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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Model-Predictive Hierarchical-Control Framework for Aggregating Residential DERs to Provide Grid Regulation Services: Preprint

This paper develops a hierarchical control fram-ework to aggregate and control behind-the-meter distributed energy resources (DERs), which will be ubiquitous in future distribution systems. Even though the increasing penetration of DERs will strain the power networks in terms of voltage regul-ation and coordination issues with existing transmission-level conventional generators, the distribution-level DERs can also be utilized to help provide flexibility to the power network while providing cost savings to the DER owners. Therefore, this paper develops a model-predictive control strategy to determine the available power flexibility, and to utilize the flexibility in an aggregated form to provide grid regulation services. Numerical simulations performed on the IEEE 37-bus test system demonstrate the efficacy of the proposed approach.

14 SOLAR ENERGY↗
DOE OSTI2020

National Grid: Using the LEAD Tool Data to Target Energy Affordability Services to Eligible Customers in New York

In the following use case, investor-owned utility company, National Grid, used the Low-Income Energy Affordability Data (LEAD) Tool to support the implementation of its Home Energy Affordability Team (HEAT), a weatherization program for income-eligible residential natural gas customers in its service territory in Long Island, New York. Using LEAD Tool data, National Grid was able to determine how many households may be eligible for the program to inform additional marketing efforts. This use case is an example of how utilities of all sizes and types in the United States can use the LEAD Tool in similar ways to gain insights and better address customer energy affordability needs.

Low-Income Energy Affordability Data Tool, LEAD To↗
DOE OSTI2021

UNREVIEWED DISPOSAL QUESTION EVALUATION: Disposal of the Perma-Fix Environmental Services Macroencapsulated Debris at the Area 5 Radioactive Waste Management Site, Nevada National Security Site, Nye County, Nevada

This Unreviewed Disposal Question Evaluation (UDQE) assesses whether the Perma-Fix Environmental Services (PERM) Macroencapsulated Debris, Radioactive Lead (Pb) Solids, Cadmium/Mercury/Silver (Cd/Hg/Ag) Containing Batteries from U.S. Department of Energy (DOE) Generators (PERM000000027, Revision 28 [PERM 2021]) is suitable for shallow land burial (SLB) at the Area 5 Radioactive Waste Management Site (RWMS) on the Nevada National Security Site (NNSS). Disposal of the PERM Macroencapsulated Debris, Radioactive Pb Solids, Cd/Hg/Ag Containing Batteries from DOE Generators meets all performance objectives of DOE Manual DOE M 435.1-1, Radioactive Waste Management Manual, Chapter IV, Section P (DOE 1999). The PERM Macroencapsulated Debris, Radioactive Pb Solids, Cd/Hg/Ag Containing Batteries from DOE Generators stream is recommended for acceptance without conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Defining a Use Case for the ADMS Test Bed: Fault Location, Isolation, and Service Restoration with Distributed Energy Resources: Preprint

Advanced distribution management systems (ADMS) integrate multiple enterprise-level functions into a single platform and offer advanced applications such as fault location, isolation, and service restoration (FLISR), to utilities to meet their operational needs for a modernized grid. These applications need to operate reliably even as distributed energy resource (DER) penetration increases on distribution systems. The ADMS test bed at the National Renewable Energy Laboratory offers utilities and vendors the opportunity to evaluate the performance of such advanced applications on distribution feeders of the future and to understand their potential benefits for a specific utility. This is done through defining use cases that address specific questions. This paper presents the definition of a use case on the performance of a commercially-available FLISR application on a feeder of an electric cooperative with DERs. Results from this use case will be disseminated to the electric utility and research community to improve understanding of the challenges and benefits that DERs present to ADMS applications and the operation of a modernized grid.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Probabilistic Day-Ahead Forecasting Using an Analog Ensemble Approach for Wind Farm Grid Services

