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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dynamic land use implications of rapidly expanding and evolving wind power deployment

Abstract The expansion of wind power poses distinct and varied geographic challenges to a sustainable energy transition. However, current knowledge of its land use impacts and synergies is limited by reliance on static characterizations that overlook the role of turbine technology and plant design in mediating interactions with the environment. Here, we investigate how wind technology development and innovation have shaped landscape interactions with social and ecological systems within the United States and contribute to evolving land area requirements. This work assesses trends in key land use facets of wind power using a holistic set of metrics to establish an evidence base that researchers, technology designers, land use managers, and policymakers can use in envisioning how future wind-intensive energy systems may be jointly optimized for clean energy, social, and environmental objectives. Since 2000, we find dynamic land occupancy patterns and regional trends that are driven by advancing technology and geographic factors. Though most historical U.S. wind deployment has been confined to the temperate grassland biome in the nation’s interior, regional expansion has implicated diverse land use and cover types. A large percentage of the typical wind plant footprint (∼96% to > 99%) is not directly impacted by permanent physical infrastructure, allowing for multiple uses in the spaces between turbines. Surprisingly, turbines are commonly close to built structures. Moreover, rangeland and cropland have supported 93.4% of deployment, highlighting potential synergies with agricultural lands. Despite broadly decreasing capacity densities, offsetting technology improvements have stabilized power densities. Land use intensity, defined as the ratio of direct land usage to lifetime power generation of wind facilities, has also trended downwards. Although continued deployment on disturbed lands, and in close proximity to existing wind facilities and other infrastructure, could minimize the extent of impacts, ambitious decarbonization trajectories may predispose particular biomes to cumulative effects and risks from regional wind power saturation. Increased land-use and sustainability feedback in technology and plant design will be critical to sustainable management of wind power.

17 WIND ENERGY↗
DOE OSTI2022

Feedstock Carbon Intensity Calculator (FD-CIC): Users’ Manual and Technical Documentation

The carbon intensities (CIs) of biofuels are determined with the life cycle analysis (LCA) technique, which accounts for the energy/material uses and emissions during the complete supply chain of biofuel including feedstock production and fuel conversion stages. Regulatory agencies such as California Air Resources Board (CARB) adopts LCA to calculate biofuel CIs. The Low Carbon Fuel Standard (LCFS) program developed by CARB allows individual biofuel conversion facilities to submit their own biofuel CIs with their facility input data and incentivizes the reduction in the CI specific to that particular facility compared to a reference fuel’s CI (Liu et al 2020). Such an incentive program has driven innovations in biorefineries to reduce their greenhouse gas (GHG) emissions by linking their revenue directly to its CI score through LCFS credit trading. Besides the biofuel conversion stage, different farming practices for feedstock growth can result in significant CI variations for feedstocks, thus for biofuels. To provide evidence-based research findings, the U.S. Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) has supported the Systems Assessment Center of the Energy Systems and Infrastructure Analysis Division at Argonne National Laboratory to examine CI variations of different farming practices to grow agricultural crops for biofuel production. Meanwhile, the ARPA-E has launched the Systems for Monitoring and Analytics for Renewable Transportation Fuels from Agricultural Resources and Management (SMARTFARM) program to develop technologies and data platforms that enable an accurate measurement of key farming parameters that can help robust accounting of the GHG benefits of sustainable, low-carbon agronomic practices at farm level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

