SEARCH · Search NASA

Results for “load following”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

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 OSTI2020

Hybrid Analytics Solution for Power Plant Operations

Expert Microsystems, Inc., MapEx Software Inc. and XMPLR Energy LLC have teamed to submit a proposal to the US Department of Energy’s Office of Fossil Energy to improve the efficiency, reliability and flexibility of existing coal-based power plants. The project, titled Hybrid Analytics Solution to Improve Coal Power Plant Operations (the “Hybrid Analytics” project), will develop, demonstrate and commercialize a novel approach that integrates two proven real-time monitoring techniques. The Hybrid Analytics approach integrates into a single, integrated solution: a) an established, advanced data-driven analytics solution that includes artificial intelligence, advanced pattern recognition and machine-learning techniques and b) a well-proven, first principle thermal heat balance model solution. The future role of coal plants will depend on the ability to cycle and follow loads to meet marginal power demands, accommodate renewables and support the grid. Essential to success in this new role is a plant’s ability to maintain high reliability, efficiency and flexibility. However, these changing operational demands put significant stresses on power plant components that directly impact the ability to deliver these requirements. In the past, plants have independently monitored performance using physics-based solutions (heat rate, boiler losses, etc.) and reliability using data-driven analytics (advanced pattern recognition). The Hybrid Analytics solution integrates both approaches to enhance fault detection, provide automated diagnostics and estimates of remaining time to act, and provide critical, enhanced and accurate real-time information to coal plant operators. As a result, coal plants can improve efficiency, reliability, and flexibility and can cost-effectively maintain their key role in the power delivery system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Advanced Sensors & Controls FWP Overview

Fossil energy power generation is needed now and in the future, but its role is shifting from baseload operation to fulfilling dispatchable power needs in regions of the United States. Novel sensors and controls will help to increase efficiency, minimize emissions, and reduce operating costs of existing power generation technologies under this increased load following role; and help enable next generation power systems with high efficiency and greater operational flexibility.<br>

Buric, Michael↗

DOE OSTI2022

Learning-based Anticipatory Control of Microreactors

Learning-based anticipatory control advances the level of autonomy of microreactor control systems, a key consideration for the unattended operation of fission batteries. In this work, an anticipatory control system is shown to provide accurate load-following for a microreactor by utilizing a model predictive control framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Stability margin analysis of the Holos-quad microreactor design

A simplified point model of the Holos-Quad microreactor is introduced. The model is based on the point kinetics equations coupled to three heat balance equations, representing the mean temperatures of the fuel particles, the graphite moderator and the helium coolant. The differential equations are converted to the frequency domain, enabling the construction of the closed-loop reactor transfer function. Using this function the stability margins of the core design is analyzed for various power levels. It is shown that the gain margins approaches infinity, demonstrating the stability of the reactor for all power levels. The phase margin at nominal power is about 60 degrees, however it shows a non-monotonous dependence on power, with minimal value obtained for about 10% of nominal power. As power level is further increased, the phase margin also increases, demonstrating the reactor becomes more stable. This behavior may be of high importance in load-follow scenarios, where the power level of the reactor changes with time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Techno-Economic Analysis of a Nuclear Reactor System coupled with a Liquid Metal Battery

There is a need for nuclear reactor systems to become more dynamic as defossilization and renewable energy sources continue to reshape the energy grid. One option to meet these changing demands is to pair the reactor with an energy storage system. This work details a technoeconomic analysis and sensitivity analysis of a high temperature gas cooled microreactor, supercritical carbon dioxide power cycle, and liquid metal battery. Dynamic modeling has shown that these three systems compliment each other to provide load following and black-start capabilities to the grid. Current cost estimates for installing the systems yield a competitive levelized cost of electricity and levelized cost of storage, indicating that such a combined system may be economically viable as technological advances lead to them being technically feasible.

