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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Cost-Benefit Analysis of Grid-Supportive Loads for Fast Frequency Response

Flexibility in inverter-based loads could be used to support the converter-dominated power grid by offering a rapid, autonomous, and adjustable power reserve during system transients to help maintain system stability. Based on technical potential, ancillary service (AS) value, and implementation costs, this study illustrates the cost-benefit analysis of grid-supportive loads (GSLs) for the supply of fast frequency response (FFR). The net benefit for each GSL is demonstrated using a case study and relevant data sources. The findings suggest that implementation costs for enabling GSL features are low compared to the value that grid operators get from the acquisition of responsive reserve services. The authors believe that, given the rising popularity of renewable energy sources, GSLs can be a useful tool for grid stability in low-inertia systems.

cost-benefit analysis↗
DOE OSTI2020

Energy Storage Analysis

This study presents a comprehensive techno-economic characterization of energy storage and exible low carbon power generation technologies that can shift energy across days, weeks, or months to balance daily, weekly, and seasonal disparities in supply and demand. Energy storage technologies evaluated here include pumped hydropower storage (PHS), adiabatic and diabatic compressed air energy storage (CAES), vanadium redox flow batteries (VRBs), pumped thermal energy storage (P-TES), and renewably produced hydrogen stored in either geologic formations or underground pipes with re-electrification via combustion turbines in combined cycles, stationary proton exchange membrane (PEM) fuel cells, or the novel use of PEM fuel cells designed for heavy-duty vehicles (HDVs) which are expected to have shorter lives but also lower capital costs. We also evaluate flexible low-carbon power generation systems, including ethanol combustion in gas turbines and natural gas combustion with carbon capture and sequestration (CCS). We estimate current costs with literature data, use learning rates to characterize future costs, and develop capacity factors calibrated to an 85% renewables grid to calculate the levelized cost of energy (LCOE) of each technology. Results illustrate that at the 12-hour storage duration, PHS and CAES have the lowest LCOE with current costs, and VRBs become competitive if future costs are achieved. At the 120-hour storage duration, hydrogen systems with geologic storage and natural gas with CCS achieve the lowest LCOE in both current and future capital cost scenarios. In particular, the new configuration of HDV-PEM fuel cells with hydrogen storage in geologic formations evaluated here could lower the LCOE by 22-27% compared to stationary fuel cell systems typically evaluated and might help enable very high (>80%) renewable energy electric power systems. P-TES and hydrogen stored in underground pipes are the least-cost options at the 120-hour storage duration rating that do not require some form of geologic storage. Sensitivity analysis and Monte Carlo analysis illustrate that the general trends seen in this study are valid for a wide range of capacity factors and future cost scenarios. The study also illustrates that coproducing and selling hydrogen to other markets could reduce the LCOE of hydrogen systems by up to 39%.

carbon capture and sequestration↗
DOE OSTI2021

H 2 Production Pathways Cost Analysis (2016 - 2021) (Final Report)

This final report documents cost analysis conducted for the Department of Energy over a five year period (2016 to 2021) pertaining to hydrogen production and delivery system components, focusing on the key remaining challenges of the technology pathways within the Hydrogen Production and Delivery sub-program portfolio. A particular focus was placed on electrolysis for the generation of hydrogen. The effort primarily used the H2A discounted cash flow computational model as a tool to project hydrogen cost ($/kgH 2 ) and determine status improvements resulting from technology advancements. The effort also considered cost as a function of production volume, employed error bars to illustrate uncertainties in the cost estimates, and utilized sensitivity analyses to show the potential for cost reductions. The project examined a range of hydrogen production and delivery related systems. These included WireTough wire-wrapped pressure vessels for hydrogen storage, proton exchange membrane (PEM) electrolysis, solid oxide electrolysis (SOE), anion exchange membrane (AEM) electrolysis, photoelectrochemical (PEC) electrolysis, solar thermochemical hydrogen (STCH) production, the cost of energy transmission, and a study on the necessary price of hydrogen to produce competitively-priced electricity via fuel cell conversion.

