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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Revenue Opportunities through Ancillary Services for Nuclear Power Plants with Integrated Firebrick Resistance- Heated Energy Storage (FIRES)

Deregulation of electricity markets has brought about major changes in the ways investments in and operation of power plants are planned and optimized. Although many NPPs have seen reduced revenue in recent years as power purchase agreement end and wholesale market electricity prices have remained low, there are opportunities to expand the technical capabilities of NPPs, participate in additional market services and increase revenue. This transaction summarizes the opportunities provided by participation in ancillary services markets potentially made possible by integration of thermal energy storage capacity, specifically the Firebrick Resistance-heated Energy Storage System (FIRES), into future nuclear power plants with high-temperature reactors and Nuclear Air-Brayton combined cycle (NACC) power conversion. The restructuring, or deregulation, of electric power systems in most of Europe and North America has had a substantial impact on the economic performance of currently operating nuclear power plants (NPPs) and the prospects for new builds. Owners of NPPs in some markets have expressed concern that low wholesale electricity market prices and insufficient compensation for capacity, reliability, and other services are threatening the financial viability of their plants. However, both current and future NPPs have the potential to increase their competitiveness by increasing the flexibility of their electricity output. Flexible output has previously only been possible in water-cooled reactors through load-following operation, which requires core power maneuvers and operation of the steam turbine at reduced efficiency. Integration of thermal energy storage systems (TESS) provides an alternative, providing the plant the option to either output electricity or store heat for greater later electric output. The plant owner may thus increase sales of electricity during hours when it is most valuable. Even more, some TESS technologies have the potential to greatly increase the net ramp rate capability of the plant. The ability to rapidly change net power output to the grid may make it possible for NPPs to secure additional revenue by providing additional minute-by-minute balancing services to the grid. FIRES is only one technology out of many that might provide additional technical capabilities at NPPs, and this discussion has only highlighted the opportunities in a single market. Analysis of other options, include steam accumulator systems, nitrate salt TESS, phase change material TESS, and opportunities in other markets are subjects of ongoing work. Deregulation of electricity markets has brought about major changes in the ways investments in and operation of power plants are planned and optimized. Although many NPPs have seen reduced revenue in recent years as power purchase agreements end and wholesale market electricity prices have remained low, there are opportunities to expand the technical capabilities of NPPs, participate in additional market services, and increase revenue. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

High-Frequency Signature-Based Fault Detection for Future MV Distribution Grids

Increasing penetration levels of inverter based distributed energy resources (DERs) impact the legacy distribution system protection. Inverter based DERs provide approximately 1.2-2 pu fault current. In systems with high penetration of inverter based DERs, it is difficult for over-current based protection schemes to differentiate between normal loading conditions and a fault. Directional, distance, and adaptive forms of protection schemes are also affected by low fault currents. This paper analyzes fault generated traveling wave (TW) based high-frequency signatures in the distribution system. In order to simulate such signatures, frequency-dependent distributed parameter line modeling approach is used in this research work to represent distribution lines and underground cables. Modified IEEE 13-bus medium voltage test system is modeled in electromagnetic transient simulation tool and multiple transient scenarios are simulated in this test system. The results are analyzed to understand the high-frequency signatures that can be used to detect and locate faults under high penetration of DERs.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS2013

Multi-Dimensional Damage Detection for Surfaces and Structures

Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or sensory system, which may include a time domain reflectometer, resistivity monitoring hardware, or other resistance-based systems. To begin, a layered composite consisting of thin-film damage detection layers separated by non-damage detection layers is fabricated. The damage detection layers are attached to a detector that provides details regarding the physical health of each detection layer individually. If damage occurs to any of the detection layers, a change in the electrical properties of the detection layers damaged occurs, and a response is generated. Real-time analysis of these responses will provide details regarding the depth, location, and size estimation of the damage. Multiple damages can be detected, and the extent (depth) of the damage can be used to generate prognostic information related to the expected lifetime of the layered composite system. The detection system can be fabricated very easily using off-the-shelf equipment, and the detection algorithms can be written and updated (as needed) to provide the level of detail needed based on the system being monitored. Connecting to the thin film detection layers is very easy as well. The truly unique feature of the system is its flexibility; the system can be designed to gather as much (or as little) information as the end user feels necessary. Individual detection layers can be turned on or off as necessary, and algorithms can be used to optimize performance. The system can be used to generate both diagnostic and prognostic information related to the health of layer composite structures, which will be essential if such systems are utilized for space exploration. The technology is also applicable to other in-situ health monitoring systems for structure integrity.

