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At least 487 records · Page 27

Aggregate residential demand flexibility behavior: A novel assessment framework

Residential demand flexibility (DF) could save the U.S. electric grid up to 10 GW of peak demand while supporting increased amounts of renewable generation. However, less than 40% of the estimated DF peak reduction capacity is currently realized, and less than 8% of American households are enrolled. These low participation rates are combined with high rates of "overriding" a DF event and eventual opt-outs among enrolled customers. There is still not a comprehensive understanding of the drivers of DF participation and occupant interaction with DF program signals. We, therefore, present a novel survey processing framework to assess occupant DF-relevant behavior from the American Time Use Survey (ATUS). Using the framework, we summarize both the extensive and intensive behavior of more than 200,000 ATUS respondents (2003-2018 data) and provide insights on the DF-relevant behavior of residential occupants, which is generally overlooked in the literature. Here we use the framework to identify the activity priorities of residential occupants in the United States during different DF-relevant periods (critical peak, peak, and off-peak). These preferred activities capture overlooked routine behaviors that could be barriers to DF participation, if ignored, and might explain the high levels of overrides often exhibited by participants of demand response.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Guide for Improved Resource Adequacy Assessments in Evolving Power Systems: Institutional and Technical Dimensions

This paper identifies and evaluates issues in traditional resource adequacy (RA) assessment practices, and how adjusting these practices may affect and depend on existing institutional arrangements for planning and procurement. The paper proposes a technical-institutional roadmap that would allow regulators in vertically-integrated jurisdictions and system planners and operators in restructured jurisdictions to revise RA practices across a range of components. First, we compile a critical review of current RA assessment practices based on (1) interviews with RA practitioners and (2) a review of recent technical literature. We find that (i) RA may need to expand beyond capacity adequacy to ensure energy adequacy – relevant for energy-limited resources such as storage – and potentially some form of ancillary service adequacy (e.g. enough ramping-up and ramping-down capability in the system); (ii) chronological hourly simulations for all hours in the year are the current best practice; (iii) metrics and models used do not reflect economic criteria in system operation and loss of load; and (iv) there is a need to improve representation of weather dependencies and weather data. Second, we review planning and RA reports for several private and public entities that plan generation and/or transmission infrastructure in the continental U.S. to look for existing practices involving resilience assessments. We find no systematic treatment of the costs of extreme weather and other hazards, the benefits of resilience, and resilience metrics in planning analyses and no systematic treatment of resilience metrics, methods, and outcomes for resource adequacy purposes. Third, we create a technical framework for probabilistic RA assessment and use it to study how key choices about how to model power system operations affect the values that are obtained for RA metrics. We find that (i) non-economic dispatch schemes that ignore economic objectives can lead to accurate RA assessments when coordinated with detailed operational strategies; (ii) multi-year data is critical to capture a wide variety of system conditions; (iii) not incorporating transmission limits into RA assessment could lead to substantial underestimation of traditional “expected value” RA metrics; and (iv) new RA metrics that capture event-specific shortfall characteristics should be used as supplements to traditional metrics. Finally, we examine RA assessments and use this information to propose a guide of evolving industry standards for resource adequacy assessments in resource planning and transmission planning. We report minimum, best, and frontier practices for temporal resolution of assessments, metrics and targets, weather data, load forecasting, characterization of variable renewable resources, characterization of transmission and market transactions, RA modeling and integration with planning processes, and capacity accreditation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fundamental Improvement of a Convergence Test for Iterative Strain-Gage Balance Load Predictions

A fundamental improvement of a convergence test for wind tunnel strain-gage balance load iterations was developed. The improvement became necessary because incorrect test results were obtained whenever the original test was applied to multi-component balances with large load capacity differences. The original test was first published in NASA TN D-6860. It uses an upper bound of the Lipschitz constant to assess convergence characteristics of balance load predictions whenever the Iterative Method is applied. The Lipschitz constant is a function of the partial derivatives of each balance load component with respect to all other load components. Unfortunately, the original definition of the convergence test overlooked the fact that the Lipschitz constant is a dimensionless quantity and that the partial derivative of one load component with respect to another load component is not always dimensionless. Therefore, an improvement of the original test was successfully developed that uses load capacities to make all inputs for the calculation of the Lipschitz constant dimensionless before use. Results from the calibration data analysis of a six-component force balance and a five-component semi-span balance are used to illustrate the application of the improved load iteration convergence test.