08 HYDROGEN↗
DOE OSTI2024

Electrically Powered High-Salinity Brine Separation Using Dimethyl Ether

Dewatering highly saline aqueous streams, from mining and geothermal leachates to industrial wastewater, is essential for effective resource recovery and safe disposal. Membraneless water extraction (MWE) uses a low-polarity solvent to separate water from concentrated aqueous solutions. In this study, we design a new MWE that uses dimethyl ether (DME) to selectively extract water from high-salinity brines, leveraging the volatility of DME to achieve rapid solvent recovery. By separating water and dissolved salts at a liquid–liquid interface, MWE minimizes the deleterious effects of scaling on vulnerable membrane and heat exchanger surfaces, reducing the need for extensive pretreatment and expensive materials. We begin by developing a computational framework for a multistage counterflow liquid–liquid contactor, which extracts water into DME, coupled with a multistage solvent regenerator that uses vapor compression to efficiently separate the desalinated water from the DME extractant. Excess Gibbs free energy and equation of state frameworks are used to model fluid phase equilibria in water–DME–sodium chloride (NaCl) mixtures, with interaction parameters estimated from experimental data. Incorporating equilibrium calculations into a system-scale computational model, we examine the performance of MWE using DME for the first time. Our analysis demonstrates that MWE can concentrate seawater desalination brine (>1.0 mol NaCl kg –1 ) to zero-liquid discharge salinities, with an energy consumption of under 50 kW h per m 3 of water extracted with a solvent recovery ratio greater than 99.9%. We highlight the importance of staging the vapor compression process to simultaneously minimize energy consumption while enabling brine concentration and product water solvent contamination. Finally, the thermodynamic framework developed here allows for the robust evaluation of new MWE solvents and systems for critical brine concentration and fractional precipitation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Phase change material-to-refrigerant heat exchangers: Experimental validation and uneven melting analysis

Thermal energy storage (TES) using phase change materials (PCMs) enables load shifting and reduces mismatches between the building's thermal demand and the heat pump (HP) system's thermal capacity. While most TES studies have focused on single-phase heat transfer fluids, PCM-to-refrigerant heat exchangers (PRHX), in which the refrigerant undergoes liquid-vapor phase change, remain largely underexplored. Here, to address this gap, this study systematically investigates a shell-and-tube PRHX operating as the condenser in an HP through experiments and simulations. A two-dimensional enthalpy-based finite-volume PRHX model was developed and validated against experimental data, including refrigerant and PCM temperature profiles, PRHX capacity, and system-level performance. Results show three characteristic stages: Stage I, the condenser temperature rapidly increases with PCM in the solid state absorbing sensible heat; Stage II, stable operation during PCM phase change; and Stage III, performance decline once part of the PCM becomes fully melted. Heat transfer analysis revealed that uneven PCM melting along the condenser length was driven primarily by variations in the refrigerant-side heat transfer coefficient, rather than local approach temperature differences. Further study demonstrated that minimizing refrigerant outlet subcooling led to more uniform PCM melting and extended Stages I and II by up to 89%. This paper provides a validated PRHX model, clarifies the mechanisms of uneven PCM melting, and highlights subcooling control as an effective strategy to improve TES performance in HP systems without requiring secondary loops.

Graphite matrix↗
DOE OSTI2022

GIS-Based Graphical User Interface Tools for Analyzing Solar Thermal Desalination Systems & High-Potential Implementation

This project developed a user-friendly, open-source, software that enables a comparative evaluation of solar thermal desalination technology options and employs geospatial data layers to identify regions of high-potential for solar thermal desalination. This was accomplished by integrating solar models with desalination models and enhancing their utility by providing GIS-based data inputs. The developed Solar Energy Desalination Analysis Tool (SEDAT) enables techno-economical evaluation of desalination technologies and selection of regions with the highest potential for using solar energy to power desalination plants. It simplifies the planning, design, and valuation of solar thermal and solar hybrid desalination systems in the U.S. and worldwide. SEDAT uses Dash for integrating various layers of large volumes of GIS data with Python-based models of solar energy generation and desalination technologies. It derives time-series of energy generation and water production, with details of plant performance and suggestions for improving the solar-desalination coupling. It is a one of-a-kind tool of analysis representing a definitive advancement in the state-of-the-art. Of solar desalination modeling This report summarizes the various phases of the tool’s development, and presents examples of the results.