Williams, Martha↗
DOE OSTI2024

Analysis of thermal and mechanical properties with inventory level of the molten salt storage tank in central receiver concentrating solar power plants

Molten salt thermal energy storage (TES) tanks ensure steady power output of concentrating solar power (CSP) plants; however, recent tank failures have highlighted the need for further analysis. Current studies primarily focus on analyzing the molten salt flow, heat transfer, and thermal efficiency. Additionally, research on the latest tank structures is limited and lacks newest experimental validation. This study measures temperature and molten salt inventory levels in the high-temperature tank at a 50 MW central receiver CSP plant, connected to the power grid in 2019. A multi-physics model was developed to evaluate thermal and mechanical properties of TES tanks by combining computational fluid dynamics and finite element modeling using real plant data. Heat loss, temperature, displacement, and stress distribution of the tank at different inventory levels were investigated. Results show that ambient air velocity near the tank roof reaches 2.14 m/s, much higher than 0.2 m/s near the wall. The temperatures of inventory fluid and tank are close, varying slightly at different levels due to thermal conduction and radiation. Because the heat loss strongly depends on temperature, the total tank loss remains nearly constant across inventory levels. Larger temperature gradients and thermal stresses are primarily localized along the tank floor edge and the air-salt interface. Notably, the maximum thermal stress at the tank edge is three times higher than that at the interface. The magnitude of total stress changes by less than 5 MPa with and without thermal load, indicating that high temperatures exert only a minor impact on tank stress. In contrast, thermal load significantly affects tank deformation, particularly at the roof edge, where values exceed 150 mm. Despite the large variation in molten salt levels, tank wall temperatures and displacements present a minor change, suggesting a weak correlation with inventory levels. In conclusion, the findings obtained in this study provide important insights on the TES tank that could be used to optimize tank design and operation strategies.

14 SOLAR ENERGY↗
DOE OSTI2016

Comprehensive Solutions for Integration of Solar Resources into Grid Operations

The need for proactive closed-loop integration of uncertainty information into system operations and probability-based controls is widely recognized, but rarely implemented in system operations. Proactive integration for this project means that the information concerning expected uncertainty ranges for net load and balancing requirements, including required balancing capacity, ramping and ramp duration characteristics, will be fed back into the generation commitment and dispatch algorithms to modify their performance so that potential shortages of these characteristics can be prevented. This basic, yet important, premise is the motivating factor for this project. The achieved project goal is to demonstrate the benefit of such a system. The project quantifies future uncertainties, predicts additional system balancing needs including the prediction intervals for capacity and ramping requirements of future dispatch intervals, evaluates the impacts of uncertainties on transmission including the risk of overloads and voltage problems, and explores opportunities for intra-hour generation adjustments helping to provide more flexibility for system operators. The resulting benefits culminate in more reliable grid operation in the face of increased system uncertainty and variability caused by solar power. The project identifies that solar power does not require special separate penetration level restrictions or penalization for its intermittency. Ultimately, the collective consideration of all sources of intermittency distributed over a wide area unified with the comprehensive evaluation of various elements of balancing process, i.e. capacity, ramping, and energy requirements, help system operators more robustly and effectively balance generation against load and interchange. This project showed that doing so can facilitate more solar and other renewable resources on the grid without compromising reliability and control performance. Efforts during the project included developing and integrating advanced probabilistic solar forecasts, including distributed PV forecasts, into closed –loop decision making processes. Additionally, new uncertainty quantifications methods and tools for the direct integration of uncertainty and variability information into grid operations at the transmission and distribution levels were developed and tested. During Phase 1, project work focused heavily on the design, development and demonstration of a set of processes and tools that could reliably and efficiently incorporate solar power into California’s grid operations. In Phase 2, connectivity between the ramping analysis tools and market applications software were completed, multiple dispatch scenarios demonstrated a successful reduction of overall uncertainty and an analysis to quantify increases in system operator reliability, and the transmission and distribution system uncertainty prediction tool was introduced to system operation engineers in a live webinar. The project met its goals, the experiments prove the advancements to methods and tools, when working together, are beneficial to not only the California Independent System Operator, but the benefits are transferable to other system operators in the United States.

