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At least 667 records · Page 37

The Use of GIS and Remotely Sensed Data in Environmental Public Health Tracking (EPHT): The HELIX-Atlanta Experience

As part of the National Environmental Public Health Tracking Network (EPHTN), the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC) is leading a project in collaboration with the NASA Marshall Space Flight Center (NASA/MSFC) called Health and Environment Linked for Information Exchange (HELIX-Atlanta). HELIX-Atlanta's goal is to examine the feasibility of building an integrated electronic health and environmental data network in five counties of metropolitan Atlanta, GA. Under HELIX-Atlanta, pilot projects are being conducted to develop methods to characterize exposure; link health and environmental data; analyze the relationship between health and environmental factors; and communicate findings. There is evidence in the research literature that asthmatic persons are at increased risk of developing asthma exacerbations with exposure to environmental factors, including PM(sub 2.5). Thus, HELIX-Atlanta is focusing on methods for characterizing population exposure to PM(sub 2.5) for the Atlanta metropolitan area that could be used in ongoing surveillance. NASA/MSFC is working with CDC to combine NASA earth science satellite observations related to air quality and environmental monitoring data to model surface estimates of fine particulate matter (PM(sub 2.5)) concentrations in a Geographic Information System (GIS) that can be linked with clinic visits for asthma on the aggregated grid level as well as the individual level at the geographic locations of the patients' residences.

Al-Hamdan, Mohammad Z.↗

Building the Sun4Cast System: Improvements in Solar Power Forecasting

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers. The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.

54 ENVIRONMENTAL SCIENCES↗

Cybersecurity Certification Recommendations for Interconnected Grid Edge Devices and Inverter Based Resources

Escalating deployment of PV and grid-edge devices on the distribution grid has increased the sustainability and efficiency of the electric grid. However, the increasing number of distributed energy resources (DERs) deployed creates a heightened cyber-physical interdependency on the distribution grid and thus creates more vectors for cyber-attacks to exploit through information and communication technology (ICT) systems and networks. For example, control signal packets can be modified, intercepted, or corrupted due to vulnerabilities in communication protocols used by microgrid controllers and grid edge devices for power control. Therefore, to mitigate and prevent cyber-attacks on grid edge devices and the inverter-based resources connected to the distribution grid, the U.S. Department of Solar Energy Technologies Office (SETO) awarded funding to the National Renewable Energy Laboratory and Sandia National Laboratory (SNL) to research, develop, and harmonize cybersecurity standards for Photovoltaic (PV) systems and for other kinds of DERs. To help develop a standard for DER cybersecurity, NREL established certification recommendations and test cases, in consensus with the solar industry and UL, for ensuring intrinsic design security for DERs. These recommendations were developed to bolster the cybersecure functionalities such as TLS, MAC, CRL, session resumption/renegotiation, and password, system, and service security management within the DER devices. The proposed test cases verify authentication, authorization, confidentiality, and data integrity for data and communications of DERs that use Transmission Control Protocol/Internet Protocol (TCP/IP). They were also developed to protect DER communications from eavesdropping, replay, man-in-the-middle, denial of service (DoS), spoofing through security certificates, least-privilege violation, and brute-force credentials. This report, which has been validated and reviewed by UL, expands upon those test cases to provide DER cybersecurity certification recommendations which increase DER resiliency and help to mitigate cyber-attacks. UL's collaboration with NREL and approval of this document will accelerate the adoption of a UL standard for DER cybersecurity.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Planetary Boundary Layer Height from AIRS and MERRA-2 Products at NASA GES DISC, and Insights from Data Intercomparison

