI2024

The National Climate Data Base (NCDB): A Bias-Corrected High-Resolution Climate Dataset

Assessing renewable energy resources under future climate scenarios has been highlighted in recent years to analyze and understand potential impacts of future change in renewable generation on the power sector. Solar energy is well-known as the most plentiful among various renewable resources and usually converted to electricity using photovoltaics (PV) technologies, and the global deployment of PV technology has increased rapidly in recent decades. In this study, we develop a statistical technique to downscale the future projection of solar irradiance for PV energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the proposed downscaling method and future extension of this research.

climate data↗
DOE OSTI2020

Probabilistic Forecast of All-Sky Solar Radiation Using Enhanced WRF-Solar: Preprint

This study presents enhancements of the Weather Research and Forecasting model with solar extensions (WRF-Solar) to provide probabilistic forecasts of solar radiation. Our approach builds ensemble WRF-Solar runs by introducing stochastic perturbations of variables that produce the largest uncertainties in predicting surface irradiance and clouds. The key variables are identified using tangent linear sensitivity analysis of six physics packages responsible for all-sky irradiance variability. An optimal strategy to stochastically perturb the selected variables is developed and applied to WRF-Solar to generate ensemble members for day-ahead solar prediction. The National Solar Radiation Database (NSRDB) is used to validate the ensemble forecast at arbitrary locations on the model grid. Preliminary results indicate that the proposed technique can potentially produce WRF-Solar ensembles providing reliable information of solar prediction uncertainty. This study describes the implemented methodology and initial results as well as future research to improve ensemble-based probabilistic forecasts with WRF-Solar.

all-sky↗
DOE OSTI2022

Impact of model predictive control-enabled home energy management on large-scale distribution systems with photovoltaics

Residential customers use more than one-quarter of the electricity in the world. Optimally managing home energy consumption is an effective way of easing the operational challenges facing the electric grid with increasing solar photovoltaics (PV). This paper studies the impact of the future proliferation of home energy management systems (HEMS) in the presence of PV on large-scale distribution systems. First, we present a stochastic HEMS model that minimizes residential customers' thermal discomfort and energy costs under uncertainty. The HEMS model schedules the optimal operations of residential appliances in the presence of PV within a mixed-integer linear programming-based model predictive control framework that links the proposed HEMS to a quasi-steady-state time-series simulation tool. Additionally, extensive simulations are conducted for a stand-alone residential home using two tariff structures and for 1977 homes on an 8,500-node distribution feeder. Simulation results quantify the impact of the future proliferation of HEMS on the large-scale distribution system with PV.

14 SOLAR ENERGY↗
DOE OSTI2022

Assessing the New Home Market Opportunity: Case Study and Cost Modeling for Solar and Storage in 2030

Residential solar and storage markets are growing in the United States. With approximately 1 million new homes constructed every year, this represents a significant opportunity for solar and storage installations. Some homebuilders have begun to build new homes with solar and storage included as a standard offering. It is not clear how solar and storage is incorporated into the new construction process and at what cost. Further, it is unclear what barriers or opportunities exist to scale this model nationwide. To fill this gap in the literature, this research conducts a case study of Mandalay Homes' new solar and storage community in Arizona to gather lessons learned. From this foundation, we further generate a set of pathways to reduce install costs and expand solar and storage market penetration in this sector. To model existing and 2030 solar and storage costs, we use the National Renewable Energy Laboratory's (NREL's) bottom-up cost model. This modeling is further informed by 12 interviews conducted with new home builders, solar contractors, and other subject matter expert organizations. Our case study analysis generated three key considerations for other homebuilders including: 1. Educating local permitting, inspection, and in some cases utility officials on solar and storage products, designs, and code compliant building practices may be required. The need for education may decline as more local governments and utilities review and approve solar and storage projects. 2. Incorporating solar and storage systems into the homebuilding process can add complexity and related coordination challenges. This does not need to result in home construction delays, but can result in costly contractor "dry runs" to construction sites. 3. Deploying solar and storage at the time of new construction has significant economies of scale, which can improve the value proposition of the systems. The case study, extant literature, and interviews were used to model both existing and future solar and storage installation costs at time of new construction. Here, we find three key cost reduction opportunities relating to solar and battery storage hardware, customer acquisition, and overhead. If future contractors can maximize the cost reduction opportunities outlined here, residential new construction costs could decline by 8 - 25% by 2030, depending on the modeled scenario. Though we expect costs to decline through 2030, it is unclear which of these scenarios may ultimately appear. Interviewees further identified a variety of barriers across each cost category that could temper the savings shown here. At the same time, interviewees described several pathways to scale the new construction solar and storage market, beyond installation cost savings. Interviewees confirmed that changes in finance, rate design, resilience policies, deployment mandates, and DER aggregation could all support more market adoption than seen today. These findings suggest that there are significant opportunities to expand new construction markets and this research can serve as a baseline to assess progress in this segment through 2030.