Strain-Gage Balance↗

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗

Assessments of data centers for provision of frequency regulation

There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. Here, when chillers are deactivated, both strategies have a similar regulation capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessing the levelized cost of energy in South Korea

This study evaluates the levelized cost of energy (LCOE) for various energy technologies in the Republic of Korea (Korea) from 2023 to 2050, highlighting cost trajectories and potential crossovers among competing technologies. The analysis projects that, based on our set of assumptions, utility-scale photovoltaic systems achieve lower LCOEs than nuclear by 2030, while fixed offshore wind is expected to become cost-competitive with coal-fired generation around the same time. Floating offshore wind is projected to reach cost parity with coal in the late 2030s. Co-firing with natural gas and green hydrogen is identified as the highest-cost generation option due to high natural gas and green fuel costs and declining capacity utilization. This study further examines the potential for hybrid systems that integrate renewable energy with energy storage to serve as flexible, cost-effective, zero-emission alternatives to green hydrogen-based generation. Spatial LCOE assessments indicate that near-shore offshore wind sites may achieve lower costs despite modest capacity factors, contingent on site-specific factors such as grid integration and social acceptance. The findings indicate that renewable energy technologies are expected to experience continued cost declines, with solar photovoltaic becoming the most competitive energy source in Korea by 2030–2035. Incorporating social costs accelerates this shift from conventional alternatives.

Green hydrogen↗

Association Between Vascular Density and Loss of Protective RAS During Early NPDR by Fractal Dimension

Purpose: Our hypothesis predicts that blood vessels within the retina increase in density during early-stage nonproliferative diabetic retinopathy (NPDR), based on previous results of a small retrospective study. For the current prospective study, the remodeling of arteries and veins during progression of early NPDR is assessed by a repertoire of parameters that includes the fractal dimension (D(sub f) ). In complex structures such as branching vascular trees, D(sub f) is a sensitive measure of space-filing capacity. The renin-angiotensin system (RAS) is implicated in DR pathogenesis and the function of circulating angiogenic cells (CACs), a critical bone marrow-derived population instrumental in vascular repair. Methods: Arterial and venous branching patterns were extracted from images of 6 normal controls and 3 early NPDR subjects (2 moderate, 1 mild) acquired by Heidelberg Spectralis (Registered Trademark) OCT following fluorescein angiography (FA). The vascular branching patterns were analyzed by NASAs VESsel GENeration Analysis (VESGEN) software, in which skeletonized representations were generated automatically to yield D(sub f) by the box-counting method. For binary 2D images, D(sub f) varies between limiting Euclidean dimensions of 1 and 2. Peripheral blood of diabetics and controls was collected for CD34+ CAC isolation. The gene expression of RAS in CACs was assessed by qPCR for Mas receptor to Ang-(1-7). The vasoreparative function of the CACs was measured by migration ability toward CXCL12 (SDF-1). Results: By D(sub f), venous and arterial densities were 1.370 +/- 0.006 and 1.329 +/- 0.016 for early NPDR, compared to 1.318 +/- 0.012 and 1.320 +/- 0.036 for control. The space filling capacity in early NPDR measured by D(sub f), a sensitive parameter, therefore demonstrated a pronounced increase for veins, but not for arteries. Mas receptor mRNA in CACs was increased in diabetics without DR but reduced with onset of NPDR, indicating possible loss of compensation of protective RAS during early DR. Migratory dysfunction of CD34+ cells was further associated with DR. Conclusions: As assessed by the fractal dimension in our preliminary study, the space-filling capacity of veins, but not arteries, was greater in early NPDR than in control. Larger patient populations will be examined as we complete our ongoing longitudinal study. Results further suggest the protective RAS axis within diabetic CACs is lost early in DR and is associated with increased vascular remodeling as evidenced by VESGEN analysis.

