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DOE OSTI2018

Illinois Distributed Generation Rebate - Preliminary Stakeholder Input and Calculation Considerations

What is the value of distributed generation to the distribution system and how do we assign that value to a rebate? This white paper is an update to Illinois Distributed Generation Rebate Calculation Considerations (PNNL-27569) and provides a preliminary look at potential distributed generation valuation methodologies and compensation options for Illinois by taking into consideration data needs and availability, stakeholder comments, and Illinois Public Utilities Act language. Pacific Northwest National Laboratory (PNNL) is supporting the Illinois Commerce Commission (ICC) with initial stakeholder engagement to advance the conversation around distributed generation valuation in Illinois. PNNL’s educational support will help set the stage for a productive formal process as the ICC will be called upon, in relatively short order, to start formal distributed generation valuation proceedings in response to Illinois Public Act 99-0906, also known as the Future Energy Jobs Act (FEJA), and codified in Illinois Public Utilities Act Section 16-107.6. This white paper does not represent the ICC’s formal investigation of distributed generation rebate valuation and is not intended to characterize or prejudge any decisions on behalf of the ICC.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Relative humidity threshold for oxygen generation by high-purity plutonium dioxides in 3013 containers

High-purity plutonium dioxide with adsorbed water in a sealed container can generate oxygen, but oxygen will not be generated in low water loading conditions. A threshold for oxygen generation has been observed in the hydrogen generation rate normalized by the specific power for high-purity plutonium dioxide. Normalized hydrogen generation rates above this threshold generate oxygen and below the threshold consume oxygen. The threshold rate is determined by the amount of water adsorbed onto the surface of the oxide. The relative humidity of the atmosphere that the oxide is in equilibrium with determines the amount of physisorbed water adsorbed on the surface. We calculate the relative humidity corresponding to the threshold rate as a function of mass and specific surface area of material stored in 3013 containers. Exceeding the calculated relative humidity may result in flammable gas mixtures of hydrogen and oxygen at some time during storage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Wholesale Electricity Markets and Resource Adequacy with High Clean Energy Generation Targets

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗
DOE OSTI2025

Testing a Hazmatpac Can with Locking Ring as a Secondary Shipping Container for Radium-224/Lead-212 Generators

A Hazmatpac can, paint can style shipping container with locking ring, was tested for use as an alternative shipping configuration for shipment of radium- 224 /lead- 212 generators. 224 Ra ( t 1/2 = 3.63 d) decays by alpha emission to radon-220 ( t 1/2 = 55.6 s). The potential for the radioactive radon gas to escape the generator column and the shipping container is of particular concern for the safe delivery of 224 Ra/ 212 Pb generators to customers. The purpose of this study was to evaluate whether the Hazmatpac can is a suitable shipping configuration, capable of containing the radon gas that may escape the generator column during transit. A 17.3 mCi 224 Ra/ 212 Pb generator was built and packaged into a Hazmatpac can. The can was smeared by a Radiological Control Technician (RCT) every day for seven days to analyze for radioactive contamination on the outside of the can. Over the course of the study, no radioactive contamination was found on the outside of the can. Therefore, the Hazmatpac can was approved as an alternative shipping configuration for shipment of 224 Ra/ 212 Pb generators.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping

Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyping activities (e.g., canopy cover estimation, plant localization, and flowering date identification). Among potential products, orthophotos play an important role in agricultural management. Traditional orthophoto generation strategies suffer from several artifacts (e.g., double mapping, excessive pixilation, and seamline distortions). The above problems are more pronounced when dealing with mid- to late-season imagery, which is often used for establishing flowering date (e.g., tassel and panicle detection for maize and sorghum crops, respectively). In response to these challenges, this paper introduces new strategies for generating orthophotos that are conducive to the straightforward detection of tassels and panicles. The orthophoto generation strategies are valid for both frame and push-broom imaging systems. The target function of these strategies is striking a balance between the improved visual appearance of tassels/panicles and their geolocation accuracy. The new strategies are based on generating a smooth digital surface model (DSM) that maintains the geolocation quality along the plant rows while reducing double mapping and pixilation artifacts. Moreover, seamline control strategies are applied to avoid having seamline distortions at locations where the tassels and panicles are expected. The quality of generated orthophotos is evaluated through visual inspection as well as quantitative assessment of the degree of similarity between the generated orthophotos and original images. Several experimental results from both UAV and ground platforms show that the proposed strategies do improve the visual quality of derived orthophotos while maintaining the geolocation accuracy at tassel/panicle locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters

The ability to generate physically plausible ensembles of variable sources is critical to the optimization of time domain survey cadences and the training of classification models on data sets with few to no labels. Traditional data augmentation techniques expand training sets by reenvisioning observed exemplars, seeking to simulate observations of specific training sources under different (exogenous) conditions. Unlike fully theory-driven models, these approaches do not typically allow principled interpolation nor extrapolation. Moreover, the principal drawback of theory-driven models lies in the prohibitive computational cost of simulating source observables from ab initio parameters. In this work, we propose a computationally tractable machine learning approach to generate realistic light curves of periodic variables capable of integrating physical parameters and variability classes as inputs. Our deep generative model, inspired by the transparent latent space generative adversarial networks, uses a variational autoencoder (VAE) architecture with temporal convolutional network layers, trained using the OGLE-III optical light curves and physical characteristics (e.g., effective temperature and absolute magnitude) from Gaia DR2. A test using the temperature–shape relationship of RR Lyrae demonstrates the efficacy of our generative “physics-enhanced latent space VAE” (PELS-VAE) model. Such deep generative models, serving as nonlinear nonparametric emulators, present a novel tool for astronomers to create synthetic time series over arbitrary cadences.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Viability Assessment of Wind and Solar Renewable Energy Generation in Support of Nationwide Vehicle Electrification

In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals, multiple computational frameworks are used to locate suitable land for renewable infrastructure development, and to quantify spatiotemporal variations in the potential energy generation and financial viability of development sites across the Unites States. First, the Oak Ridge Siting Analysis for power Generation Expansion tool (OR-SAGE) is used to assess the suitability of land for potential wind and solar energy development across the contiguous U.S. From there, resource data from the National Solar Radiation Database (NSRDB) and the Wind Integration National Dataset (WIND) are used in concert with the National Renewable Energy Laboratory (NREL) Renewable Energy Potential (ReV) model to calculate the variation in potential generation capacity for each resource. Additionally, the capital and operational expenditures are calculated for an example configuration of each renewable technology. These measures are then used to calculate the levelized cost of energy (LCOE) of potential sites. All of these results are then processed and analyzed to determine where in the U.S. solar and wind energy are most viable. This viability is based on available generation potential, consistency and stability of energy generation over time, and economic viability with respect to LCOE.

Miller, Brandon [ORNL] (ORCID:0009000300169201)↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Method of Carbon Obligation Allocation Between Generation Side and Demand Side in Power System

Under the background of low carbon electricity, the study of the carbon obligation allocation between different members in the power system has significant theoretical and practical value. As important members in the power system, both generators and loads should take the responsibility of carbon reduction and thus carbon obligation is supposed to be allocated between both sides. Consequently, the carbon obligation allocation between the generation side and the demand side is proposed, and the problem is modeled as a cooperative game based cost allocation problem. The Aumann-Shapley method is used to solve the problem. The mechanism of allocating carbon obligation in both generation side and load side is compared with the allocation only on the generation side and the load side. The results of case study show that both generators and loads take the responsibility of emission reduction of the power system in the proposed mechanism, which can stimulate the energy saving and consumption reduction behavior of generators and loads and reduce the carbon emission of the power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Apparatuses and methods for generating electric fields

Apparatuses and methods relating to generating an electric field are disclosed. An electric field generator may include a semiconductive material configured in a physical shape substantially different from a shape of an electric field to be generated thereby. The electric field is generated when a voltage drop exists across the semiconductive material. A method for generating an electric field may include applying a voltage to a shaped semiconductive material to generate a complex, substantially nonlinear electric field. The shape of the complex, substantially nonlinear electric field may be configured for directing charged particles to a desired location. Other apparatuses and methods are disclosed.