14 SOLAR ENERGY↗
DOE OSTI2022

Scout Benchmark Scenarios for U.S. Building Energy and CO2 Emissions to 2050

Overview and Intended Use Cases: These scenarios establish a range of futures for U.S. buildings sector energy use and CO2 emissions to 2050 using Scout (scout.energy.gov), a reproducible and granular model of U.S. building energy use, emissions, and consumer costs developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office (BTO). Scout benchmark scenario data are suitable for the following example use cases: setting high-level policy goals for the U.S. buildings sector to 2050 (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050); exploring the effects of key dynamics driving U.S. buildings sector energy and CO2 emissions to 2050 that could be affected by policy levers (e.g., raising minimum technology performance levels; accelerating electrification and/or retrofit rates; introducing breakthrough technologies to the market); determining priority segments (regions, building types, and end use/technology types) and sequencing of U.S. buildings sector energy and CO2 emissions reductions to 2050 under a given set of assumptions; and/or identifying the energy and emissions impacts or cost effectiveness of specific technologies or operational approaches of interest—in isolation or after considering competition with other measures in a scenario portfolio. Scenario Summary: A total of 8 scenarios explore the effects of changes across both the demand- and supply-side of building energy use on annual U.S. building energy use and CO2 emissions from 2022–2050. Scenarios are organized into three groups representing low, moderate, and best-case potentials for building decarbonization, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗
DOE OSTI2023

Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.

capacity expansion↗
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
DOE OSTI2018

2014-2018 Summary of NCAR activities in the Earth Energy Exascale System Model (E3SM) project

NCAR participation in E3SM activities as part of this funded collaborative project has been successful in leveraging the existing atmosphere model development experience from CESM scientists and applying it to initial v1 atmosphere model (EAM) development and analysis. NCAR partners collectively had many decades of experience in parameterization development, running and tuning coupled models and building the required software infrastructure to support ongoing model developments. Furthermore, collaboration between E3SM and CESM developers was of mutual benefit to both modeling endeavors. In the earlier periods of the project, participation in E3SM both complemented core critical path DOE activities and advanced individual parameterization development; including orographic drag, convection parameterization, convective gustiness and cloud and microphysical processes. Significant progress has been made implementing model capabilities for separating out the physics and dynamics grids, and providing the infrastructure for including orographic elevation class communication between the land and atmosphere models. Our activities working with the E3SM workflow and software engineering teams have established efficient protocols and infrastructure for the sharing of CESM and E3SM model codes of interest to both modeling groups, a large component of which is the mutual communication of common code bugs. As well as these specific project tasks all NCAR project members have been regular participants in atmosphere and coupled group telecons, as well as PI meetings. We have been fully engaged with and contributed to decisions regarding v1 atmosphere model developments, coupled model simulations, model tunings, and software engineering infrastructure. NCAR’s contribution to more recent E3SM development activities has centered on analysis of v1 release and pre-release simulations in order to address outstanding systematic biases and communicate climate improvements. Of particularly note is the work in understanding clouds and cloud feedbacks, shortcomings in ENSO and sub-seasonal variability; in particular the Madden Julian Oscillation (MJO). Contributions have been made to a number of papers that are currently published or in preparation detailing model performance in CMIP6-protocal experiments. They outline the simulations of mean climate, clouds and convection processes, convective gustiness, atmospheric blocking coupled climates. The contributions of NCAR’s funded activities to the E3SM atmosphere in the initial years of the project have had a positive impact on many aspects of the model simulations described in these papers.