vascular↗

Cruise-Efficient Short Takeoff and Landing (CESTOL): Potential Impact on Air Traffic Operations

The National Aeronautics and Space Administration (NASA) is investigating technological and operational concepts for introducing Cruise-Efficient Short Takeoff and Landing (CESTOL) aircraft into a future US National Airspace System (NAS) civil aviation environment. CESTOL is an aircraft design concept for future use to increase capacity and reduce emissions. CESTOL provides very flexible takeoff, climb, descent and landing performance capabilities and a high-speed cruise capability. In support of NASA, this study is a preliminary examination of the potential operational impact of CESTOL on airport and airspace capacity and delay. The study examines operational impacts at a subject site, Newark Liberty Intemational Airport (KEWR), New Jersey. The study extends these KEWR results to estimate potential impacts on NAS-wide network traffic operations due to the introduction of CESTOL at selected major airports. These are the 34 domestic airports identified in the Federal Aviation Administration's Operational Evolution Plan (OEP). The analysis process uses two fast-time simulation tools to separately model local and NAS-wide air traffic operations using predicted flight schedules for a 24-hour study period in 2016. These tools are the Sen sis AvTerminal model and NASA's Airspace Concept Evaluation System (ACES). We use both to simulate conventional-aircraft-only and CESTOL-mixed-with-conventional-aircraft operations. Both tools apply 4-dimension trajectory modeling to simulate individual flight movement. The study applies AvTerminal to model traffic operations and procedures for en route and terminal arrival and departures to and from KEWR. These AvTerminal applications model existing arrival and departure routes and profiles and runway use configurations, with the assumption jet-powered, large-sized civil CESTOL aircraft use a short runway and standard turboprop arrival and departure procedures. With these rules, the conventional jet and CESTOL aircraft are procedurally separated from each other geographically and in altitude during tenninal airspace approach and departure operations, and each use a different arrival runway. AvTeminal implements its unique Focal-point Scheduling Process to sequence, space and delay aircraft to resolve spacing and overtake conflicts among flights in the airspace and airport system serving KEWR. This Process effectively models integrated arrival and departure operations. AvTerminal assesses acceptance rates and delay magnitude and causality at selected locations, including en route outer boundary fixes, tenninal airspace arrival and departure boundary fixes, terminal airspace arrival merge and departure diverge fixes, and runway landing and takeoff runways. The analysis compares the resulting capacity impacts, flight delays and delay sources between CESTOL and conventional KEWR operations. AvTerminal quantitative results showed that CESTOL has significant capability to increase airport arrival acceptance rates (35-40% at KEWR) by taking advantage of otherwise underused airspace and runways where available. The study extrapolates the AvTerminal-derived KEWR peak arrival and departure acceptance rates to estimate capacity parameter values for each of the OEP airports in the ACES modeling of traffic through the entire NAS network. The extrapolations of acceptance rates allow full, partial or no achievement of CESTOL capacity gains at an OEP airport as determined by assessments of the degree to which local procedures allow leveraging of CESTOL capabilities. These assessments consider each OEP airport's runway geometries, runway system configurations, airport and airspace operations, and potential CESTOL traffic loadings. The ACES modeling, simulates airport and airspace spacing constraints imposed by airport runway system, terminal and en route air traffic control and traffic flow management operations using airport acceptance rates representing conventional-aircraft-only and CESTOL-mixed operations. CEOL aircraft are assumed to have Mach 0.8, and alternatively Mach 0.7, cruise speeds to examine compatibility with conventional aircraft operations in common airspace. The ACES results provides estimates of CESTOL delay impact NAS-wide and at OEP airports due to changes in OEP airport acceptance rates and changes in en route airspace potential conflict rates. Preliminary results show meaningful nationwide delay reductions (20%) due to CESTOL operations at 34 major domestic airports.