The Atmospheric Infrared Sounder (AIRS) is the hyperspectral infrared sounder onboard NASA's Aqua satellite, launched in 2002. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the Aqua AIRS mission and the subsequent Suomi-National Polar-orbiting Partnership Cross-track Infrared Sounder (CrIS) mission. The Planetary Boundary Layer (PBL) Height is a new variable added in the AIRS Version 6 support product. It is derived based on gradients of the retrieved atmospheric thermodynamic profile, and gives the pressure at the top of PBL over the ocean. The GES DISC also provides services for the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product generated by the Goddard Earth Observing System Model, Version 5 (GEOS-5) data assimilation system. The monthly PBL Height variable has been available in the Giovanni system, which is a Web-based application developed by the GES DISC providing a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. In this work, we will present the monthly PBL Height data from AIRS and MERRA-2 and the services to support data intercomparison, such as access, plotting, subsetting, re-gridding, and generation of a multi-year monthly mean. We will also show intercomparison results, and evaluate whether (over the ocean) AIRS can observe PBL features similar to the reanalysis product at monthly and longer-term scales.

AIRS↗

Validation of the National Solar Radiation Database (NSRDB) (2005-2012): Preprint

Publicly accessible, high-quality, long-term, satellite-based solar resource data is foundational and critical to solar technologies to quantify system output predictions and deploy solar energy technologies in grid-tied systems. Solar radiation models have been in development for more than three decades. For many years, the National Renewable Energy Laboratory (NREL) developed and/or updated such models through the National Solar Radiation Data Base (NSRDB). There are two widely used approaches to derive solar resource data from models: (a) an empirical approach that relates ground-based observations to satellite measurements and (b) a physics-based approach that considers the radiation received at the satellite and creates retrievals to estimate clouds and surface radiation. Although empirical methods have been traditionally used for computing surface radiation, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Project (GSIP) is an operational physical model from the National Oceanic and Atmospheric Administration (NOAA) that computes global horizontal irradiance (GHI) using the visible and infrared channel measurements from the Geostationary Operational Environmental Satellites (GOES) system. GSIP uses a two-stage scheme that first retrieves cloud properties and then uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. NREL, the University of Wisconsin, and NOAA have recently collaborated to adapt GSIP to create a high temporal and spatial resolution data set. The product initially generates the cloud properties using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms [3], whereas the GHI is calculated using SASRAB. Then NREL implements accurate and high-resolution input parameters such as aerosol optical depth (AOD) and precipitable water vapor (PWV) to compute direct normal irradiance (DNI) using the DISC model. The AOD and PWV, temperature, and pressure data are also combined with the MMAC model to simulate solar radiation under clear-sky conditions. The current NSRDB update is based on a 4-km x 4-km resolution at a 30-minute time interval, which has a higher temporal and spatial resolution. This paper demonstrates the evaluation of the data set using ground-measured data and detailed evaluation statistics. The result of the comparison shows a good correlation to the NSRDB data set. Further, an outline of the new version of the NSRDB and future plans for enhancement and improvement are provided.

14 SOLAR ENERGY↗

Cooperation in Transmission Expansion Planning: Enhancing Grid Reliability and Efficiency Under a Changing Climate

Electricity grids are challenged to maintain reliability during more intense and frequent extreme weather events due to climate change. This challenge is exacerbated by multi-sector electrification and power sector decarbonization through increased reliance on variable renewable energy, which necessitates the expansion of transmission infrastructure. However, transmission expansion planning is often complicated by intertwined planning authorities and jurisdictions, and allocation of large capital investment needs. These factors cause authorities to manage transmission investments individually (i.e., only/mostly intraregional planning), which can lead to suboptimal transmission networks. This study investigates the potential benefits of cooperative transmission expansion planning (i.e., both intraregional and interregional planning that optimizes transmission investments across the entire physical system). Using sectoral and economic optimization, and machine learning models, it analyzes the impact of different levels of cooperation among transmission planning regions within U.S. Western Interconnection in 2019 and 2059 via an iterative investment process. Furthermore, it examines the effects of future climate change on transmission cooperation by simulating historical heat waves from 2019 under conditions of 2059. The results indicate that cooperative transmission planning leads to lower wholesale electricity prices, decreased energy outages, and reduced greenhouse gas emissions. However, the advantages of collaboration diminish during widespread heat waves, despite remaining beneficial especially for regions like California Independent System Operator with substantial solar installations. The study underscores the importance of transmission cooperation in reducing costs and enhancing reliability, emphasizing the need for strategic investments in storage to address challenges posed by future extreme weather events with varying spatial scales.