58 GEOSCIENCES↗
DOE OSTI2015

Turbulent kinetics of a large wind farm and their impact in the neutral boundary layer

High-resolution large-eddy simulation of the flow over a large wind farm (64 wind turbines) is performed using the HIGRAD/FIRETEC-WindBlade model, which is a high-performance computing wind turbine–atmosphere interaction model that uses the Lagrangian actuator line method to represent rotating turbine blades. These high-resolution large-eddy simulation results are used to parameterize the thrust and power coefficients that contain information about turbine interference effects within the wind farm. Those coefficients are then incorporated into the WRF (Weather Research and Forecasting) model in order to evaluate interference effects in larger-scale models. In the high-resolution WindBlade wind farm simulation, insufficient distance between turbines creates the interference between turbines, including significant vertical variations in momentum and turbulent intensity. The characteristics of the wake are further investigated by analyzing the distribution of the vorticity and turbulent intensity. Quadrant analysis in the turbine and post-turbine areas reveals that the ejection motion induced by the presence of the wind turbines is dominant compared to that in the other quadrants, indicating that the sweep motion is increased at the location where strong wake recovery occurs. Regional-scale WRF simulations reveal that although the turbulent mixing induced by the wind farm is partly diffused to the upper region, there is no significant change in the boundary layer depth. The velocity deficit does not appear to be very sensitive to the local distribution of turbine coefficients. However, differences of about 5% on parameterized turbulent kinetic energy were found depending on the turbine coefficient distribution. Furthermore, turbine coefficients that consider interference in the wind farm should be used in wind farm parameterization for larger-scale models to better describe sub-grid scale turbulent processes.

17 WIND ENERGY↗
DOE OSTI2021

The impact of alkali‐ion intercalation on redox chemistry and mechanical deformations: Case study on intercalation of Li, Na, and K ions into FePO 4 cathode

Abstract Batteries made of charge carriers from Earth‐crust abundant materials (e.g., Na, K, and Mg) have received extensive attention as an alternative to Li‐ion batteries for grid storage. However, a lack of understanding of the behavior of these larger ions in the electrode materials hinders the development of electrode structures suitable for these large ions. In this study, we investigate the impact of alkali ions (Li, Na, and K) on the redox chemistry and mechanical deformations of iron phosphate composite cathodes by using electrochemical techniques and in situ digital image correlation. Na‐ion and Li‐ion intercalation demonstrate a nearly linear correlation between electrochemical strains and the state of charge and discharge. The strain development shows nonlinear dependance on the state of charge and discharge for K ions. Strain rate calculations show that K ion intercalation results in a progressive increase in the strain rate for all cycles. Li and Na intercalation induce nearly constant strain rates with the exception of the first discharge cycle of Na intercalation. When the same amount of ions are inserted into the electrode, the electrode shows the lowest strain generation upon Li intercalation compared to larger alkali ions. Na and K ions induce similar volumetric changes in the electrode when the state of charge and discharge is around 30%. Although the electrode experiences larger absolute strain generation at the end of the discharge cycles upon Na intercalation, strain rates were found to be greater for K ions. Potential‐dependent behaviors also demonstrate more sluggish redox reactions during K intercalation, compared to Li and Na. Our quantitative analysis suggests that the strain rate, rather than the absolute value of strain, is the critical factor in amorphization of the crystalline electrode.

25 ENERGY STORAGE↗
DOE OSTI2016

Satellite detection of soil moisture related water stress impacts on ecosystem productivity using the MODIS-based photochemical reflectance index

We report satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate global terrestrial ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to vegetation photosynthetic light use efficiency (LUE), GPP and canopy water-stress. Here in this paper, we use the NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing major plant functional type (PFT) classes within the continental USA (CONUS) to assess GPP sensitivity to soil moisture related water stress. The sPRI (scaled PRI) metric derived using MODIS band 13 as a reference channel (sPRI13) shows generally higher correspondence with tower GPP estimates than other potential MODIS reference bands. The sPRI13 observations were used as a proxy for soil moisture related water supply constraints to LUE within a satellite data driven terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally favorable correspondence with tower GPP estimates (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a water supply proxy indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent soil moisture related water supply controls influencing photosynthesis, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations. Lastly, these observations may provide an effective tool for characterizing sub-grid spatial heterogeneity in soil moisture related controls that inform coarser scale observations and estimates determined from other satellite observations and earth system models.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Analysis of hydrogen as a Transportation Fuel FY17 Report