Couluris, G. J.↗

Physical Processes for Driving Ionospheric Outflows in Global Simulations

We review and assess the importance of processes thought to drive ionospheric outflows, linking them as appropriate to the solar wind and interplanetary magnetic field, and to the spatial and temporal distribution of their magnetospheric internal responses. These begin with the diffuse effects of photoionization and thermal equilibrium of the ionospheric topside, enhancing Jeans' escape, with ambipolar diffusion and acceleration. Auroral outflows begin with dayside reconnexion and resultant field-aligned currents and driven convection. These produce plasmaspheric plumes, collisional heating and wave-particle interactions, centrifugal acceleration, and auroral acceleration by parallel electric fields, including enhanced ambipolar fields from electron heating by precipitating particles. Observations and simulations show that solar wind energy dissipation into the atmosphere is concentrated by the geomagnetic field into auroral regions with an amplification factor of 10-100, enhancing heavy species plasma and gas escape from gravity, and providing more current carrying capacity. Internal plasmas thus enable electromagnetic driving via coupling to the plasma, neutral gas and by extension, the entire body " We assess the Importance of each of these processes in terms of local escape flux production as well as global outflow, and suggest methods for their implementation within multispecies global simulation codes. We complete 'he survey with an assessment of outstanding obstacles to this objective.

Moore, Thomas Earle↗

Offshore Wind in the US Gulf of Mexico: Regional Economic Modeling and Site-Specific Analyses

The goal of this study is to assess offshore wind energy resources in the Gulf of Mexico (GOM) and to quantify its technical and economic potential in order to inform Federal and GOM state strategic energy planning over the next decade. The objectives are to: describe site-specific and regional benefits and challenges of deploying offshore wind in the GOM and discuss the current research to mitigate challenges; review and quantify the wind resource capacity and energy potential in the GOM region for each GOM state including state and federal waters, distance from shore, and water depth; perform geospatial regional economic assessments of levelized cost of energy (LCOE), levelized avoided cost of energy (LACE), and net value (Section 3.4.2); evaluate three representative hypothetical locations for site-specific analysis; perform a high-level assessment of local supporting infrastructure availability, including existing services (e.g., fabrication facilities, vessels, ports) and possible grid connection options; assess the regional economic impacts of a 600 megawatt (MW) offshore wind power plant installed at a representative site in the GOM.

17 WIND ENERGY↗

Availability of Critical Benchmark Experiments for the Pebble Tanker Transportation Model for Nuclear Criticality Safety Validation of TRISO Pebbles

This study addresses the need for comprehensive investigations into TRi-structural ISOtropic (TRISO) fuel pebble transportation validation. In this work, an exploratory model, the pebble tanker(PT), was developed with the aim of facilitating the validation of nuclear criticality safety calculations in the context of industrial-scale transportation of TRISO fuel. The PT model was designed to investigate the availability and applicability of critical benchmark experiments crucial for assessing the transportation of these pebbles. This work incorporated sensitivity/uncertainty (S/U) similarity studies to quantify the applicability of critical benchmark experiments and to address nuclear data uncertainties in the context of TRISO transportation. Two container models were investigated: one for the Hermes-type pebble and one for the Pebble Bed Modular Reactor (PBMR)–type pebble. The models were simplified, considering fuel, containment, and either water or air, to enable a focus on the underlying physics of applications involving TRISO fuel pebbles using the PT model. A crucial aspect under consideration was the capacity of the transport package to hold pebbles while ensuring subcriticality in the flooded state. An approach in the criticality validation process involves assessing the similarity between systems through an integral index parameter evaluation. This involves calculating a correlation coefficient (referred to as c k ) based on shared nuclear data–induced uncertainty between a benchmark experiment and the application of the PT model. To facilitate this analysis, the SCALE tools, particularly the CSAS6-Shift, TSUNAMI-3D-Shift, and TSUNAMI-IP sequences, were employed for comprehensive studies in neutronics and S/U analysis. Our findings showed that there are sufficient critical experimental benchmarks to perform this validation of the PT model in the most reactive state, i.e. when the tanker is flooded. This paper provides valuable insights into validating a transport package for Generation IV TRISO fuel pebbles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Enabling Floating Solar Photovoltaic (FPV) Deployment: FPV Technical Potential Assessment for Southeast Asia