14 SOLAR ENERGY↗
DOE OSTI2023

Nucleation-mediated reshaping of facetted metallic nanocrystals: Breakdown of the classical free energy picture

Shape stability is key to avoiding degradation of performance for metallic nanocrystals synthesized with facetted non-equilibrium shapes to optimize properties for catalysis, plasmonics, and so on. Reshaping of facetted nanocrystals is controlled by the surface diffusion-mediated nucleation and growth of new outer layers of atoms. Here, Kinetic Monte Carlo (KMC) simulation of a realistic stochastic atomistic-level model is applied to precisely track the reshaping of Pd octahedra and nanocubes. Unexpectedly, separate constrained equilibrium Monte Carlo analysis of the free energy profile during reshaping reveals a fundamental failure of the classical nucleation theory (CNT) prediction for the reshaping barrier and rate. Why? Nucleation barriers can be relatively low for these processes, so the system is not locally equilibrated before crossing the barrier, as assumed in CNT. This claim is supported by an analysis of a first-passage problem for reshaping within a master equation framework for the model that reasonably captures the behavior in KMC simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

European residential wood pellet trade and prices dataset

The European market for wood pellets used in small-scale heating systems has been expanding significantly over the past decade. For an analysis of market efficiency in the Journal Energy with the title “The European wood pellets for heating market - price developments, trade and market efficiency“ wood pellet prices have been collected as well as trade flows downloaded for the trade relations between Austria, Germany, Italy and France. Only since January 2012 monthly wood pellet trade data is published by Eurostat. This, now monthly expanding data-set provides new opportunities for analysing the development of this important renewable energy commodity. Furthermore, national wood pellet prices published by national authorities and interest groups are improving in quality in the recent years. The collection and combination of these data-sets are a chance for novel econometric analysis. This paper presents valuable tools and processes to acquire and prepare this data and connects to a data and code repository for downloading the resources described in this and the related Journal Energy publication.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Low embodied energy and carbon, high lifetime silicon boules via a combined chemical vapor deposition/float zone process

This work evaluates a new process route to making float zone (Fz)-quality silicon wafers using a combination of computational fluid dynamics (CFD) modeling and technoeconomic analysis. Our analysis finds that the new process competes with Czochralski (Cz)-grown wafers on a levelized cost of energy system level. The new process also decreases embodied energy and carbon of silicon photovoltaics (PV) by ~6x circumventing the energy-costly Siemens process used in polycrystalline silicon (poly-Si) production plants to generate feedstock for Fz and Cz boules. Instead of using poly-Si from the Siemens process to feed crystallization, the new process uses the high-purity, trichlorosilane (TCS) precursor gas to grow a poly-Si feed rod in-situ during a modified Fz1,2 boule growth process. The gas-to-boule float zone process enables opportunity to produce high-purity (low metals and oxygen content), uniformly doped single crystal silicon boules and wafers with high bulk lifetimes (τ bulk > 15 ms) to enable higher efficiency cells (>27 %) with fewer known degradation mechanisms than Czochralski (Cz)-grown wafers. These benefits reduce the levelized cost of electricity (LCOE) of PV-produced electricity. Here we show the results of our CFD and chemical modeling of the process to prove feasibility and economic viability.