This report summarizes the results of literature reviews, surveys and analyses performed to evaluate the potential of hydrogen-fueled vehicles to be an economically viable transportation alternative. Five existing and important drivers of expanding hydrogen-fueled transportation adoption are multi-billion dollar sales reservations of Nikola Class 8 trucks, CALSTART viability analysis of hybrid-hydrogen drayage trucks in the shipyard cargo application, analysis showing economic advantages of Fuel Cell Electric Vehicles (FCEV)s over Battery Electric Vehicles (BEV)s beginning at 150-mile ranges, the announcement of a commercial 5kg electrolyzer, and commercial plans or vehicle availability by nine vehicle manufacturers of FCEV passenger vehicles. But hydrogen infrastructure availability needed to support broad adoption of hydrogen-fueled vehicles is limited to less than 50 publicly-available refueling stations, primarily in California. The demand side (consumer) economics associated with FCEV adoption showed strong economic sensitivity to the original vehicle’s fuel economy (mpg), distance traveled, and hydrogen (H2) generation costs. Seven use cases were used to evaluate the broad range of potential FCEV purchasers, including autonomous vehicle applications. Each consumer use case analysis resulted in a different hydrogen fuel cost that would be equivalent to the current fuel cost being paid by the consumer. The H2 generation costs (supply side) were sensitive to the volume of H2 supplied and H2 production costs needed to repay H2 supply facility capital costs and produce competitively-priced energy. H2FAST was used to more accurately incorporate capital, maintenance and production costs into a viable H2 supply cost to the consumer. When the H2 generation and consumer economics were combined, several applications with positive economics became clear. The availability of low-cost hydrogen pipeline connections, and therefore low-cost hydrogen, greatly benefits the California drayage truck application with hybrid-hydrogen retrofits being repaid within seven years. Class 8 trucks could also take advantage of these low-cost, but regional hydrogen supplies. In addition, the IVYS electrolyzer-based hydrogen generation product showed the potential to deliver hydrogen economically in an urban or freeway off-ramp setting to a limited number of passenger vehicles in areas with low-cost electricity. These positive, manually developed results show the need to develop more advanced tools to provide an expanded evaluation of the economics of hydrogen-based fuel applications. The use cases evaluated showed significant potential for hydrogen-fueled vehicles to have a sustainable impact as a transportation fuel. The positive impact is not limited to transportation fuels, but also grid resilience and flexibility through the use of controllable and variable electrolyzer output to rapidly adjust to changing grid conditions and enable greater integration of solar and wind generated power. This capability would directly enable alternative fuel vehicles to impact energy consumption, GHG emissions, and the economy at the regional and national levels.

08 HYDROGEN↗
DOE OSTI2022

Mapping thermal energy storage technologies with advanced nuclear reactors

Advanced nuclear power plants (NPPs) will potentially need to operate in environments where power generation flexibility is more highly valued than the stability or baseload generation capability for conventional demand curves. Thermal energy storage (TES) systems would enable NPPs to respond nimbly to market variability and could also position advanced NPPs to participate differently in restructured markets, thus further enhancing their economic competitiveness. TES systems could also benefit the electric grid by eliminating the need for peaking plants, as well as by improving the economic performance of baseload NPPs. While TES technologies afford a unique opportunity to address many of these challenges, the applicability of these systems is also complicated by the fact that various advanced NPPs are designed differently, each with its own temperature range, size, operating fluids, and operating conditions. Hence, TES systems face significant barriers to investment, as more information on their compatibility and performance metrics is needed to quantify the advantages provided by each, as well as the challenges these technologies might face if coupled with a particular type of advanced NPP. This study explores the possibility of integrating a wide variety of TES technologies with various categories of advanced NPPs, based on their operating characteristics. To help decision makers, users and developers decide which TES technology is best suited to a particular category of advanced NPPs, this research present a Phenomena Identification and Ranking Table (PIRT) analysis of 10 TES systems that could potentially be coupled with advanced NPPs, which themselves are divided into nine categories based on their operating conditions. Then, each advanced NPP category is evaluated for compatibility with the 10 TES systems by assembling and discussing a database of information concerning 10 engineering questions, defined herein in as figures of merit (FOMs), such as: technology readiness level (TRL), temperature compatibility, energy density, size, cycle frequency, ramp time, realignment frequency, geographic needs, environmental impact, and interventions. By assembling a database of information concerning the TES technologies' compatibility with various advanced NPP systems, this study can help developers acquaint themselves with a particular TES technology before choosing to build a new integrated installation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Impact of Hydrological Data on Power System Operational Studies: Preprint