GEN3D Experimental and Numerical Development of GEN3 Durability Models

Understanding of the high temperature durability of particles and the materials that contain them is critical to next generation of concentrating solar power (CSP) technology. Here we studied the durability of particles and their containment materials under extreme UV cycling, thermal cycling, and in low-speed high temperature mechanical wear situations. The optical stability of seven candidate particles has been determined following exposure to the high temperature conditions present in a generation 3 particle-based CSP technology. Particle solar weighted absorptance and emittance measured periodically during 10,000 high solar irradiance exposure cycles and up to 400 hours of isothermal aging has been documented. The particle aging due to repeated exposure to concentrated solar flux represented the 30-year lifetime of a power plant. Models were fit to the absorptivity and emissivity data following the isothermal aging provides the projected optical degradation of the particles as a function of temperature. Mechanical wear was studied through the use of custom developed wear testing facilities for measuring high temperature impact wear, abrasion wear, and particle attrition. Additionally, a novel technique for measuring the high temperature mechanical properties of single particles was developed. Through these tests it was observed that high nickel alloys generally showed lower wear than comparable iron based steels, particularly at elevated temperatures of 800°C. Mechanical wear at these temperatures is a highly complex phenomenon combining both mechanical wear and oxidation. Additionally, the containment materials wear rates are influenced by the particles (both hardness and roundness), making the wear mechanisms complex. The initial wear test conducted in the abrasion test rig revealed a substantial amount of oxide materials in the particle bed after testing (in relative to later tests), and substantially more wear, likely indicating a need for concern in startup operation of particle facilities to not incur high wear from the presence of oxides. Particle attrition experiments have only been conducted for a single material but increase size distribution, reduction in circularity, and particle diameter is observed. Efforts to develop predictive models was limited due to a testing campaign that prioritized testing materials for particle pathway developers over building a comprehensive design of experiments. The results discussed in this report inform future CSP developers and researchers further de risking the technology and assisting in its future development. ParticleBased CSP development provides a path to dispatchable solar power generation with storage at a price competitive in the current energy market. Lowering the cost of CSP technology provides a carbon free power generation solution that can assist in the transition from fossil fuels to renewable sources of electricity.

14 SOLAR ENERGY↗
DOE OSTI2023

Distributed Coaxial Cable Sensors for In-Situ Condition Based Monitoring of Coal-Fired Boiler Tubes

The increasing contributions of renewable energy sources present new challenges to the operation and maintenance of the existing coal-fired power plants. One of the major operational risks is the unexpected failure of superheater boiler tubes, leading to the most unplanned power plant outrages. The boiler tube failure is difficult to predict due to the harsh operating environments. Therefore, condition-based monitoring (CBM) with a reliable high temperature sensor becomes necessary to produce a meaningful assessment of the health condition of boiler tubes and their remaining lifetime. In this work, the stainless-steel and quartz coaxial cable sensor (SSQ-CCS) is proposed for in-situ distributed monitoring of the boiler tube temperatures in existing coal-fired power plants. Comprehensive tests have been conducted with an in-house testing facility at Clemson University to study and evaluate the sensors’ performance in the temperature range of 100℃ to 600℃. The results indicated that the measurement resolution of the SSQ-CCS sensor is better than 1℃, and the drift is less than 2% over long-period testing. Meanwhile, multi-physics finite element analysis has been conducted to optimize the design and evaluate the safety of the SSQ-CCS temperature sensor under various operational conditions. Based on the performance obtained in the laboratory-scale testing, a field test has been implemented at a power plant. Four SSQ-CCS temperature sensors were installed for in-situ monitoring of the temperatures of a power plant’s superheat tube assembles. The data acquisition system has been successfully set up and collected sensing signals for more than three months. The sensing signals have been post-processed, and the monitored temperature history through the SSQ-CCS temperature sensor has been validated and compared with the conventional high temperature thermal couple data.

Jiao, Xinyu↗
DOE OSTI2024

Performance Year 1 Technical Report - OPEN COG Grid: Extendable Coherent Models-Datasets for Cognitive Power Grids

The OPEN COG Grid project is a collaborative effort between LLNL, NREL, and Texas A&M University (TAMU) to develop synthetic power system datasets that (i) contain all technical information that would be available in a real system, allowing to conduct studies ranging from dynamic simulation to long term planning studies; ii) are accessible to researchers from the broader data sciences community, as oppossed to power system experts only; and (iii) This report summarizes the work conducted during the first 15 months of execution of the project. These activities encompassed: 1. Conduct a survey of existing open data sets and open source power systems simulators, their supported use cases, and accessibility (Chapter 1). 2. Define a new extensible specification for power system data, covering all parameters necessary for most computational use cases (Chapter 2). 3. Collecting real technical system data to complete missing parameters in existing open source datasets (Chapter 3). 4. Develop models that capture the behavior of emergent actors in power grids, neglected by existing datasets; aggregated residential demand response (Chapter 4) and demand response of cryptocurrency miners (Chapter 5). 5. Collect detailed spatial information on distributed energy resources, particular, solar photovoltaic facilities (Chapter 6). The following chapters provide detailed descriptions of these tasks, the assumptions taken, and their findings. In conducting these tasks, the project team produced: two (accepted) conference papers; one journal paper under submission; one draft journal paper pending submission; released one repository with the developed power system data specification, with documentation and examples; and one extended dataset for the Texas power grid under review for release. The team hopes these contributions will enhance access to power system data and remove barriers to the development of new computational techniques for power systems, particularly, those inspired by cognitive sciences.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Addressing Inherent Challenges to Chemical Relithiation of Cycled End‐of‐Life Cathode Materials