42 ENGINEERING↗
DOE OSTI2018

Efficient reversible uniform and non-uniform random number generation in UNU.RAN

Reversible random number generations are useful in large-scale fault-tolerant parallel computations and parallel discrete event simulations that are based on reversible computation. The Universal Non-Uniform Random Number Generator (UNU.RAN) is one of the popular random number generators used in the simulation community, but the generators are forward-only in nature. In this paper, we develop new reverse algorithm for the default uniform random number generator algorithm of UNU.RAN and also a few nonuniform random generators that use the Transform Density Reduction (TDR) method. We verify the correctness of reversals of our algorithms and also provide performance results to demonstrate reverse computing runtime adds little overheads relative to its forward counterpart.

Yoginath, Srikanth↗
DOE OSTI2019

Gas discharge tube true random number generator

A hardware random number generator comprises a gas discharge tube, an average voltage generator, and a comparator. The gas discharge tube includes first, second, and third terminals and may generate a variable voltage on the second terminal when a supply voltage is applied to the first and third terminals. The average voltage generator receives the variable voltage from the gas discharge tube and may generate an average voltage equal to a moving average value of the variable voltage over successive periods of time. The comparator receives the variable voltage and the average voltage and may generate a random stream of data bits, such that a value of each bit varies according to the relative magnitudes of the variable voltage and the average voltage.

42 ENGINEERING↗
DOE OSTI2019

Blended service schedule for a power generator

A power generation system includes a power generator operatively connected to a plurality of sensors and a processor. The processor is configured to observe usage-based or event-based data regarding one or more components and consumables of the power generator. A usage-based service schedule is observed for the one or more event-based components and consumables. Operation-based data is received from the plurality of sensors regarding the functioning of the power generation system and one or more operation-based components and consumables of the power generator. An operation-based service schedule is determined for the one or more operation-based components and consumables based on the operation-based data. A blended service schedule is generated, the blended service schedule including the usage-based service schedule and the operation-based service schedule. The blended service schedule is then provided to at least one of a local monitor or a remote monitor.

Keene, Kevin↗
DOE OSTI2016

Local, Regional, and Global Trade-Offs of Hydropower Relicensing Decisions An Analysis of Electric Generation, Revenue, Electricity Market, Greenhouse Gas Emissions, and Local Environmental Impacts

Large hydropower systems incur various impacts on society and the environment, but the manner in which these systems are operated can determine the severity of these impacts. The federal hydropower relicensing process – which occurs only once every 30-50 years – examines a number of potential impacts, but disregards others. This paper identifies some of the local, regional, and global trade-offs that should be examined more explicitly in relicensing proceedings. These include higher-resolution analyses of impacts on generation and revenue (including ancillary services) and the potential greenhouse gas impacts of different hydropower operating regimes. Any reduction of low-carbon generation may result in global environmental and social harms if it is replaced by fossil fuel generation. Although rarely quantified in the hydropower relicensing process, this is an important value in understanding the range of costs and benefits of different operating proposals. Using a case study of the Yuba River Development Project, this study finds that an environmentally protective operating regime reduces electric generation by 6.1% but increases ancillary services provision by 1.9% on average. The reduced hydropower generation is replaced by natural gas generation, resulting in an increase in CO2 emissions with a global social cost of about $1 million annually.

13 HYDRO ENERGY↗
DOE OSTI2020

Induced Markov chain for wind farm generation forecasting

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

17 WIND ENERGY↗
DOE OSTI2021

Differential neutron spectrum generator and related methods and systems

A neutron spectrum generator is disclosed herein including a neutron source, a scatterer positioned in a direct path between the neutron source and a neutron detector, and a material shell configured to have at least one non-uniform characteristic selected from the group consisting of a material, a thickness, a length, an angle, a layer, and combinations thereof to generate a specific spectrum at the neutron detector that is different than the spectrum of the neutron source. A related method includes measuring a first response generated by a first material shell of a neutron spectrum generator interacting with a neutron source, replacing the first material shell with a second material shell, measuring a second response generated by a second material shell of a neutron spectrum generator interacting with the neutron source, and determining a total fission response by determining a difference between the first response and the second response.