Hydropower is expected to play an important role in maintaining grid reliability and flexibility as the share of of variable renewable energy increases. While the current hydropower operational models have been studied and used widely, they haven't been updated for decades to meet new performance standards. For example, current steady state and dynamic models often neglect hydrological conditions, which may lead to unrealistic expectations when relying on hydropower for energy and ancillary services. To study this impact, a multi-timescale hydrological model was created by leveraging the National Renewable Energy Laboratory-developed Multi-timescale Integrated Dynamics and Scheduling (MIDAS) tool. Using MIDAS, we compare the impact of considering hydrological conditions in a day-ahead unit commitment (DAUC) schedule on the reduced 240-bus Western Interconnect (WI) test system under winter and summer case studies. We show that neglecting current hydrological conditions of hydropower plants in power system models can lead to an overestimation of hydropower capabilities, which could lead to power balancing issues. For example, power system DAUC simulation results of our reduced test system show that in the case where hydrological conditions are not considered in the model, an approximate 31% overestimation of hydropower capabilities occurs in the summer case and approximately 60% occurs in the winter case compared to what is available. Additionally, results show an underestimation of WI day-ahead power system generation costs by approximately $54M - $80M in the weekly summer scenario and $116M - $126M in the weekly winter scenario. This analysis helps to underscore the importance of considering hydrological data in power system operational studies.

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

Small-Signal Stability Impacts of Load and Network Dynamics on Grid-Forming Inverters

This paper presents several stability analyses for grid-forming inverters and synchronous generators considering the dynamics of transmission lines and different load models. Load models are usually of secondary importance compared to generation source models, but as the results show, they play a crucial role in stability studies with the introduction of inverter-based resources. Given inverter control time scales, the implications of considering or neglecting electromagnetic transients of the network are very relevant in the stability assessments. In this paper, we perform eigenvalue analyses for inverter-based resources and synchronous machines connected to a load and explore the effects of multiples models under different network representations. We explore maximum loadability of inverter-based resources and synchronous machines, while analyzing the effects of load and network dynamic models on small-signal stability. The results show that the network representation plays a fundamental role in the stability of the system of different load models. The resulting stability regions are significantly different depending on the source and load model considered.

grid forming inverters↗
DOE OSTI2022

EVSE Cybersecurity and Resilience

Consequence-driven Cybersecurity Analysis for Extreme Fast Charging Electric Vehicle Infrastructure Electric vehicle (EV) development and associated charging infrastructure are expected to advance rapidly. Thirty percent of all global vehicle sales may be EVs and hybrid EVs by 2025, and they will rely on increasingly sophisticated strategies for grid integration. Next-generation EV charging infrastructure is expected to include interconnected renewable resources, such as photovoltaic (PV) arrays and battery storage systems, along with grid-edge devices. Although distributed energy resources (DERs) are useful in several ways, such as peak shaving at high demand times and backup supply for added resilience, the integration of vehicle charging and DERs could create more avenues for cyberattack. Physical and/or remote access to EV charging station components, including charge ports, power electronics, controllers, and local generation (e.g., PV and energy storage) could be paths to cause power fluctuations, leading to altered operations at the charging station, escalated privileges to administrative systems, exfiltration of financial information (including personally identifiable information), and reduced grid stability. One compromised EV supply equipment component can open the door to a variety of exploitable vulnerabilities. Cloud computing and mobile application control have the potential to expand the threat surface to non-repudiation and firmware integrity challenges. Vendor clouds have access to hundreds of chargers, and if compromised, can scale the attack surface exponentially. The high power and voltage levels of xFC infrastructure (e.g., 400 kW at 1000- V DC) increase the hazards and ability to impact the grid and vehicles more than lower-power charging systems. Legacy communications systems and protocols could also put EV infrastructure at risk of cyberattacks requiring a robust patch management process. Communications networks link EVs and chargers to several stakeholders - including charging station operators, grid operators, vendors/manufacturers, and aggregators - who have both physical and network access to share information for control, monitoring, and analytics. Information in these networks that is vulnerable to compromise includes the state of charge, charging duration, payment information, electricity price, and load control. Analyzing and prioritizing these interconnections risks could help address cybersecurity related to data leakage and manipulation.

charging↗