Southeast Asia (SE Asia) is a region with growing energy demand and increasing development of floating solar photovoltaic (FPV) systems, which can help meet countries' renewable energy and energy security goals. This study uses a high-level geospatial assessment methodology to estimate the technical potential for monofacial and bifacial FPV on reservoirs and natural waterbodies in the ten countries within the Association of Southeast Asian Nations (ASEAN). Technical potential consists of the suitable waterbody area for FPV development (km2), the capacity of FPV that could be installed on this suitable area (MW), and the annual energy that could be generated from these installations (GWh/year). This first-of-its-kind FPV technical potential assessment for SE Asia can help policymakers and planners better understand the role that FPV could play in meeting regional energy demand and can ultimately guide investment decisions. Although this work focuses on SE Asia, the methodology may also be applicable for countries in other regions, with adaptations. The FPV technical potential results are also integrated into the Renewable Energy (RE) Data Explorer online tool (https://www.re-explorer.org/).

bifacial↗

Enabling Floating Solar Photovoltaic (FPV) Deployment: FPV Technical Potential Assessment for Southeast Asia

Southeast Asia (SE Asia) is a region with growing energy demand and increasing development of floating solar photovoltaic (FPV) systems, which can help meet countries' renewable energy and energy security goals. This study uses a high-level geospatial assessment methodology to estimate the technical potential for monofacial and bifacial FPV on reservoirs and natural waterbodies in the ten countries within the Association of Southeast Asian Nations (ASEAN). Technical potential consists of the suitable waterbody area for FPV development (km 2 ), the capacity of FPV that could be installed on this suitable area (MW), and the annual energy that could be generated from these installations (GWh/year). This first-of-its-kind FPV technical potential assessment for SE Asia can help policymakers and planners better understand the role that FPV could play in meeting regional energy demand and can ultimately guide investment decisions. Although this work focuses on SE Asia, the methodology may also be applicable for countries in other regions, with adaptations.

14 SOLAR ENERGY↗

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.

Hannah Alpert↗

Photovoltaic refrigeration application: Assessment of the near-term market

This foreign and domestic market assessment was performed as part of the Tests and Applications Project being conducted by NASA-LeRC as part of the Department of Energy's (DOE) National Photovoltaic Program. One of the objectives of that program was to stimulate the demand for photovoltaic power systems so that appropriate markets would be developed in concert with the increasing photovoltaic production capacity. The refrigeration application represented a possible market for photovoltaics; hence, a brief survey of potential applications was conducted. Both refrigerators and refrigeration systems were considered in the assessment although the primary emphasis is on refrigerators of 9 cu ft of less. Three user sectors were examined: (1) government, (2) commercial/institutional, and (3) general public.

Rosenblum, L.↗

Water Availability for Biorefineries in the Contiguous United States and the Implications for Bioenergy Production Distribution

Renewable biofuel production depends on many factors, including feedstock availability, refinery and shipment infrastructure, and in particular, water availability. This study assesses water requirement and availability for mainstream biorefinery technologies in the contiguous United States (CONUS). The assessment is conducted in newly defined spatial units, namely, biorefinery planning boundaries, considering feedstock availability, transportation cost, and refinery capacity requirement for cost-effectiveness. The results suggest that the total biorefinery water use in the CONUS by 2030 will be low compared to the total water availability. However, biorefinery water requirements can aggravate the water stress situation in many regions, including the Great Plains, California Central Valley, and the upper Columbia-Snake River basin in Washington. Bioenergy productions in these regions can be largely constrained by water. Here, it is projected that biofuel production will concentrate in Northern Plains, Lake States, and Corn Belt regions, which contribute 94.4% of the conventional, 86.1% of biodiesel, and 54.8% of cellulosic biofuel production mandated by the renewable fuel standard. If biorefineries are constrained to use less than 10% of the locally available water, up to 7% of planned cellulosic biofuel production will be affected. Findings from this study can aid the sustainable planning of national bioenergy production.