14 SOLAR ENERGY↗
DOE OSTI2024

A Machine Learning Bias Correction on Large–Scale Environment of High–Impact Weather Systems in E3SM Atmosphere Model

Large–scale dynamical and thermodynamical processes are common environmental drivers of high–impact weather systems causing extreme weather events. However, such large–scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high–impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large–scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ~1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high–impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large–scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias–corrected large–scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large–scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large–scale storm environments simulated by low–resolution climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Seasonal Reconfiguration of Electrical Distribution Systems to Mitigate the Impact of Electric Vehicle Charging

Power grids face challenges in their infrastructure related to the integration of electric vehicles (EV). In particular, EV charging stations may induce instability in key system parameters such as substantial voltage drops, active power losses, and transformer overload due to high demand during charging periods. This article presents a seasonal reconfiguration strategy based on the differential evolution (DE) algorithm, aimed at enhancing system performance under highly variable and stochastic load profiles, particularly those driven by EV charging. The DEA algorithm is hybridized with the find-union (FU) algorithm to efficiently ensure network radiality throughout the optimization process. The proposed methodology is validated on a hybrid distribution system composed of the IEEE 33-bus network, a modified IEEE 13-bus system, and a specific 13-bus microgrid. Results have demonstrated that seasonal reconfiguration significantly reduces active power losses and mitigates transformer loading during critical demand hours, thereby quantifiably increasing the system’s performance. As an integral component of the proposed approach, an analysis of CO2 emissions associated with energy losses is included, allowing a contextualized assessment of the environmental benefits of seasonal reconfiguration in various geographical areas.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Early Exploration of a Flexible Framework for Efficient Quantum Linear Solvers in Power Systems

The rapid integration of renewable energy resources presents formidable challenges in managing power grids. While advanced computing and machine learning techniques offer some solutions for accelerating grid modeling and simulation, there remain complex problems that classical computers cannot effectively address. Quantum computing, a promising technology, has the potential to fundamentally transform how we manage power systems, especially in scenarios with a higher proportion of renewable energy sources. One critical aspect is solving linear systems of equations, crucial for power system applications like power flow analysis, for which the Harrow-Hassidim-Lloyd (HHL) algorithm is a well-known quantum solution. However, HHL quantum circuits often exhibit excessive depth, making them impractical for current Noisy-Intermediate-Scale-Quantum (NISQ) devices. In this paper, we introduce a versatile framework, powered by NWQSim, that bridges the gap between power system applications and quantum linear solvers available in Qiskit. This framework empowers researchers to efficiently explore power system applications using quantum linear solvers. Through innovative gate fusion strategies, reduced circuit depth, and GPU acceleration, our simulator significantly enhances resource efficiency. Power flow case studies have demonstrated up to a eight-fold speedup compared to Qiskit Aer, all while maintaining comparable levels of accuracy.

quantum computing, Harrow-Hassidim-Lloyd, high-per↗
DOE OSTI2022

Laser Surface Processing of Alloys for Corrosion Protection (Final Project Report of Marine Energy Seedling Project)

This is the final project report for the MHK Seedling project. The report describes use of laser surface processing (LSP) to modify the surface of test materials (Al, steel) and the corrosion testing performed on the resulting samples in different corrosion environments. Data shows that LSP improved the corrosion resistance of Al and steel used in this work relative to respective non-LSP samples. The data also showed that each material had a specific range of laser processing conditions where the beneficial effects of LSP (i.e. improvement in corrosion protection) were observed. Application of LSP to enable low-cost materials in marine environments, additional microstructural analysis and long-term testing are proposed to further develop this technology for marine renewable energy and systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Renewable Thermal Energy Systems: Characterization of the Most Important Thermal Energy Applications in Buildings and Industry (Report 1)

