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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Vibrational Signatures of Electronic Properties in Renewable-Energy Catalysis

The objective of this research program is to discover and develop new approaches for ab initio computational simulations of molecular motion. Specifically, this program aims to decipher the connection between the underlying electronic structure and the accordant molecular vibrations in reactive ions and radicals for renewable-energy purposes. Recent experimental progress in ion sources and optical spectroscopies has unearthed considerable new inner-sphere detail for these complexes, but the connection between these spectral signatures and mechanistic information often remains elusive, to the continued frustration of experimentalists. For this purpose, new anharmonic vibrational frequency methods, along with a publicly deployed software package, will be developed. Working closely with committed experimental collaborators, this conceptual and computational framework will be used to explain the results of new spectroscopy experiments, focusing specifically on the inner-shell mechanisms of renewable-energy catalysis. The oxidation half of catalytic water-splitting chemistry will be a central focus, along with fundamental studies of the manner in which strong ions and radicals activate solvent as a chemical species. The resulting products of the research program will include openly available software and algorithms for the ab initio simulation of challenging vibrational spectra, as well as critical mechanistic insight into energy-focused catalytic processes that are opaque to other existing analytical techniques.

42 ENGINEERING↗
DOE OSTI2025

Cost-Effective Thermally Activated Building Systems to Support a Power Grid System With High Penetrations Of As-Available Renewable Energy Resources

With a goal to reduce the energy cost for building operation as well as to support renewable energy sources (RES) for the power grid reliability, quality, resilience, and dispatchability, this project developed and demonstrated a novel thermally activated building envelope system that integrates Phase Change Material (PCM)-based Thermal Energy Storage (TES) and the hydronic activation into the building envelope. The main objectives of this study are: 1) to design and laboraorty-test a novel thermally activated building envelope system that integrate PCM-based TES and the hydronic activation into building envelope, and 2) to exploit this new system to significantly reduce the energy cost of operating buildings and manage and support renewable energy sources (RES), e.g., solar and wind for the power grid reliability, quality, resilience, and dispatchability. To achieve the project objectives, a new low-cost, fire-retardant PCM packaging technology (CenoPCM) was developed specifically for high-volume building applications.

25 ENERGY STORAGE↗
DOE OSTI2026

OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems

We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Laboratory of the Rockies's (NLR) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Biochemical Conversion of Herbaceous Biomass to Renewable Diesel: Biorefinery Marginal Air Quality Impacts and Comparison to Feedstock Production

This study assesses the air quality impacts of an advanced biorefinery that produces renewable diesel blendstock (RDB) from lignocellulosic biomass via aerobic respiration (Davis et al. 2022) by estimating fine particulate matter (PM2.5) impacts from biorefinery emissions. It continues a prior analysis that used a geospatial assessment to identify source regions for biomass feedstocks and studied the impact of feedstock production emissions on air quality (Thind et al. 2022). Thind et al. (2022) identified RDB biorefineries that can use corn stover feedstocks of 2,000; 5,200; and 9,100 dry metric tons per day (DMT/day), based in Iowa, and suggested 7 unique counties can serve as hosts for a biorefinery that draws biomass feedstock from neighboring counties. Given 13 unique county-biorefinery size combinations and two waste lignin end uses at the biorefinery (lignin as a fuel for electricity generation and lignin for pellet production), the air-quality-related sustainability aspects of each of these 26 scenarios are assessed by estimating the annual average impacts of biorefinery emissions on the dispersion and formation of secondary PM2.5 in the atmosphere using a novel reduced-complexity air quality model called the Intervention Model for Air Pollution (InMAP). The 26 biorefinery design combinations help capture how a biorefinery's emissions of air pollutants and their resulting impact on local and regional air quality are influenced by the magnitude of production scale, lignin utilization strategy, and location of a proposed biorefinery. Methods developed in Thind et al. (2022) are applied to estimate the constraints on primary PM2.5 and secondary PM2.5 precursor emissions based on compliance with U.S. Environmental Protection Agency's (EPA's) annual primary National Ambient Air Quality Standard (NAAQS) of PM2.5 (i.e.12.0 micrograms per cubic meter (microgram/m3)) at downwind receptors of a biorefinery. Incremental PM2.5 concentrations caused by the emission of biorefining corn stover into RDB are assessed and compared to those of corn stover production. To illuminate which upstream supply chain stage of renewable diesel production contributes most to air quality impacts, marginal PM2.5 concentrations are compared between both stages at multiple downwind air quality monitor locations. In addition, through a hotspot analysis, we identify the primary contributing factors of emissions within the feedstock production and biorefinery stage operations. In doing so, we provide insights for improving the air pollutant emission-related sustainability of advanced lignocellulosic biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2025

Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System

This paper investigates the challenges and solutions associated with integrating a hydrogen-generating nuclear-renewable integrated energy system (NR-IES) under a transactive energy framework. The proposed system directs excess nuclear power to hydrogen production during periods of low grid demand while utilizing renewables to maintain grid stability. Using digital real-time simulation (DRTS) in the Typhoon HIL 404 model, the dynamic interactions between nuclear power plants, electrolyzers, and power grids are analyzed to mitigate issues such as harmonic distortion, power quality degradation, and low power factor caused by large non-linear loads. A three-phase power conversion system is modeled using the Typhoon HIL 404 model and includes a generator, a variable load, an electrolyzer, and power filters. Active harmonic filters (AHFs) and hybrid active power filters (HAPFs) are implemented to address harmonic mitigation and reactive power compensation. The results reveal that the HAPF topology effectively balances cost efficiency and performance and significantly reduces active filter current requirements compared to AHF-only systems. During maximum electrolyzer operation at 4 MW, the grid frequency dropped below 59.3 Hz without filtering; however, the implementation of power filters successfully restored the frequency to 59.9 Hz, demonstrating its effectiveness in maintaining grid stability. Future work will focus on integrating a deep reinforcement learning (DRL) framework with real-time simulation and optimizing real-time power dispatch, thus enabling a scalable, efficient NR-IES for sustainable energy markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
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↗
NASA NTRS1979

Toward the renewables - A natural gas/solar energy transition strategy

The inevitability of an energy transition from today's non-renewable fossil base toward a renewable energy base is considered from the viewpoint of the need for a national transition strategy. Then, one such strategy is offered. Its technological building blocks are described in terms of both energy use and energy supply. The strategy itself is then sketched at four points in its implementation; (1) initiation, (2) early transition, (3) late transition, and (4) completion. The transition is assumed to evolve from a heavily natural gas-dependent energy economy. It then proceeds through its transition toward a balanced, hybrid energy system consisting of both centralized and dispersed energy supply technologies supplying hydrogen and electricity from solar energy. Related institutional, environmental and economic factors are examined briefly.

Hanson, J. A.↗
NASA NTRS1981

Thermal infrared remote sensing of surface features for renewable resource applications

The subjects of infrared remote sensing of surface features for renewable resource applications is reviewed with respect to the basic physical concepts involved at the Earth's surface and up through the atmosphere, as well as the historical development of satellite systems which produce such data at increasingly greater spatial resolution. With this general background in hand, the growth of a variety of specific renewable resource applications using the developing thermal infrared technology are discussed, including data from HCMM investigators. Recommendations are made for continued growth in this field of applications.

Welker, J. E.↗
NASA NTRS1986

Tunisia Renewable Energy Project systems description report

In 1979, the Agency for International Development (AID) initiated a renewable energy project with the Government of Tunisia to develop an institutional capability to plan and institute renewable energy technologies in a rural area. The specific objective of the district energy applications subproject was to demonstrate solar and wind energy systems in a rural village setting. The NASA Lewis Research Center was asked by the AID Near East Bureau to manage and implement this subproject. This report describes the project and gives detailed desciptions of the various systems.

Scudder, L. R.↗
NASA NTRS2022

Washington, D.C. & Maryland Energy: Estimating Solar Potential Using NASA POWER Data to Inform Renewable Energy Policy for Washington, D.C.

In line with the Sustainable D.C. 2.0 plan to combat climate change, Washington D.C. aims to decrease its greenhouse gas emissions by 100% by 2050. As solar energy is a clean, renewable energy form, its integration into the region’s power grids lowers energy costs and incentivizes sustainable development. We partnered with the Washington D.C. Department of Energy & Environment (DOEE) to determine how urban areas surrounding D.C. can better be incorporated into decisions regarding renewable energy policy. The team used NASA’s Prediction of Worldwide Energy Resources (POWER) solar data and a Light Detection and Ranging (LiDAR) derived digital surface model, to estimate and visualize rooftop solar potential for Maryland’s Prince George’s and Montgomery counties. POWER provided solar irradiance data adjusted for tilt angle while the digital surface model contributed aspect and slope data. This methodology factored out areas that were unsuitable for solar panel installation while displaying areas that possess a high potential for energy return. The team found the total rooftop solar potential for the study area to be almost 32 million kW, which is equivalent to roughly 660 kW per building. The methodology used to generate the solar potential maps can be applied to other regions of the country seeking to efficiently utilize solar energy. The end users at the DOEE can use our resulting solar potential map and data table to effectively target buildings that have the highest potential to generate solar energy.