25 ENERGY STORAGE↗

DOE OSTI2023

Modeling a Gas-Cooled Microreactor Balance of Plant for the Virtual Test Bed

High Temperature Gas-cooled Reactors (HTGRs) are one of the technology considered for microreactor designs because of their high performance and technological maturity. Several designs are being developed. These microreactor cores are connected to power conversion system (PCS) through a heat exchanger. For transient analysis, the feedback of the PCS or of the primary loop can be important, therefore, it is necessary to develop robust models for the balance of plant that can be coupled to a core model. In this work, a balance of plant model using the MOOSE Thermal Hydraulics module (THM) is presented and demonstrated for startup and load-follow transients. This model can be seamlessly coupled with any MOOSE-based multi-physics core model using the MOOSE multi-app approach.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Hydrogen and its Vital Role in a Clean Energy Future

Large-scale, low -cost hydrogen production can enable an economically competitive, secure, and environmentally beneficial future energy system across multiple sectors. Furthermore, clean hydrogen can address specific sectors that are hard to decarbonize (e.g., heavy-duty trucking, load-following electricity, iron, steel, and cement) and can help the U.S. meet the net zero carbon goal by 2050. To achieve this goal, tens of millions of metric tons of clean, reliable, and affordable hydrogen will be needed annually1. In 2021, the Hydrogen Energy Earthshot was launched, and its goal is to reduce the cost of clean hydrogen to $1 per $1 kilogram in 1 decade (1 1 1) 2. One very promising pathway for large-scale hydrogen production is water splitting. Water splitting technologies range from commercial technologies such as electrolyzers to approaches that are at a much earlier stage of development, such as photoelectrochemical (PEC) and thermochemical (TCH) processes. All these water splitting pathways offer diverse benefits in energy storage, grid services, and cross-sector emissions reductions while taking advantage of the diverse domestic resources. However, critical materials-, component- and system-level challenges must be addressed to improve efficiency and durability and reduce cost. To address these barriers and move these promising and high impact technologies forward, the HydroGEN Advanced Water Splitting Materials (AWSM) and the H2 from the Next-generation of Electrolyzers of Water (H2NEW) consortia were formed and supported by the Department of Energy (DOE) EERE Hydrogen and Fuel Cell Technologies Office (HFTO). HydroGEN (https://www.energy.gov/eere/h2awsm/) consortium, established in 2016, is an Energy Materials Network (EMN) that aims to accelerate the materials R&D of low technology readiness level (TRL) advanced water splitting (AWS) technologies. The consortium comprises five core national laboratories and focuses on four early-stage AWS pathways: alkaline exchange membrane (AEM) electrolysis, proton conducting solid oxide electrolysis (p-SOEC), photoelectrochemical, and thermochemical water splitting. Liquid alkaline and PEM electrolyzers are already commercial and significant advancements in oxygen conducting solid oxide electrolysis cells (o-SOECs) have been realized. Yet, these systems are still too expensive and not sufficiently durable for wide-scale commercialization. To enable high-volume manufacturing of affordable, durable, efficient electrolyzers, H2NEW (https://h2new.energy.gov/), another multi-lab consortium, was established in 2020. This comprehensive, concerted effort is focused on overcoming barriers related to components and materials integration and scale-up to achieve performance, durability, with an initial focus to achieve $2/kg H2 by 2026.

AEM↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM

Demand response (DR) serves an important role in improving the efficiency and stability of power systems. In recent years, with advances in communication and smart device technologies, many aggregators have emerged to facilitate end customer participation in DR programs. These aggregators, equipped with customized optimal control algorithms, are capable of providing various grid services. Among them is load scheduling during DR events, namely following a load signal provided by the utility company while minimizing overall customer discomfort. However, as the number of aggregators keeps increasing, it becomes challenging for utility companies to conduct load scheduling for multiple aggregators and generate reference signals for each of them. This paper proposes an optimization framework using hierarchical alternating direction method of multipliers (H-ADMM) to optimally generate load following signals for multiple aggregators. Under this framework, utility and multiple aggregators work in a cooperative manner, aiming at minimizing an overall system cost from different levels of the power system hierarchy, while protecting user privacy. A case study has been conducted in a system with multiple aggregators, based on control of HVAC loads. Experimental results validate the effectiveness of the proposed algorithm.

ADMM↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM: Preprint

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Iodine Capture by Ag-Loaded Solid Sorbents Followed by Ag Recycling and Iodine Immobilization: An End-to-End Process