Recycling end‐of‐life (EOL) lithium‐ion batteries (LIBs) is important to retain valuable resources from critical materials present in EOL battery waste. Direct recycling methods offer an opportunity to recover intact valuable cathode materials with minimal re‐processing. An important step of the direct recycling process is relithiation which is used to restore lithium content to EOL cathode materials. However, little has been done to study how preprocessing steps such as washing or binder removal may affect relithiation methods in the direct recycling process. Here, the evolution of fluorine byproducts left over from preprocessing steps during a low‐temperature chemical redox mediator relithiation process is tracked. A facile washing step is presented as a solution for mediating adverse effects of surface contamination on the chemical relithiation performance. The structure, lithium content, and electrochemical performance of relithiated EOL NMC 622 material that underwent a pre‐relithiation washing step to remove fluorine byproducts is shown to match that of pristine NMC 622. In this work, it is showed that redox mediator relithiation as a part of a direct recycling process is a promising low energy method that can be applied to EOL material with inherent surface impurities if the proper pre‐relithiation processing steps are implemented.

25 ENERGY STORAGE↗
DOE OSTI2023

AN OVERVIEW OF THE DESIGN AND PERFORMANCE TESTING OF A 275 BAR INTEGRALLY GEARED SUPERCRITICAL CO2 COMPRESSOR FOR POWER GENERATION

An integrally geared compressor-expander (compander) for supercritical CO2 (sCO2) was developed to convert thermal energy to electricity. With operating pressures of 275 bar, this turbomachine represents the state of the art in integrally geared machine architecture, hitting compressor inlet densities of 600 kg/m3 and discharge pressures of 275 bar. The product development was funded by the Department of Energy’s Energy Efficiency and Renewable Energy Office under EE0007114 to advance the state of the art in concentrated solar power applications; however, the technology itself is agnostic to heat source, and is predicted to achieve a thermal-to-electric conversion efficiency of 50% for any indirect heat source capable of providing turbine inlet temperatures of 700°C or greater. While the program encompassed the design and testing for the compressor and turbine elements, this paper will focus on the compressor design and operation. The paper will begin with an introduction to the cycle design and analysis of an indirectly heated integrally geared sCO2 compander, a discussion of the mechanical and aerodynamic design of the compressor that is a two stage radial compressor operating subcritically at 27,512 rpm, and will then proceed to describe the test facility and measured data to characterize the performance and robustness of the machine. The paper will conclude with a discussion on lessons learned throughout the course of commissioning and testing. Practical aspects of testing a compressor operating near the dome including complications relating to obtaining an accurate compressor flow map, efficiency calculations, flow unsteadiness, and associated measurement uncertainties will be discussed.

wilkes, jason↗
DOE OSTI2026

Energy Resilience Options for the Koolauloa Community Resilience Hub – Energy Technology Innovation Partnership Project, Cohort 2: Summary of Findings and Assessment

Hui o Hau‘ula (HoH) is a community organization dedicated to the well-being of the population of the Ko‘olauloa district on the Hawaiian island of Oahu. In response to growing concerns about challenges related to extreme weather events or natural disasters, HoH formulated the concept of the Ko‘olauloa Community Resilience Hub, or KCRH. The KCRH facility would serve as a focal point for the community during normal conditions, while also providing essential services and acting as a safe space during emergencies, natural or man-made. The concept of the KCRH was initially developed in partnership with the Hawaii Natural Energy Institute, +Lab Architects, and the City and County of Honolulu. In the fall of 2023, the U.S. Department of Energy, under the Energy Technology Innovation Partnership Project Program (ETIPP), provided support to the KCRH project, in the form of technical assistance (TA) to be provided by its National Laboratory complex. In this case, the core TA was provided by Sandia National Laboratories, and it was directed to providing options for designing an energy system based at the KCRH that could support critical loads in the event of a 30- day grid outage. The National Renewable Energy Laboratory (NREL) provided communications and logistics support in the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation

Impacts to baleen whales are of particular concern in the context of offshore wind development because of their conservation status, the overlap of their habitat with current and planned offshore wind energy facilities, and their expected sensitivity to low-frequency sounds, such as those produced during pile driving. Therefore, this report focuses on monitoring technologies capable of detecting this species group. The scope of this report is to assess the current state of technologies and methods for monitoring baleen whales in low- and no-light conditions in conjunction with offshore wind foundation installation. This work considers the performance of various sensing technologies that can be used to observe the presence of baleen whales near offshore construction activities. The scope of work includes: 1. Technology Performance Metrics – Identify metrics that can be used to assess technology performance. 2. Technology Evaluation – Synthesize the past performance of technologies with respect to the performance metrics based on available literature. 3. Technology Characterization Framework – Describe a potential framework to characterize technology performance with a standardized approach. 4. Technology Research and Development Needs – Identify future needs and opportunities for research, development, and deployment to improve technologies.

17 WIND ENERGY↗
DOE OSTI2024

Tandem Predictions for HPC Jobs

At the core of the predictive analytics applied to High Performance Computing (HPC), the most prominent tasks are the prediction of job runtimes and the prediction of job queue times, both of which have the potential for informing HPC users during their every-day decision making. Accurate runtime predictions can help users better choose so-called wallclock times at job submission, decreasing the odds of their jobs waiting in queues longer than necessary. The accurate and timely queue time predictions offered for the available partitions can inform the favorable selection of partitions for running jobs. This potential is well understood as we see in the abundance of research studies that propose solutions for these tasks, including the work published in the last several years. These tasks are seemingly receptive to the Machine Learning (ML) solutions, considering that there is no shortage of training data where HPC centers over time run millions and millions of jobs. However, we study the existing research literature, as well as look for examples in the toolchains supported on the exemplar HPC facilities, and, surprisingly, do not find any practical solutions that are ready to be adopted. We interpret this as a manifestation of the shortage of UX/UI efforts that support HPC analytics and also as a sign that the research has not come to the consensus on solving these tasks. In this study, we aim to shed new light on the long-running task of job queue time prediction by exploring the utility of runtime predictions in improving prediction accuracy and, actually, predicting these two metrics together, in tandem. In other words, we show how runtime predictions become valuable input in the queue time modeling. We challenge the existing approaches to feature engineering for the queue time prediction and describe promising results we obtained for a large dataset of HPC jobs from a supercomputer at the National Renewable Energy Laboratory.

HPC↗
DOE OSTI2025

Tandem Predictions for HPC Jobs: Preprint

At the core of the predictive analytics applied to High Performance Computing (HPC), the most prominent tasks are the prediction of job runtimes and the prediction of job queue times, both of which have the potential for informing HPC users during their every-day decision making. Accurate runtime predictions can help users better choose so-called wallclock times at job submission, decreasing the odds of their jobs waiting in queues longer than necessary. The accurate and timely queue time predictions offered for the available partitions can inform the favorable selection of partitions for running jobs. This potential is well understood as we see in the abundance of research studies that propose solutions for these tasks, including the work published in the last several years. These tasks are seemingly receptive to the Machine Learning (ML) solutions, considering that there is no shortage of training data where HPC centers over time run millions and millions of jobs. However, we study the existing research literature, as well as look for examples in the toolchains supported on the exemplar HPC facilities, and, surprisingly, do not find any practical solutions that are ready to be adopted. We interpret this as a manifestation of the shortage of UX/UI efforts that support HPC analytics and also as a sign that the research has not come to the consensus on solving these tasks. In this study, we aim to shed new light on the long-running task of job queue time prediction by exploring the utility of runtime predictions in improving prediction accuracy and, actually, predicting these two metrics together, in tandem. In other words, we show how runtime predictions become valuable input in the queue time modeling. We challenge the existing approaches to feature engineering for the queue time prediction and describe promising results we obtained for a large dataset of HPC jobs from a supercomputer at the National Renewable Energy Laboratory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Methodology for Determination of Cellulosic Glucans and Hemicellulose Content in a Fuel Ethanol Production Facility (CRADA Final Report)

Develop a single methodology for determination of the total cellulosic glucan, including both cellulose and beta-glucans, along with hemicellulose content in corn kernel fiber which could be utilized by the dry grind corn ethanol production industry to determine the cellulosic converted fraction of the corn kernel fiber. The work will build upon a methodology already described in literature but will specifically focus on a more complete determination of the structural polysaccharides in corn kernel fiber to make it more applicable to the corn ethanol industry.