Edward Cronin↗
NASA NTRSDate not supplied

NASA Initiatives to Support Renewable Energy and Sustainable Infrastructure

Initiatives to build and manage climate-resilient infrastructure require spatially explicit environmental and climate information. NASA’s vantage point of Earth from space provides valuable observations that, in concert with additional information, can be used to inform both the design and operation of infrastructure that builds resilience to climate stressors. In this presentation, we provide an overview of how NASA Earth science is used to support decision-making associated with climate adaptation and mitigation, with a particular focus on renewable energy and sustainable infrastructure. Much of this work is currently delivered through NASA’s Prediction of Worldwide Energy Resources (POWER) project, which generates high quality solar and meteorological data products that are customized to the needs of user communities. Importantly, these products are delivered through a variety of web-based applications that make it easier for users to access relevant and timely information. We will highlight several examples of how the impact of POWER is scaled via a robust user community and discuss further plans to expand impact. Additionally, this presentation will highlight efforts of the NASA Earth Science Division’s Energy & Infrastructure Applications program to expand collaborative activities with researchers and practitioners that work on renewable energy and sustainable infrastructure.

Allison K Leidner↗
DOE OSTI2024

Design of Zone-Based Hierarchical Protection System for 100% Renewable Microgrids: Preprint

Design of a reliable and secure protection system for a 100% renewable microgrid with only inverter-based resources (IBRs), is quite challenging. Most of the existing protection schemes in the state-of-the-art are suitable for microgrids with mixed-type of distributed energy resources (DERs) that covers both rotating machine-based DERs as well as IBR-based DERs, where the fault current level is moderately high. Due to drastic reduction in fault current level based on mode of operation and the variation of the low fault current level based on the operating level of the IBRs, the existing protection schemes face critical challenges, in case of a 100% renewable microgrid. This article proposes a zone-based hierarchical protection scheme that partitions a microgrid into various zones-of-protection and assigns speed-based hierarchical protection schemes in order to address the fundamental challenges of such microgrids. The performance of the proposed scheme is evaluated using time-domain simulation study on a microgrid test system. The results corroborates that the proposed hierarchical zone-based protection scheme exhibits enhanced reliability, security and dependability while tested with various fault cases (fault types, locations, and impedances), and non-fault cases during both grid-tied and islanded mode.

grid-forming inverter↗
DOE OSTI2024

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.

first-principles calculations↗
DOE OSTI2024

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids: Preprint

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗
DOE OSTI2025

Assessing the Performance and Impact of PV Technologies on Storage in Hybrid Renewable Systems

Traditional monofacial photovoltaic (mPV) systems are commonly adopted and well-documented because of their lower upfront costs in comparison to bifacial photovoltaic (bPV) systems. This study investigates how PV technologies impact energy storage in grid-scale hybrid renewable systems, focusing on optimizing and assessing the performance of mPV and bPV technologies integrated with pumped storage hydropower. Using Ludington City, Michigan as a case study and analyzing real-world data such as solar irradiance, ambient temperature, and utility-scale load profiles, the research highlights the operational and economic benefits of bPV systems. The results reveal that bPV systems can pump approximately 10.38% more water annually to the upper reservoir while achieving a lower levelized cost of energy ($0.0578/kWh for bPV vs. $0.0672/kWh for mPV). This study underscores the outstanding potential of bPV systems in enhancing energy storage and management strategies, contributing to a more sustainable and resilient renewable energy future.

13 HYDRO ENERGY↗
DOE OSTI2025

Comparative Study of Enhanced Geothermal System Supply Curves Across CONUS from Two Temperature Models Using the Renewable Energy Potential Model (reV)

Enhanced geothermal systems (EGS) have had recent breakthroughs within the geothermal sector. These breakthroughs are reflected in the National Renewable Energy Laboratory (NREL) 2024 Annual Technology Baseline and will result in updated EGS supply curves (i.e., the available resource capacity relative to cost). Our research uses NREL's Renewable Energy Potential (reV) model to compare EGS supply curves across the conterminous United States (CONUS) for two different temperature models: the Stanford temperature model (STM) and the Southern Methodist University temperature model (SMU). The reV model provides the levelized cost of energy (LCOE) at a consistent resolution across CONUS, taking into consideration transmission costs and constraints as well as technical exclusions pertaining to sensitive cultural, ecological, or infrastructure locations. In addition to a countrywide analysis of both models, we also conducted a regional analysis of Texas. We observed the STM had, on average, lower temperatures across different depths, resulting in slightly higher mean and median LCOEs as compared to the SMU temperature model at the same depths. In the regional analysis for Texas, however, when we compared only the common points between the two temperature models, the STM had lower median and mean LCOEs compared to SMU due to higher temperatures at depths greater than 5 km.

enhanced geothermal systems↗
DOE OSTI2026

Comparative life-cycle assessments and techno-economic analysis of renewable natural gas production pathways from biogas

Renewable natural gas (RNG) offers a promising pathway for decarbonizing hard-to-abate sectors. This study shows that, relative to conventional upgrading technologies (i.e., membrane separation and pressure swing adsorption), the catalytic methanation reaction (CMR) at water resource recovery facilities doubles RNG output. When consuming lowcarbon hydrogen, the CMR reduces operational energy use and global warming potential. Techno-economic analysis indicates that the CMR is not yet competitive but will become viable if hydrogen reaches $1/kg. Heat integration and hydrogen cost are key drivers of overall performance.

03 NATURAL GAS↗