Capacity Expansion Model↗

Design of Experiments Involving Molybdenum in SNL SPRF/CX Facility

This report is part of the collaboration with the Nuclear Criticality Safety Program and constitutes the “CED-2 report” of the experiments proposed in the SPRF/CX facility of SANDIA National Laboratories to contribute to the validation of Molybdenum in thermal energy spectrum. It supplements the study carried out in the CED-1 report by providing a more precise design of the proposed experiments and presents a complete evaluation of the experimental uncertainties. In the CED-1 report, corresponding to the preliminary design of the experiments, IRSN identified several promising configurations that could be implemented in the SPRF/CX facility of SNL. They use metallic molybdenum either in the form of foils between the UO 2 pellets inside BUCCX rods, or in the form of sleeves surrounding 7uPCX rods. In this CED-2 report, a new design using molybdenum sleeves surrounding BUCCX rods is also analyzed and the experimental uncertainties of all the proposed configurations are estimated. Given the constraints to carry out the experiments and the costs associated with the manufacturing of the foils, the experiments using molybdenum foils are discarded. Similarly, the design using molybdenum sleeves around BUCCX rods leads to significant manufacturing costs which could certainly be partially offset by use of existing grids but which would lead to slightly lower values of the integral sensitivities to the cross sections of molybdenum. Consequently, the design using molybdenum sleeves around 7uPCX rods is favored insofar as it presents higher $k_{eff}$ sensitivities to the molybdenum cross sections and that there is still possibility to reduce the number of sleeves to reduce the cost of experiments. Regarding feedback on nuclear data in support of criticality safety assessment, one of the advantages of the work described here is that the proposed experiments are not correlated with the MIRTE and FP experiments using molybdenum. In addition, they lead to higher sensitivity values in the thermal energy range than the existing experiments and partly “cover” the first resonance of the 95 Mo, which is a real advantage for improving knowledge on molybdenum cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experimenting with the GMAO 4D Data Assimilation

The Global Modeling and Assimilation Office (GMAO) has been working to promote its prototype four-dimensional variational (4DVAR) system to a version that can be exercised at operationally desirable configurations. Beyond a general circulation model (GeM) and an analysis system, traditional 4DV AR requires availability of tangent linear (TL) and adjoint (AD) models of the corresponding GeM. The GMAO prototype 4DVAR uses the finite-volume-based GEOS GeM and the Grid-point Statistical Interpolation (GSI) system for the first two, and TL and AD models derived ITom an early version of the finite-volume hydrodynamics that is scientifically equivalent to the present GEOS nonlinear GeM but computationally rather outdated. Specifically, the TL and AD models hydrodynamics uses a simple (I-dimensional) latitudinal MPI domain decomposition, which has consequent low scalability and prevents the prototype 4DV AR ITom being used in realistic applications. In the near future, GMAO will be upgrading its operational GEOS GCM (and assimilation system) to use a cubed-sphere-based hydrodynamics. This versions of the dynamics scales to thousands of processes and has led to a decision to re-derive the TL and AD models for this more modern dynamics, thus taking advantage of a two-dimensional MPI decomposition and improved scalability properties. With the aid of the Transformation of Algorithms in FORTRAN (l'AF) automatic adjoint generation tool and some hand-coding, a version of the cubed-sphere-based TL and AD models, with a simplified vertical diffusion scheme, is now available, enabling multiple configurations of standard implementations of 4DV AR in GEOS. Concurrent to this development, collaboration with the National Centers for Environmental Prediction (NCEP) and the Earth System Research Laboratory (ESRL) has allowed GMAO to implement a hybrid-ensemble capability within the GEOS data assimilation system. Both 3Dand 4D-ensemble capabilities are presently available thus allowing GMAO to now evaluate the performance and benefit of various ensemble and variational assimilation strategies. This presentation will cover the most recent developments taking place at GMAO and show results from various comparisons from traditional techniques to more recent ensemble-based ones.