09 BIOMASS FUELS↗
DOE OSTI2023

Hydroelectric Power and Hydrogen Production Integration

Hydropower-based hydrogen production could introduce opportunities for new revenue streams for hydropower plants, including from energy storage and regeneration as well as from sale of the hydrogen product to external markets. Hydrogen-based energy storage and regeneration could also help support Idaho Power’s decarbonization goals by decreasing dependence on fossil-based peaking power plants. Additionally, integration of hydrogen production with hydropower generation could help address the issue of low dissolved oxygen river water conditions that commonly accompany hydropower plant operations by utilizing the oxygen byproduct from an electrolytic hydrogen production process as a resource for mitigation of low dissolved oxygen water conditions. Comprehensive techno-economic analysis of the hybrid hydroelectric and hydrogen energy storage system has revealed critical insights into the pathways and considerations for optimizing the economic value and environmental benefits of such systems. Among the three identified pathways of natural gas blending, regeneration, and direct sale of hydrogen, the direct sale of hydrogen emerges as the most profitable, particularly given the current pricing dynamics of hydrogen and electricity. However, as we anticipate a future grid characterized by higher renewable energy penetration, the landscape may evolve, featuring lower average electricity prices, heightened fluctuations, and more significant seasonal variations. Consequently, the attractiveness of electricity regeneration through hydrogen and the benefits of long-duration hydrogen storage are expected to increase substantially in such a dynamic energy scenario. The careful selection of component sizes within the hybrid system proves to be paramount for ensuring cost-effectiveness. Notably, the size of the hydrogen market has emerged as a critical determinant for the optimal size of the electrolyzer. Hydrogen storage should be sized to meet energy shifting requirements. The appropriate size of the fuel cell/microturbine generator hinges on the shape of electricity prices and the available revenue streams derived from participating in grid services. Striking the right balance among these components is essential for maximizing the overall efficiency and profitability of the hydrogen facility. Furthermore, the by-product of electrolysis, namely oxygen, introduces an additional dimension to the system's functionality. The oxygen generated can be effectively utilized for dissolved oxygen (DO) mitigation, particularly with larger electrolyzer sizes capable of satisfying the complete oxygen demand for this purpose. While the economic benefits derived from saved oxygen purchase costs may be relatively modest compared to other revenue streams, the environmental advantages of repurposing oxygen for DO mitigation could help Idaho Power meet their environmental obligations. In addition to the identified factors shaping the viability of hybrid hydrogen production and hydroelectric generation, it is noteworthy that the integration of hydrogen energy storage offers a unique advantage during unusually wet years. In such periods of increased water inflow, the hydrogen storage capacity serves as a valuable supplement to the reservoir. By utilizing hydrogen energy storage as a complementary reservoir, the system gains flexibility in reservoir management when dealing with fluctuations in water availability.

08 HYDROGEN↗
DOE OSTI2022

Economic dispatch for electricity merchant with energy storage and wind plant: State of charge based decision making considering market impact and uncertainties

Here this paper investigates how the market impact of electricity merchants and uncertainty of wind generation affect their co-optimized scheduling policy, specifically for merchants who have both energy storage and wind plants. In the existing literature, merchants' trading actions are usually assumed not to affect market prices; however, a large-scale energy storage merchant's actions can affect market prices. To this end, we approximate the electricity price by a linear function of the quantity of power traded by the merchant in the reward function to achieve decision-making incorporating the market impact. This paper utilizes the dynamic programming approach to analyze merchants' optimal multi-period decision-making incorporating market impact, uncertain wind generation, and energy storage constraints. First, our results demonstrate that for a merchant with co-located energy storage facilities and wind power plants, the energy storage's feasible state of charge (SOC) range can be segmented into four possible sub-ranges by three analytically developed SOC reference points. The unique optimal trading decision can be achieved by comparing the current energy inventory and the SOC references of the next period. Second, our results show that market impact and uncertainties substantially change the optimal storage scheduling policy by impacting the values of the reference points. To mitigate the negative effect of the merchant's market impact on buying and selling actions, the merchant may reduce the amount of generating or pumping electricity each period to maximize profit. Moreover, we identify and investigate the trade-off between market price and transaction quantity. Our findings provide co-optimized scheduling guidance for electricity merchants with co-located energy storage and renewable power plants systems.