14 SOLAR ENERGY↗
DOE OSTI2024

Bias Correction and Statistical Downscaling of Future Solar Irradiance Projections Using the NSRDB

Assessing renewable energy resources under future climate scenarios has been highlighted to understand potential impacts of future climate change in renewable generation on the power sector. Climate model projection has been recognized by the renewable energy community as a useful data set to analyze the impacts of future climate change on renewable resources. However, future climate projections generated from general circulation models (GCMs) contain inherent biases that need to be corrected for accurate analysis of future projections of climate variables. In addition, the coarse spatiotemporal resolution of GCMs needs to be improved for regional climate studies. In this work, we develop statistical methods to downscale future projections of global horizontal irradiance (GHI) in a computationally efficient way. Our approach builds statistical downscaling models that correct bias of climate projection of GHI and downscale the future GHI projection from daily-scale to hourly-scale. The National Solar Radiation Database (NSRDB) is used to calibrate the statistical models and validate the downscaled GHI projections across the contiguous United State (CONUS). Preliminary results show that the statistical approach efficiently downscales climate projections of GHI with a nBIAS of 3%, nMAE of 34 % and nRMSE of 46% calculated against NSRDB for CONUS. This study describes the implemented methodology and initial results as well as future research to create high-resolution climate data sets for solar energy applications.

analytical models↗
DOE OSTI2023

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗
DOE OSTI2023

Final Technical Report: Impact of Wildfires on Solar Generation, Reserves, and Energy Prices

This study quantifies the potential impacts of wildfires on the California grid, specifically the impacts under three different wildfire scenarios: a "no wildfire" scenario and two wildfire-specific scenarios, "2020 wildfire" and "enhanced wildfire" (with both wildfire scenarios assuming spatial distribution of the wildfire location the same as the 2020 fires). The study combines each scenario with two solar energy infrastructures: one corresponding to the current solar installation and the other to future (midcentury) solar installation. The analysis is conducted using state-of-the-science modeling tools: primarily WRF-Chem for atmospheric modeling with chemistry to account for impacts of wildfires on solar radiation and PLEXOS for electricity market simulations. The analysis suggests that wildfires can significantly attenuate solar radiation at both short downwind distances as well as far from the emissions sources. Although the study is limited in scope, and the analysis studies only a few of the many factors that can affect photovoltaic generation and electricity markets, it indicates that wildfire smoke is an important factor that needs to be carefully considered and analyzed in planning the future grid.

electricity market↗
DOE OSTI2021

Distributed Solar and Storage Adoption Modeling

The National Renewable Energy Laboratory (NREL) is analyzing the rapidly increasing role of energy storage in the electrical grid through 2050 through its Storage Futures Study. In one phase of the study, NREL used the laboratory's Distributed Generation Market (dGen) model to examine the various future distributed storage capacity adoption scenarios, results, and implications.

agent-based modeling↗
DOE OSTI2024

The National Climate Database (NCDB): An Unbiased 100-Year Dataset for PV Modeling

In this study, we develop a statistical technique to downscale the future projection of solar irradiance for photovoltaics (PV) energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the downscaling method, a summary of the 100-year dataset from 2001-2100, and future extension of this research.

bias correction↗
DOE OSTI2024

Detection of astrophysical neutrinos at prospective locations of dark matter detectors

We study the prospects for detection of solar, atmospheric neutrino, and diffuse supernova neutrino background (DSNB) fluxes at future large-scale dark matter detectors through both electron and nuclear recoils. We specifically examine how the detection prospects change for several prospective detector locations [Sanford Underground Research Facility (SURF), SNOlab, Gran Sasso, China Jinping Underground Laboratory (CJPL), and Kamioka] and improve upon the statistical methodologies used in previous studies. Because of its ability to measure lower neutrino energies than other locations, we find that the best prospects for the atmospheric neutrino flux are at the SURF location, while the prospects are weakest at CJPL because it is restricted to higher neutrino energies. On the contrary, the prospects for the DSNB are best at CJPL, due largely to the reduced atmospheric neutrino background at this location. Including full detector resolution and efficiency models, the CNO component of the solar flux is detectable via the electron recoil channel with exposures of ∼ 10 3 ton-yr for all locations. These results highlight the benefits for employing two detector locations, one at high and one at low latitude. Published by the American Physical Society 2024

Astronomy & Astrophysics↗