Todling, R.↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of interinstitutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action— particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of inter-institutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action—particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

De-Risking Large-Scale PV Systems Through Data Analytics

Large-scale photovoltaic system performance analysis is being conducted within the US Department of Energy's-sponsored PV Fleet Performance Data Initiative. This collaboration with commercial PV system owners collects and evaluates PV field performance data, and provides reports on aggregated results. Drawing on over 2200 sites across the US and over 24,000 separate PV inverters we have collected in excess of 8.3 gigawatts (GW) of performance data, representing 6-7% of the entire US installed PV capacity. A mixture of utility-scale and large commercial systems are represented, averaging 4.1 megawatts (MW) in size and 5 years in age. Initial results show average system degradation rates at -0.75% / year, which is slightly higher than historically reported module-level values of -0.5%/year. We also found that the availability of systems averaged 97.7%, which is lower than the typical 99% uptime assumed by many project economic forecasts. Given these results, we compared monthly performance with expected production values, based on satellite weather data and a simple PVWatts performance model. We found that systems were performing within 10% of monthly expectation over 90% of the time, with a fleet average vs expected monthly value of 0.994. We also evaluated the impact of extreme weather events on system performance, and found a range of short-term and longer-term performance effects ranging from grid outage, system downtime, module damage and accelerated long-term degradation rate.

analysis↗

Transformer Health Monitoring Using Dissolved Gas Analysis

As integral components of any power plant, transformers supply the generated electricity to the grid. However, a transformer’s cellulose-based paper insulation and the mineral oil in which it is immersed break down over time under standard operating conditions—or more rapidly due to potential faults within the system. As the transformer’s mineral oil breaks down, gases are released that can be measured and monitored. This technical brief exhibits a collection of diagnostic and prognostic techniques that utilities can adopt in lieu of labor-intensive periodic preventive maintenance routines. Furthermore, prognostic models have been incorporated using the latest version of the Institute of Electrical and Electronics Engineers (IEEE) standard (IEEE, 2019) for dissolved gas analysis (DGA), thus expanding it to include estimation of the time to maintenance. Overall, four different methodologies are explained, each of which aids in determining a transformer’s state of health. These methodologies include the Chendong model, the IEEE thermal life consumption model (IEEE, 2012), a diagnostic model for DGA, and a prognostic model for DGA that uses an autoregressive integrated moving average (ARIMA) model. An additional improvement for estimating missing system parameters by using monitoring data (i.e., a tool for parameter estimation utilizing Powell’s method) is presented, enabling the IEEE thermal life consumption model to benefit not only the collaborating power plant, but also the power industry at large.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Direct numerical simulations and modeling of a spatially-evolving turbulent wake