17 WIND ENERGY↗
DOE OSTI2025

Ecovoltaic solar energy development can promote grassland bird communities

Ecologically informed photovoltaic (PV) developments that co-prioritize PV electricity generation with ecosystem function (‘ecovoltaics’) have emerged as a promising land sharing strategy to minimize ecological conflicts associated with PV solar energy development. While habitat-focused ecovoltaic designs can conceptually benefit biodiversity by offsetting or enhancing impacts of PV development, foundational field research is needed to examine how wildlife respond to these novel ecosystems. We conducted passive acoustic monitoring (PAM) in 2023 and 2024 at 13 solar facilities and paired control sites to investigate avian community responses to ecovoltaic facilities in the Midwestern United States. Compared to control sites (row crop agricultural fields), we found that ecovoltaic sites supported more grassland bird species throughout a 17-week monitoring period between May and September. Grassland bird communities on ecovoltaic sites were also more stable than on agricultural controls, as measured by the Jaccard dissimilarity index. We also used PAM-based weekly species occurrences in an occupancy-modelling framework to investigate the influence of PV development and other landscape variables on grassland bird occupancy. 10 out of 13 modelled grassland bird species had greater predicted occupancy probabilities (ψ) on PV sites than control sites. Synthesis and applications. Our findings suggest that properly sited and developed ecovoltaic solar facilities in human altered landscapes can improve habitat for birds and other wildlife, but further research is needed to understand which species may benefit most from these novel ecosystems.

14 SOLAR ENERGY↗
DOE OSTI2021

TCR Input to NUREG-1537 Process for Advanced Nuclear Technologies Derived from Additive Manufacturing

There has been a renewed interest by several advanced reactor developers to use NUREG-1537 “Guidelines for Preparing and Reviewing Applications for the Licensing of Non-Power Reactors” as a basis for their safety analysis report content and organization. Recently, SHINE Medical Technologies, LLC (SHINE), which is a non-power, Aqueous Homogenous Reactor design radioisotope production facility, received a construction permit based around their NUREG-1537 safety evaluation report (ADAMS No. ML16229A140). Advanced reactor developers are interested in using NUREG-1537 as a basis for their safety analysis report content and organization because of its successful application towards research reactors, graded approach, and simplicity in structure and requirements. However, NUREG-1537 is still largely geared toward light water reactors (LWRs) and many improvements could be made or supported through guidance documents for advanced reactors. For nuclear power to play a role in the future zero-carbon energy portfolio, a supportive regulatory structure is needed to lower regulatory uncertainty and barriers to deployment. At the time of this report, no such document or pathway exists for advanced nuclear technologies, including those derived from nontraditional technology such as advanced manufacturing technology (AMT) and, specifically, additive manufacturing. This report will explore and provide recommendations as to how advanced nuclear technologies derived from additive manufacturing technologies could employ the use of an ISG, other guidance document, or revisions to NUREG-1537 to lower the regulatory uncertainty and barriers for adoption.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Holistic Fuel Cell Electric Vehicle/Hydrogen Station Optimization Model (CRADA CRD-18-00745 Final Report)

The National Renewable Energy Lab (NREL), Argonne National Lab (ANL), Sandia National Lab (SNL), and Frontier Energy, Inc comprise a team that will perform a review of currently available models that can simulate both a hydrogen station and a fuel cell electric vehicle (FCEV), and whose owners are willing to make them available freely. We will then down select to a single model or model pair, secure agreements for their free use, and validate the resulting model or coupled models. For example, we may evaluate an existing 1-D hydrogen fueling model developed by Kyushu University for the Japanese New Energy and Industrial Technology Development Organization (NEDO). The validation will take place using data from various sources, potentially including the European Joint Research Center (JRC) HyTransfer project, SAE testing performed by Powertech to validate SAE J2601, and whole-station validation using the NREL’s Hydrogen Infrastructure Testing and Research Facility (HITRF). The team will make the model and all the validation data open to the public at the end of the project.

1-D hydrogen fueling model↗
DOE OSTI2022

Optimal Wind Turbine Design for H2 Production

NREL and industrial partners GE and Nel seek to advance affordable green hydrogen production by optimizing wind turbine design specifically for hydrogen production and validating designs using NREL's ARIES facilities. This project will couple wind turbine, wind plant, solar plant, and electrolyzer models to predict hydrogen production from variable, renewable power sources. It will then use gradient-based optimization with exact-analytic gradients to optimize wind turbine rotor diameter, hub height, and power rating for optimal hydrogen production. Finally, it will validate the optimal turbine designs using the ARIES research platform, where it will compare a baseline turbine to the optimal design for a variety of scenarios and resources.

electrolyzer↗