Here, this article demonstrates the complete process of I 2(g) capture using Ag-exchanged faujasite (AgX) and Ag-exchanged mordenite (AgZ) zeolite sorbents, the recovery of Ag for recyclability of iodine capture, and the immobilization of iodide (from the elution process) into an iodosodalite waste form, which is chemically and environmentally stable. The gaseous iodine, I 2(g) , was captured in the AgX via chemisorption by Ag and converted to AgI within the aluminosilicate zeolite frameworks. The elution reaction in Na 2 S resulted in the precipitation of Ag 2 S and dissolution of I – and Na + into the aqueous solution, where powdered sorbent showed higher conversion efficiency than the granular form, which is attributed to Na 2 S-solution diffusion limitations in the granules. The Ag 2 S-containing aluminosilicate precipitates were filtered out of the solution, and the filtrate (aqueous solution) was used to synthesize iodosodalite to immobilize iodide. The iodine capture using the recovered Ag 2 S-containing sorbents shows equivalent iodine loadings to the AgX starting material of Q e = 0.355 g/g for powdered material and 0.255 g/g for granular material, demonstrating the potential recycling of Ag for iodine capture as Ag 2 S-based sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Spatial and Temporal Interpolation Analysis Process of Shock Loading

The following document serves to describe the current process that is utilized by W-13 analysts to approximate the pressure-time boundary condition seen by a test object from shock tube loading. The intent of this report is to capture the current capability and to encourage continued growth and development. Information on the required input variables, mapping process, and generated output information is covered in the following sections. Throughout the document, gaps and weaknesses of the mapping process are noted to encourage future development efforts.

42 ENGINEERING↗

DOE OSTI2026

Persistent Elevated Soot Emissions Induced by Clustered Stochastic Preignition Events

Stochastic Preignition (SPI) is an abnormal combustion phenomenon that can occur in spark-ignition engines particularly under high-load operation. SPI is characterized by uncontrolled initiation of combustion prior to spark discharge, an abnormal combustion process that can lead to severe knock events and significant engine damage. SPI has been associated with fuel properties, lubricant composition, and engine design and operation. Here, in this work, a single-cylinder test engine with a dry-sump oil system was utilized to study the SPI response of E10 and E25 fuels with a range of Reid Vapor Pressure (RVP). An automated test procedure was employed, consisting of ten square-waved load profile segments, with each segment composed of 5 min of low-load operation followed by 25 min of sustained high-load operation. These tests were replicated across multiple days of testing including a lubricant triple flush between tests, and an online Fuel in Oil diagnostic measurement. Exhaust particulate emissions were continuously measured by an AVL microsoot sensor (MSS). Elevated particulate matter emissions were observed to occur concurrently with SPI events as blooms of soot. Particularly after clustered events (i.e., multiple SPI cycles occurring within 10 consecutive engine cycles), high soot emissions were observed to persist over several days of sequential operation despite daily lubricant changes, a complete warm-up procedure, and sustained low-load operation between test segments. This result implies that the particulate emissions trends may be dominated by deposit-based effects, where higher load operation is needed to alter deposition and formation processes. The observed soot blooms were also found to correspond to a reduction in the engine fueling and the fuel engine oil dilution rate despite the engine exhaust remaining at stoichiometric exhaust operation. These observations suggest that post-SPI events, pathways for lubricant migration and consumption into the combustion chamber may occur until these pathways are closed from deposit formation or ring dynamics during extended operation. These observed sooting propensity persisted with all fuels tests, but a linear correlation was observed between the summation of soot and particulate matter index (PMI) value for each fuel as well as SPI events, proving that PMI is a crucial fuel property for reducing SPI.

Splitter, Derek [Oak Ridge National Laboratory (OR↗

DOE OSTI2021

Impact of particle loading and phase coupling on gas–solid flow dynamics: A case study of a two-phase, gas–solid flow in an annular pipe

The present study is devoted to a two-phase, gas–solid flow in an annular pipe (hollow cylinder) at an elevated pressure of 15 bars and moderate Reynolds number of circa 6000. The influence of the particle loading, the interaction between the phases, and turbulence dispersion on the flow dynamics is systematically studied by means of computational fluid dynamics simulations, employing the Ansys FLUENT commercial package. The cases with a particle volumetric fraction of 1.2% are referred to as “high particle loading,” and those with 0.13% are denoted as “low particle loading.” The following cases are investigated: (1) pure gas flow; (2) low particle loading two-phase flow with one-way coupling and with turbulence dispersion; (3) low particle loading two-phase flow with two-way coupling but without turbulence dispersion; (4) low particle loading two-phase flow with two-way coupling and with turbulence dispersion; (5) high particle loading two-phase flow with one-way coupling and with turbulence dispersion; (6) high particle loading two-phase flow with two-way coupling but without turbulence dispersion; and (7) high particle loading two-phase flow with two-way coupling and with turbulence dispersion. Additionally, the boundary layer is found to grow without fluctuations of the turbulent kinetic energy (TKE) for cases 1, 2, and 5. For case 4, the TKE fluctuations have been identified, although they appear to be less substantial than those in cases 6 and 7. The authors attribute the semi-chaotic nature of the TKE fluctuations to the particle loading and two-way coupling. In addition, the onset and development of the flow instability have been observed at a random axial distance in cases 4, 6, and 7. Such instability is also attributed to the two-way coupling with turbulence dispersion in the flow. It is concluded that the particle loading, one-way, or two-way coupling between the phases, and the turbulence dispersion models significantly influence the development of the flow dynamics with the same inlet and boundary conditions. Consequently, it is not a trivial question, which result a user should trust. The present computational results inspire to perform verification as well as experimental validation of the simulations, so the simulation results can subsequently be used with confidence for design analysis.