Scates, Wade↗
DOE OSTI2022

Generative attribute optimization

A generative attribute optimization (“GAO”) system facilitates understanding of effects of changes of attribute values of an object on a characteristic of the object and automatically identifying attribute values to achieve a desired result for the characteristic. The GAO system trains a generator (encoder and decoder) using an attribute generative adversarial network. The GAO model includes the trained generator and a separately trained predictor model. The GAO model inputs an input image and modified attribute values and employs the encoder and the decoder to generate a modified image that is the input image modified based on the modified attribute values. The GAO model then employs the predictor model to that inputs the modified image and generate a prediction of a characteristic of the modified image. The GAO system may employ an optimizer to modify the attribute values until an objective based on the desired result is achieved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Minimizing Transuranic Waste Generated in Hot Cells at Oak Ridge National Laboratory Through Use of a Non-Destructive CO{sub 2} Pellet Cleaning System - 19577

Wastes generated in shielded hot cells containing materials contaminated with transuranic (TRU) waste present unique problems in waste disposal at Department of Energy (DOE) sites. Oak Ridge National Laboratory (ORNL) routinely processes materials contaminated with TRU waste from the High Flux Isotope Reactor (HFIR) and from other sources (both on and off-site) in their hot cell facilities, generating wastes that require eventual disposal. The waste streams generated by these processes are often high activity and exhibit high dose rates, driving them into the remote-handled (RH) category at the Waste Isolation Pilot Plant (WIPP). Reduction of the TRU waste footprint is desirable from a disposal cost perspective due to constraints with RH waste processing and a lack of space availability at the WIPP. Historically TRU waste generated at ORNL has been processed by the TRU Waste Processing Center (TWPC), which belongs to the Department of Energy's Office of Environmental Management (DOE-EM). Now that Oak Ridge legacy TRU waste is reaching its final stage, DOE-EM has turned over the mission of processing newly-generated TRU waste streams to the DOE Office of Science at ORNL. To reduce the volume of potential TRU waste occupying valuable space in the ORNL Hot Cells, a non-destructive CO{sub 2} pellet cleaning system will be used to capture particulate contaminants removed from the surfaces of waste inside the ORNL Non-Reactor Nuclear Facilities (NNFD) Hot Cells at the Irradiated Fuels Examination Laboratories (IFEL). The particulate will be segregated by particle size and captured for disposal later. This action will separate some of the TRU isotopes (particulate) from the larger waste volume (debris waste items), resulting in both lower waste disposal costs and reduced TRU waste volumes. This will be accomplished through a specialized cyclone separator. Secondary wastes are usually generated through other methods of decontamination, such as water jets and abrasive agents. These secondary wastes are absent with the CO{sub 2} pelletized system, due to sublimation of the dry ice upon impact. This is an important consideration with IFEL, a facility whose primary mission is to perform a series of R and D testing on nuclear fuel rods. Liquid is not a feasible method of decontamination as the IFEL's drains in the Hot Cells were plugged years ago due to Resource Conservation and Recovery Act (RCRA) regulations. Constraints at IFEL, such as criticality safety concerns with use of hydrogenous materials, are also alleviated with the non-destructive CO{sub 2} pellet cleaning system. These are a couple of the considerations why this method of decontamination is preferred. Due to concerns with oxidizers at WIPP grouting will be performed on the contaminated particulate produced during the trapping by the cyclone separation phase. This method will comply with mitigating oxidizing properties in TRU waste, required by the recently published Basis of Knowledge (BoK) document as part of Acceptable Knowledge (AK) by WIPP. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