Wind resource assessment and wind power forecasting are used in research and industry to anticipate future power output at scales ranging from individual wind turbines to entire wind farms. Probabilistic day-ahead wind forecasting is useful for anticipating how a wind farm could potentially participate in the day-ahead market by providing upper and lower bounds for expected power generation, thus informing grid operators of its uncertainty. Understanding this uncertainty is part of a larger project focused on building a platform that combines efforts in weather forecasting, aerodynamic and economic modeling to create maximum value of a wind plant to better provide services to the grid. This effort is also known as the Atmosphere to Electrons to Grid (A2E2G) project. One method for producing a probabilistic forecast is through the analog ensemble approach (Delle Monache et al., 2011). This method leverages historical forecasts and their corresponding observations as a training data set from which future forecasts can be made. For some future forecast, the most similar historical forecasts (analogs) are identified on a regular time basis such as once per a 3-hour window. The most similar analogs, based on a metric such as root mean square error (RMSE), are recorded and their corresponding verifying observations are used as an ensemble member for this future forecast. Prior work in this area demonstrates improvements over raw Numerical Weather Prediction (NWP) forecasts and shows skill similar to techniques such as logistic regression and machine learning (Delle Monache et al., 2013; Alessandrini et al., 2015). Here, we take the High-Resolution Rapid Refresh model (HRRR) day-ahead forecast (0-36 hours) to create a probabilistic day-ahead forecast using an analog ensemble approach. The HRRR has an hourly temporal resolution, with a spatial resolution of 3 km. The 12 UTC HRRR model run is downloaded every day for one year from August 2019 - July 2020, with the first 11 months serving as a bank of analogs from which the forecasting algorithm can create a probabilistic forecast. Once downloaded, the original HRRR forecast is temporally interpolated to 5-minutes, aligning with both the temporal resolution of the observations as well as the timescale relevant for day-ahead power forecasts. The forecast is validated at the M2 tower at the Flatirons Campus of the National Renewable Energy Laboratory (NREL) at a typical wind turbine height of 80 m. Variables such as wind speed, wind direction, and turbulence intensity are incorporated into the probabilistic forecast model and weighted according to their relative importance to the forecast. Based on metrics such as mean bias error (MBE), mean absolute error (MAE), and root mean square error, the analog ensemble forecast outperforms the raw HRRR forecast during the testing period of July 2020. Figure 1 illustrates an example day-ahead forecast compared against the verifying observations. The general variability and ramps are captured throughout the day, with potential to further improve the analog ensemble model through machine learning techniques.

numerical weather prediction↗
DOE OSTI2021

Large-Scale Adoption of Self Synchronized Universal Droop Controller-Based Inverters to Enable Ancillary Services for Different Modes of Distribution System Operations

This poster presents the results of using the self-synchronized universal droop controller to enable solar power to provide ancillary services so that the use of solar power can be increased. A 300-node system using the IEEE 123 bus test feeder are modeled on a real time power system simulator with the results presented.

Arce, Laura↗
DOE OSTI2022

Clean Energy Solutions Center Services

The Clean Energy Solutions Center is a web-based resource that helps governments design and adopt policies and programs that support the deployment of clean energy technologies. The Solutions Center's three main offerings are Ask an Expert policy assistance, training and peer-to- peer learning forums and a rich library of technical tools and publications. These services are provided at no cost to users.

ask an expert↗
DOE OSTI2023

Modeling of Stress Distribution in Molten Salt Thermal Energy Storage Tanks for In-Service Central Receiver Power Plants

Failures in molten nitrate salts thermal energy storage tanks (TES) have been occurring in several concentrating solar power (CSP) plants around the world after a few months or years of operation. These failures are mainly related to a combination of high stress, corrosion, large deformation, and thermal cycling. Most of these failures are a consequence of the infancy of this technology; technical standards for design, fabrication, implementation, and operation of molten salt tanks operating at temperatures up to 565 degrees Celsius do not exist and most of current in-service tanks have been designed using the recommendations from the American Petroleum Institute (API) 650 and the American Society of Mechanical Engineers ASME section II standards, which are applicable for TES tanks operating at lower temperatures. We have developed a 3-dimensional model of a representative molten salt hot tank design that uses typical CSP plant operation conditions and allows determining the temperature and stress distribution in the tank. The model also considers the initial floor residual stresses and distortion after its welding fabrication. We have identified critical thermal gradients in the tank floor and shell and locations in the tank where the stresses are high and could become susceptible points for failure.

concentrating solar power↗
DOE OSTI2020

ISOCS-based Extended In Situ Gamma Spectrometry Services Tool SuperISOCS for Waste Measurements - 20275