Understanding of turbulent free shear flows (wakes, jets, and mixing layers) is important, not only for scientific interest, but also because of their appearance in numerous practical applications. Turbulent wakes, in particular, have recently received increased attention by researchers at NASA Langley. The turbulent wake generated by a two-dimensional airfoil has been selected as the test-case for detailed high-resolution particle image velocimetry (PIV) experiments. This same wake has also been chosen to enhance NASA's turbulence modeling efforts. Over the past year, the author has completed several wake computations, while visiting NASA through the 1993 and 1994 ASEE summer programs, and also while on sabbatical leave during the 1993-94 academic year. These calculations have included two-equation (K-omega and K-epsilon) models, algebraic stress models (ASM), full Reynolds stress closure models, and direct numerical simulations (DNS). Recently, there has been mutually beneficial collaboration of the experimental and computational efforts. In fact, these projects have been chosen for joint presentation at the NASA Turbulence Peer Review, scheduled for September 1994. DNS calculations are presently underway for a turbulent wake at Re(sub theta) = 1000 and at a Mach number of 0.20. (Theta is the momentum thickness, which remains constant in the wake of a two dimensional body.) These calculations utilize a compressible DNS code written by M. M. Rai of NASA Ames, and modified for the wake by J. Cimbala. The code employs fifth-order accurate upwind-biased finite differencing for the convective terms, fourth-order accurate central differencing for the viscous terms, and an iterative-implicit time-integration scheme. The computational domain for these calculations starts at x/theta = 10, and extends to x/theta = 610. Fully developed turbulent wake profiles, obtained from experimental data from several wake generators, are supplied at the computational inlet, along with appropriate noise. After some adjustment period, the flow downstream of the inlet develops into a fully three-dimensional turbulent wake. Of particular interest in the present study is the far wake spreading rate and the self-similar mean and turbulence profiles. At the time of this writing, grid resolution studies are underway, and a code is being written to calculate turbulence statistics from these wake calculations; the statistics will be compared to those from the ongoing PIV wake measurements, those of previous experiments, and those predicted by the various turbulence models. These calculations will lead to significant long-term benefits for the turbulence modeling effort. In particular, quantities such as the pressure-strain correlation and the dissipation rate tensor can be easily calculated from the DNS results, whereas these quantities are nearly impossible to measure experimentally. Improvements to existing turbulence models (and development of new models) require knowledge about flow quantities such as these. Present turbulence models do a very good job at prediction of the shape of the mean velocity and Reynolds stress profiles in a turbulent wake, but significantly underpredict the magnitude of the stresses and the spreading rate of the wake. Thus, the turbulent wake is an ideal flow for turbulence modeling research. By careful comparison and analysis of each term in the modeled Reynolds stress equations, the DNS data can show where deficiencies in the models exist; improvements to the models can then be attempted.

Cimbala, John M.↗

Preparing Distribution Utilities for the Future - Unlocking Demand-Side Management Potential: A Novel Analytical Framework

The balance of supply and demand in the power systems has traditionally been served solely through generation and network capacity planning and operations. However, with increased requirements for flexibility due to the uptake in variable renewable generation sources such as wind and solar there is a need to increased demand-side flexibility. In addition, there are increased communications and flexibility capabilities emerging on the demand-side from the adoption of advanced metering infrastructures and smart meter deployment and intelligent loads such as smart thermostats and schedulable white goods (e.g. dishwashers and washing machines). Unlocking demand-side flexibility can bring system benefits from peak load reduction bringing about generation capacity and network upgrade deferral, to reducing demand and more efficient utilization of generation and network capacity. Unlocking demand-side flexibility is an evolving process for utilities and solutions must be tailored to each specific customer group. Demand-side management (DSM) is a broad set of tools that can include demand response (both dispatchable and non-dispatchable), energy efficiency and distributed energy resources and demand-side technologies. The National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL) and Deloitte, examined the potential of DSM in BRPL’s service territory, developing detailed information on customer classes and willingness to participate in DSM. The study developed modeling frameworks for load analysis and the analysis tools to assess the potential of time-of-use tariffs in motivating customers to reduce their peak period energy consumption. The study shows that BRPL customers, specifically their domestic customers, are willing to participate in DSM programs and that time-of-use pricing can help BRPL reduce their peak demand and help unlock demand-side flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Additional EIPC Study Analysis: Interim Report on High Priority Topics

Between 2010 and 2012 the Eastern Interconnection Planning Collaborative (EIPC) conducted a major long-term resource and transmission study of the Eastern Interconnection (EI). With guidance from a Stakeholder Steering Committee (SSC) that included representatives from the Eastern Interconnection States Planning Council (EISPC) among others, the project was conducted in two phases. Phase 1 involved a long-term capacity expansion analysis that involved creation of eight major futures plus 72 sensitivities. Three scenarios were selected for more extensive transmission- focused evaluation in Phase 2. Five power flow analyses, nine production cost model runs (including six sensitivities), and three capital cost estimations were developed during this second phase. The results from Phase 1 and 2 provided a wealth of data that could be examined further to address energy-related questions. A list of 13 topics was developed for further analysis; this paper discusses the first five.