54 ENVIRONMENTAL SCIENCES↗

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2

The project Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2 is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Los Angeles Basin presents an opportunity for large-scale geologic CO2 storage. Due to its large population and historical and geologic setting as one of the most prolific oil and gas producing basins in the United States, the region is home to more than 12 major power plants and oil refineries that produce more than 5 million metric tons of fossil fuel-related CO2 emissions each year. GeoMechanics Technologies worked to characterize the Pliocene and Miocene sediments in the Wilmington Graben, offshore of Los Angeles, California, for high-volume CO2 storage. The Graben is located offshore of the Los Angeles and Long Beach Harbor area, making it accessible yet geologically isolated from the nearby Wilmington oilfield and onshore areas. These sediments span more than 5,000 feet of vertical interval with an estimated storage resource of more than 100 million metric tons of CO2. The project team analyzed and interpreted existing geologic data within the region, including detailed exploration well log data and 2-D and 3-D seismic data. New seismic lines were acquired to fill in current data gap areas and two new characterization wells were drilled and logged. This information was integrated with existing geologic interpretations for adjacent onshore areas to help characterize optimal areas for CO2 storage and seals to safely store CO2. Integrated 3-D geologic and geomechanical models for the Wilmington Graben were developed to simulate the fate and transport of injected CO2 in the subsurface and to assess risks. This project contributed to the understanding of injectivity, containment mechanisms, rate of dissolution and mineralization, and storage capacity of the Wilmington Graben and associated analogous basins. This effort also provided greater insight into the potential for offshore geologic formations to safely and permanently store CO2.

.las↗

Scale and Regionality of Nonelectric Markets for U.S. Nuclear Light Water Reactors

This study assesses existing and potential industries that could conceivably be directly coupled to existing nuclear reactors. The goal is to identify the scale, location, and accessibility of the candidate industrial-product markets, as well as process feedstocks that are available near the plants to establish new industries. For example, CO 2 as a feedstock can be combined with H 2 to produce formic acid (FA), transportation fuels, and lubricants. These new plants can be entirely supported with the heat and electricity provided by a nearby NPP. The potential demand for nonelectric industrial products was assessed by documenting current and possible growth of nonelectricity product markets considered. This assessment used DOE- and industry-supported tools, data, and projections to capture regional industrial market opportunities. Electricity-capacity markets that reward large and reliable generators, such as NPPs, were considered because the electricity market will likely continue to be an important revenue source to NPPs. The key is to balance the needs of energy customers so as to optimize revenue for the affiliated energy customers or partners. In most cases, flexible plant energy delivery and power generation for the grid will require either energy storage or a stock of intermediate products to sustain the industrial customers when the NPP dispatches electricity to the grid. A diverse mix of temperate regions with operating NPPs around the U.S.—representing a variety of operating markets, local generation mix, and seasonal climates—were chosen for this market study. Both current and future market opportunities for candidate industrial-product markets surrounding these NPPs were studied. Figure 2 illustrates the regions chosen for this study. The success of developing nonelectric industrial-product markets as alternative revenue-generating sources for LWRs depends, not only on demand from growing existing markets, such as petroleum refining and NH 3 production, but also on the development of new markets such as light-duty (LD) and heavy-duty (HD) hydrogen FCEVs, synfuels, chemical production, biofuels, metal refining, injection of hydrogen into NG pipelines for gas power-generating units, FA, polymers, and close-coupled industrial heat applications, all of which can significantly increase demand relative to current levels while decarbonizing energy sectors. This study also presents a sample analysis of the economics of hydrogen production in an area of Minnesota, considering the capital and operating costs of a hydrogen plant as well as the local market demand for hydrogen. It includes some assumptions on electricity-grid pricing, showing how hydrogen could be integrated with an NPP and be competitive with the incumbent hydrogen-production process, steam methane reforming (SMR). The objectives of this study include: Provide U.S. NPP operators a robust sampling of the market demand location, scale, and accessibility (including storage and transportation) of the wide variety of industrial-product choices that can be produced using nuclear thermal energy and electricity proximate to a subset of U.S. NPPs to inform the industry of the potential opportunity; show examples and trade-off analyses of how U.S. LWR operators can access these markets, including storage and transportation of industrial products to their intended markets; and present a general analysis example for one industrial product (hydrogen) in one region (Minnesota area), including production, storage, and transportation, to show how nuclear-hybrid integrated energy systems (IESs) could access local markets and improve the profitability of an NPP.

03 NATURAL GAS↗