Canberra's In Situ Object Counting System (ISOCS) is an established tool used for gamma spectrometry. It allows physical representation of complex geometries and mathematical calculation of the calibration function while avoiding the need for radioisotope standards. ISOCS provides a large range of templates to generate the geometry for most nuclear waste components in nuclear facilities. Nonetheless, there are some complex geometries where the accuracy attainable is limited by the conventional ISOCS templates. An ISOCS-based extended in-situ Gamma Spectrometry service tool has been developed, based on the so-called SuperISOCS (SISOCS) software. This tool was developed to generate the most complex geometries. The principle of geometry construction is based on the composition of 8 different primitive geometries. The primitive object is able to be cut and to change a part of an object. An object is able to overlap to another one to form a more complex object. These functions refine the modelled geometry compared to the real objects and decrease the measurement systematic error because they allow the mathematical model to represent the real-life geometry more faithfully through reducing the approximations and simplifications that need to be made The algorithm of SISOCS is the same as that of standard ISOCS. A set of calculations was done in comparison with MCNP efficiency calculation and SISOCS results. 80 different models were compared between SISOCS and MCNP, with added 30 cases compared between ISOCS and SISOCS. The average differences were less than 2%, for all energy's efficiency calculations. In this paper we illustrate the benefits that this new tool can provide, in terms of improved accuracy for complex realistic geometries, through simulation of some example scenarios. Furthermore, we demonstrate, through SISOCS modelling of the real object data test, the comparison between SISOCS to ISOCS calculations for the same geometry. This paper describes the added functions that are easily employed using SISOCS. Our results show the potential application and benefit of this technique for real waste assay projects and the way to integrate the tool into the waste assay systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Graph Neural Network-based Tracking as a Service

Recent studies have shown promising results for track finding in dense environments using Graph Neural Network (GNN)-based algorithms. However, GNN-based track finding is computationally slow on CPUs, necessitating the use of coprocessors to accelerate the inference time. Additionally, the large input graph size demands a large device memory for efficient computation, a requirement not met by all computing facilities used for particle physics experiments, particularly those lacking advanced GPUs. Furthermore, deploying the GNN-based track-finding algorithm in a production environment requires the installation of all dependent software packages, exclusively utilized by this algorithm. These computing challenges must be addressed for the successful implementation of GNN-based track-finding algorithm into production settings. In response, we introduce a ``GNN-based tracking as a service'' approach, incorporating a custom backend within the NVIDIA Triton inference server to facilitate GNN-based tracking. This paper presents the performance of this approach using the Perlmutter supercomputer at NERSC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Circular Economy for Photovoltaics in Service of Energy Transition

The challenge of energy transition is immediate and immense; current projections target 75 TW of photovoltaics (PV) capacity by 2050. While any transition to renewable energy technology is preferable to the current fossil-based system, it is ideal to improve the sustainability of PV to minimize negative environmental and social impacts. Circular economy (CE) has been proposed as a method to improve the sustainability of PV, especially for emerging materials like perovskites. CE is a set of actions, principles, and systems which aim to design out waste and keep products and materials in use, to reduce environmental impacts and enable sustainable development. At the most basic level, CE is "reduce, reuse, recycle", the R-actions, in ranked order. CE of a PV technology can be metricized in a variety of ways, such as the Material Circularity Indicator (Smith and Jones, Ellen MacArthur Foundation, 2019) or recycling rates. Unfortunately, standard CE metrics have several shortcomings for measuring renewable energy technologies in the context of deployment for energy transition (Figge 2018, Saidani 2019): 1) Only measure mass flows; 2) De-prioritization of the use phase in favor of mass circularity when scoring; and 3) Tight focus on a single product scale The use phase and energy flows of PV are key to energy transition, and therefore need to be quantified. Additionally, correlating product-scale to system-scale is necessary for quantifying the environmental impacts of energy transition. Life Cycle Assessment (LCA) can address some of these concerns, but also focuses on a single product scale and has trouble capturing the dynamics of system-scale energy transition, such as the interaction of module lifetime with manufacturing demands for energy transition deployment schedules. Therefore, we developed an open-source Python-based system dynamics model to quantify the mass, energy and carbon impacts of CE R-actions for PV technologies in the energy transition; PV in the CE (PV ICE) (Ovaitt & Mirletz 2021). The tool captures supply chains from material extraction through end of life, incorporating 5 circular end of life pathways. PV ICE takes in any evolving bill of materials, module properties and deployment schedule to support researchers and decision makers with data-backed insights. In this work, we quantify and compare proposed CE sustainable PV module designs and lifecycle management strategies, spanning currently commercialized technologies, government and industry technology targets, and several low Technology Readiness Level (TRL) emerging PV technologies, including perovskites. Our analyses capture the projected evolutions of lifetime, efficiency and material circularity of these PV technologies, as well as their material supply chains. Our analyses emphasize the importance of examining a suite of metrics to identify priorities and tradeoffs, and inform design or lifecycle management decisions holistically. Previous analyses have demonstrated the central importance of PV module lifetime to support energy transition while minimizing impacts. High levels of material circularity (>90%) enable minimizing lifecycle wastes, can reduce virgin material demands if paired with improving efficiency, but demonstrate tradeoffs in energy return on investment. In the fervor of new material and technology development, it is important to remember that CE is not the end goal; decarbonization and energy transition are the end goal. CE should be used in service to improve the sustainability of PV, and R-actions evaluated for their usefulness and efficacy to this end.