Electricity Grid↗

The Diurnal Cycle of Precipitation and Organized Convection in a Set of Global Mesoscale Simulations with the NASA GEOS AGCM

The NASA Global Modeling and Assimilation Office (GMAO) has conducted a series of 40-day nonhydrostatic global simulations with horizontal grid spacing ranging from 200 km to 3 km, as part of the DYAMOND model intercomparison project. The Goddard Earth Observing System (GEOS) model was run with the Grell-Freitas scale-aware convection scheme, which smoothly reduces parameterized deep convection with increasing resolution. Here we evaluate the diurnal cycle and other statistics of precipitation and organized convection as a function of resolution. For validation we use the 0.1 degree IMERG precipitation and 4 km Merged IR brightness temperature datasets, focusing on four regions: the continental United States, Amazonia, the equatorial Indian ocean, and the Maritime Continent. Early results indicate good phase agreement but excessive magnitude of the continental diurnal cycle of precipitation at coarser resolutions, with improved magnitude as resolution increases and the role of parameterization is reduced. Convective cloud clusters are identified with a brightness temperature threshold, and we find realistic numbers of the largest clusters (>10^4 km sq) at all resolutions, while the number of smaller clusters increases with resolution, approaching observations when dx=3 km. The observed diurnal cycle in the cluster size distribution is also reproduced, with realistic magnitude in the highest resolution runs. Precipitation characteristics across cluster sizes are also examined. The results show the potential for global mesoscale simulations as a community science resource, and we invite collaboration to explore these runs in greater detail.

Arnold, Nathan↗

Achieving a Net-Zero Future: The Role of Nuclear Energy

Governments and private industry around the world have established aggressive goals to achieve net-zero emissions for the power, industrial, and transportation sectors by 2050. These aggressive goals demand immediate action if we are to be successful, and they require us to think more holistically about our clean energy options. Programs within the U.S. Department of Energy (DOE) are addressing these holistic solutions. Traditionally, electricity generation and management are considered independently from meeting energy demands for industry and transportation. As we seek to eliminate emissions across all energy use sectors we need to reassess how energy demands are met. When we consider overall energy use, only one-third is in the form of electricity. Additional energy demands are in the form of heat or steam for industrial processes, in addition to direct fuel use for transportation. These sectors are much harder to abate, and electrification may not be the best option. Reducing environmental emissions at an affordable cost, while maintaining grid reliability and resilience, will require us to leverage all of the clean energy resources available. The DOE Office of Nuclear Energy (DOE-NE) program on Integrated Energy Systems (IES) is led by researchers at Idaho National Laboratory (INL), and work is conducted in partnership with an array of other DOE laboratories, industry, and academia. The primary focus of IES research is to assess the technical and economic potential of nuclear-driven IES to enhance the flexibility and utilization of nuclear reactors working alongside renewable generators to meet an array of energy demands—thereby maximizing the utilization of clean energy resources across all energy sectors. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. The DOE-NE program additionally partners with the Hydrogen and Fuel Cell Technologies Office under the DOE Office of Energy Efficiency and Renewable Energy to jointly fund the development of analysis tools, technologies, and nuclear-integrated hydrogen demonstration projects. This presentation will highlight the wide array of R&D being conducted across multiple DOE-funded programs to develop and deploy nuclear-based IES that will be key to achieving our net-zero goals. By working with key collaborators in the nuclear industry, analytical studies are now becoming a reality in demonstration projects.

08 HYDROGEN↗