This report is the first in a three-report series that evaluates the provision of renewable heat for industry and buildings via current and prospective renewable thermal energy system (RTES) technologies. The RTES project has undertaken initial research focused on technologies that could be suited for industrial process heat applications at different temperature levels, and, where possible, gathered performance and cost data for these technologies. This project does not directly evaluate RTES for distributed residential or commercial applications, nor does it yet include documented cases or modeling of RTES using geothermal, biomass, waste heat, renewable fuels like renewable natural gas, or hydrogen production. The three technical reports are summarized as follows: Renewable Thermal Energy Systems: Characterization of the Most Important Thermal Energy Applications in Buildings and Industry (Report 1), this report: summary of thermal demands of U.S. industry and buildings, and relevant hybrid RTES configurations; Renewable Thermal Energy Systems: Systemic Challenges and Transformational Policies (Report 2): discussion of socio-technical characteristics of RTES, innovation challenges, and supporting policies. Available at: https://www.nrel.gov/docs/fy23osti/83020.pdf; Renewable Thermal Energy Systems: Modeling Developments and Future Directions (Report 3): Energy yield and performance modeling of RTES, techno-economic analysis via case studies, and proposed development of a user decision support tool. Available at: https://www.nrel.gov/docs/fy23osti/83021.pdf.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Powered by dGen Webinar [Slides]

NLR's Powered By Webinar Series featuring NLR's dGen Modeling Tool. The Distributed Generation Market Demand (dGenTM) model simulates customer adoption of distributed energy resources for residential, commercial, and industrial entities in the United States or other countries through 2050. The model enables analysis at multiple geographic levels (national, state, and utility, or below) and offers sophistication in representation of decision-making regarding economic and behavioral considerations. Analysts have used dGen to answer questions about load forecasting and integrated resource planning, policy analysis, locational value of distributed energy resources, and more. dGen is open source, and various energy organizations - including independent system operators, regional transmission organizations, and the California Energy Commission - use the model internally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Insights from NREL’s Electrification Futures and LA100 Studies

Electrification of end-use technologies could have important implications for bulk power sector planning, operations, and impacts. By combining previously-defined electrification scenarios with capacity expansion modeling, we evaluate the potential challenges and opportunities associated with electrification. Our scenario analysis reveals that electrification reduces energy consumption and air emissions from across the energy sector, and its impacts on energy system costs are modest due, in part, to the abundance of low-cost resources in the United States.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

ESTABLISHING ETHICAL GUIDELINES FOR APPLYING ARTIFICIAL INTELLIGENCE TO IAEA SAFEGUARDS

Drawing upon globally recognized efforts by a variety of institutions, the paper develops a practical and defensible framework for consideration and use by the International Atomic Energy Agency (IAEA) to support the adoption of credible ethical standards for autonomous and intelligent systems (AIS). The analysis is based on a future hypothetical AIS that identifies signatures of misuse, diversion, and other research and development (R&D). The hypothetical system serves as an exemplar for subject matter expert (SME) workshop participants to begin to answer ethical AIS questions around how these systems should be governed and maintained, what the internal and external considerations associated with artificial intelligence (AI) tools are, and where the boundaries between ethical and non-ethical uses are. The ethical AIS workshop explored several important topics: (a) Recommendations that can be currently implemented by the IAEA, (b) Proposed defensible criteria and metrics aligned with an ethical AI for safeguards implementation, (c) Discussion of future needs and capabilities, and (d) Derive appropriate next steps and actions to support filling current technological, operational, and cultural gaps and realizing an effective ethical AI for safeguards framework. The Establishing Ethical Guidelines for Applying AI to IAEA Safeguards project creates awareness in the community of the ethical AIS approach.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Performance Validation of a Thermally Integrated 50 kW High Temperature Electrolyzer System

In the proposed project, INL and OxEon seek to improve the value proposition of hydrogen production by integrating reversible fuel cell operations at relatively small scale for distributed energy applications. This goal will be accomplished by converting a 50 kW solid oxide electrolysis cell or SOEC system into a reversible system that operates at 30 kW in electrolysis mode and approximately 10 kW in fuel cell mode. The reversible SOC system will be operated for over 3,000 hours using an improved catalyst in the fuel electrode. Steam for the electrolysis will come from an electric boiler Thermal Energy Distribution System that will be configured to mimic an industrial source of low-grade heat. Thermodynamic analysis will be performed to demonstrate the potential of the system to achieve >85% system efficiency in electrolysis mode. Finally, a technoeconomic analysis will be completed to show potential to produce hydrogen at a cost of $2/kg. The figure at the right indicates a target cost breakdown to achieve that goal.

08 HYDROGEN↗