carbon↗
DOE OSTI2025

Evaluation of Machine Learning Models for Automated Data Analysis in In-Service Nuclear Power Plant Inspections

The commercial nuclear power industry is facing a potential shortage of certified nondestructive evaluation (NDE) analysts to meet future in-service inspection demands. Automated data analysis (ADA) currently supports human inspectors in tasks such as eddy current evaluations for steam generator examinations. Machine learning (ML) systems are nearing the capability to pass performance demonstration tests for ultrasonic testing (UT) inspections of reactor pressure vessel upper head penetrations in nuclear power plants (NPPs). Current research and development is focused on assisted analysis (AA) of ADA versus fully automated examinations. This presentation will cover assessment of ML flaw detection on dissimilar metal weld (DMW) piping joints.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Experimental and Computational Study of Weld Drop-Through Hydraulic Effects in Multi-Layer Concentric Pipes Servicing Cryogenic Liquid Hydrogen

The Cryogenic Moderator System (CMS) at the Oak Ridge National Laboratory (ORNL)-Spallation Neutron Source (SNS) supplies liquid hydrogen, through vacuum insulated transfer lines to the moderators. The welding process used to make the transfer lines produces weld drop-through, which can constrict the flow of hydrogen and/or cause thermal bridges between adjacent layers. To ensure proper operation of the CMS it is therefore necessary to conduct a flow test to verify the pressure drop caused by the welds. Measurements in as-built piping sections intended to provide liquid hydrogen service to the SNS-CMS system were performed to test the effect of weld penetrations into the fluid flow area focusing on pressure drop effects. The reference test sections were designed using prototypical piping dimensions, materials and expected penetration welds. A numerical study using Computational Fluid Dynamics (CFD) tools in the transfer lines provided a conversion factor from the pressure drop measured in the lines with water to the expected pressure drop using liquid cryogenic hydrogen. The results show evidence of a maximum pressure drop modification in water of 78 KPa in the tested parts, which scales to liquid hydrogen as PHydrogen = 5.2 KPa. The maximum measured equivalent blockage area percentage was found in the as-built TDM transfer line spool 2 with a value of 31%. The measured values obtained in the as-built transfer lines provided accurate values to estimate the expected total pressure drop in the CMS system providing operational limits for the current recirculatory capacity. The effect of the weld drop-through in hydrogen evacuation capacity scenarios was better evaluated as a result of this study.

Dominguez-Ontiveros, Elvis [ORNL] (ORCID:000000018↗
DOE OSTI2023

Coordinated Wind Power Plant and Battery Control for Active Power Services

This article considers joint active power control of wind turbines and battery storage to follow a plant-level power reference signal. The joint control dynamically curtails the energy from a subset of the wind turbines and stores or withdraws energy from the battery to meet the power reference setpoint while accounting for wind plant aerodynamic interactions, such as wake losses. As a use case, we study the performance of the controller in maintaining a constant power output over hourly periods. A wind plant operating in this way would rely much less on other grid resources to meet its contractual agreements, thereby improving grid reliability, especially in grids with high penetration of wind and solar generation. We compare the operation of the wind plant under joint active power control to standard power-maximizing control with battery support. We present an analysis of the performance of the control system architecture. To study the impact of the battery size on performance, we simulate a 50-MW wind plant supported by batteries ranging from 8 to 64?MWh. We then evaluate the over and undergeneration penalties incurred by the plant during the simulation period.

17 WIND ENERGY↗
DOE OSTI2025

In-service corrosion and grain boundary oxidation in neutron-irradiated 316 stainless steel baffle-former bolts

Reactor core internal components such as baffle-former bolts (BFBs) are subjected to significant mechanical stress, corrosive environment, and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and of the bolts. In this work, characterization was performed on the oxidized surface of stainless steel BFBs harvested from a commercial pressurized water reactor (PWR) after 40 years of operation. The analysis shows that a complex multilayered surface oxide with six identified layers formed that is different from 2-layer structure commonly observed in model experiments. The oxide varies by composition – predominantly Fe, Cr, and Ni, grain size, and phase, and has features resembling both unirradiated and radiation/ corrosion experiments likely due to the low radiation flux compared to ion-irradiation or the test reactor radiation. In addition, grain boundary oxidative attack featured a pathway for Fe and other elements to move from the metal matrix to the outermost oxide. In conclusion, the results help assess PWR lifetime extension, put into context previous experimental studies, and provide input for designing experiments combining radiation and corrosion effects.

Baffle-former bolt↗