42 ENGINEERING↗

DOE OSTI2025

Loading Capacity and Dilute Nitric Acid Rinse of Diglycolamide Resin for the Recovery of Transplutonium and Rare Earth Elements from Mark-18A Targets

N,N,N′,N′-tetraoctyldiglycolamide (TODGA) as a resin (“DGA resin”) produced by Eichrom Technologies will be used by Savannah River National Laboratory for the indiscriminate extraction of trivalent actinides and rare earth elements with the intent of recovering Cm and Am from dissolved irradiated 242 Pu Mark-18A targets in 7 to 9 M nitric acid. The extracted constituents will be recovered as an oxide by direct thermal decomposition of the loaded resin followed by calcination of the resultant residue. The characteristics of DGA resin with non-radiological feed simulant representative of the anticipated feed in the Mark-18A process, with Sm and Nd as surrogates for Cm and Am, respectively, including breakthrough point and saturation capacity were evaluated in this work. Additionally, this work examined the losses from the loaded resin by rinsing the resin bed with dilute acid to reduce the nitrate concentration in the resin bed prior to thermal decomposition operations to improve the safety posture of the process. A resin loading profile was developed, and the resin was determined to have a trivalent metal saturation capacity of 74 μmol/mL resin under the experimental conditions evaluated. Following a wash of the loaded resin bed with fresh 8 M HNO 3 , the trivalent metals retained was reduced to 68 μmol/mL resin, which represents the practical capacity of the resin for the Mark-18A process. Lighter lanthanides breakthrough the resin well before the saturation capacity is reached. Rinsing the saturated resin bed with 0.26 M HNO 3 was found to result in a rapid reduction in retention of rare earth elements by the resin. After 2.8 bed volumes of dilute acid rinse, the mean resin bed free acid concentration was reduced to 0.28 M and 3.1 bed volumes of dilute acid rinse resulted in a reduction of the cumulative rare earth element retention to 52 μmol/mL of resin.

Transplutonium separations↗

DOE OSTI2024

MICROREACTOR APPLICATIONS, RESEARCH, VALIDATION, AND EVALUATION (MARVEL) REACTOR ? STATUS, CONSTRUCTION, AND TESTING

The paper presents the current status of the Microreactor Applications, Research, Validation, and Evaluation (MARVEL) microreactor design, qualification testing, fabrication, and high-level construction schedule. An overview of initial criticality, low power physics testing, and start-up testing is included, as well as an overview of the envisioned processes in which end-users can engage the project for access to operational data or specific demonstrations. Designed by the Idaho National Laboratory (INL) under the auspices of the US Department of Energy’s Microreactor Program for construction and operation at the INL, MARVEL is a small, fully functional advanced reactor with UZrH fuel and thermal output of 85 kW. It offers a unique opportunity for scaled demonstrations that can dramatically accelerate the design, licensing, and deployment of commercial microreactors for power production or process heat applications. MARVEL’s objective is to build a small liquid-metal thermal reactor at the INL to demonstrate design and operating processes for microreactors, microgrid integration, and process heat applications. MARVEL finished 90%-final-design in September 2023 and completed an independent project assessment in early 2024. Fabrication of long-lead components and fuel, safety analysis review, and procurement for construction are underway. MARVEL assembly and construction will start in 2025 and fuel loading is expected in mid- 2027. Initial criticality will be performed in a dry condition in late 2027, followed by loading of NaK coolant and start-up testing. Approximately six months later, release for unrestricted operations will enable subsequent testing of microreactor characteristics, microgrid integration and select heat extraction applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