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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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DOE OSTI2025

Optimizing Grid Regulation With Gravity Storage Systems: A Comparative Analysis With Different Motor Inertias

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a high-inertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.

frequency regulation↗

DOE OSTI2024

FARM User Guidance and Instructions

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, the general workflow and the software requirements of FARM module are summarized, and the detailed instructions for installing FARM software, running built-in example cases, deriving Linear Parameter-Varying (LPV) state-space models, and using FARM for user-defined power dispatch problems are provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1973

The Lyapunov stabilization of satellite equations of motion using integrals

A method is introduced that weakens the Lyapunov or in track instability of satellite equations of motion. The method utilizes a linearized energy integral of satellite motion as a constraint on solutions obtained by numerical integration. The procedure prevents local numerical error from altering the frequency associated with the fast angular variable and thereby reduces the Lyapunov instability and the global numerical error. Applications of the method to satellite motion show accuracy improvements of two to three orders of magnitude in position and velocity after 50 revolutions. A modification of the method is presented that allows the use of slowly varying integrals of motion.

Nacozy, P. E.↗

NASA NTRS1984

ALESEP: A computer program for the analysis of airfoil leading edge separation bubbles

The ALESEP program for the analysis of the inviscid/viscous interaction which occurs due to the presence of a closed laminar transitional separation bubble on an airflow is presented. The ALESEP code provides a iterative solution of the boundary layer equations expressed in an inverse formulation coupled to a Cauchy integral representation of the inviscid flow. This interaction analysis is treated as a local perturbation to a known solution obtained from a global airfoil analysis. Part of the required input to the ALESEP code are the reference displacement thickness and tangential velocity distributions. Special windward differencing may be used in the reversed flow regions of the separation bubble to accurately account for the flow direction in the discretization of the streamwise convection of momentum. The ALESEP code contains a forced transition model based on a streamwise intermittency function and a natural transition model based on a solution of the integral form of the turbulent kinetic energy equation. Instructions for the input/output, and program usage are presented.

Davis, R. L.↗

NASA NTRS1986

ALESEP. Part 2: A computer program for the analysis of leading edge separation bubbles on infinite swept wings

A program called ALESEP is presented for the analysis of the inviscid-viscous interaction which occurs due to the presence of a closed laminar-transitional separation bubble on an airfoil or infinite swept wing. The ALESEP code provides an iterative solution of the boundary layer equations expressed in an inverse formulation coupled to a Cauchy integral representation of the inviscid flow. This interaction analysis is treated as a local perturbation to a known solution obtained from a global airfoil analysis; hence, part of the required input to the ALESEP code are the reference displacement thickness and tangential velocity distributions. Special windward differencing may be used in the reversed flow regions of the separation bubble to accurately account for the flow direction in the discretization of the streamwise convection of momentum. The ALESEP code contains a forced transition model based on a streamwise intermittency function, a natural transition model based on a solution of the integral form of the turbulent kinetic energy equation, and an empirical natural transition model.

Davis, R. L.↗

NASA NTRS1989

An improved algorithm for the modeling of vapor flow in heat pipes

A heat pipe vapor flow algorithm suitable for use in codes on microcomputers is presented. The incompressible heat pipe vapor flow studies of Busse are extended to incorporate compressibility effects. The Busse velocity profile factor is treated as a function of temperature and pressure. The assumption of a uniform saturated vapor temperature determined by the local pressure at each cross section of the pipe is not made. Instead, a mean vapor temperature, defined by an energy integral, is determined in the course of the solution in addition to the pressure, saturation temperature at the wall, and the Busse velocity profile factor. For alkali metal working fluids, local species equilibrium is assumed. Temperature and pressure profiles are presented for several cases involving sodium heat pipes. An example for a heat pipe with an adiabatic section and two evaporators in sequence illustrates the ability to handle axially varying heat input. A sonic limit plot for a short evaporator falls between curves for the Busse and Levy inviscid sonic limits.

Tower, Leonard K.↗

DOE OSTI2024

Optimizing Grid Regulation With Gravity Storage Systems: A Comparative Analysis With Different Motor Inertias: Preprint

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between the energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid generation-demand imbalances is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS systems provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 seconds from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS with a high-inertia motor may be able operate over a broader range of frequency variations whereas a low-inertia system may be limited by thermal constraints of the motor.

frequency regulation↗

DOE OSTI2024

Optimizing Grid Regulation with Gravity Energy Storage Systems: A Comparative Analysis with Different Motor Inertias

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a highinertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.

ENERGY STORAGE,POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1982

Photovoltaic array reliability optimization

An overview of the photovoltaic array reliability problem is presented, and a high reliability/minimum cost approach to this problem is presented. Design areas covered are cell failure, interconnect fatigue, and electrical insulation breakdown, and three solution strategies are discussed. The first involves controlling component failures in the solar cell (cell cracking, cell interconnects) and at the module level (must be statistically treated). Second, a fault tolerant circuit is designed which reduces array degradation, improves module yield losses, and controls hot-spot heating. Third, cost optimum module replacement strategies are also effective in reducing array degradation. This can be achieved by minimizing the life-cycle energy cost of the photovoltaic system. The integration of these solutions is aimed at reducing the 0.01% failure rate.

Ross, R. G., Jr.↗

DOE OSTI2026

Plan It Together: Optimizing Across Generation, Transmission, Distribution, and Distributed Energy Resources

Integrated planning holds the promise of unlocking lower total system cost solutions by connecting previously siloed planning processes. This article summarizes the state of bulk and local grid planning today and details multiple new analytical approaches that can enable more holistic planning methods to develop comprehensive solutions to generation, transmission, distribution, and distributed energy resource needs. These include both iterative approaches as well as cooptimization techniques. In addition to the benefits of these methods, the technical and institutional challenges and associated solutions are also discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system

New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.

08 HYDROGEN↗

DOE OSTI2020

Wind Energy Technologies Office Multi-Year Program Plan Fiscal Years 2021—2025

WETO's Multi-Year Program Plan outlines the Office’s research priorities and plans through the year 2025. With the objectives of reducing the cost of wind energy, enabling the integration of substantial amounts of wind energy into the evolving national energy system, and creating siting and environmental solutions to reduce environmental impacts, the Plan provides insight into DOE’s wind energy research priorities, and will guide planning and execution of future R&D activities. It is organized in six sections: offshore wind, land-based wind, distributed wind, systems integration, modeling and analysis, and crosscutting initiatives.

17 WIND ENERGY↗

NASA NTRS1984

A comparison of the efficiency of numerical methods for integrating chemical kinetic rate equations

The efficiency of several algorithms used for numerical integration of stiff ordinary differential equations was compared. The methods examined included two general purpose codes EPISODE and LSODE and three codes (CHEMEQ, CREK1D and GCKP84) developed specifically to integrate chemical kinetic rate equations. The codes were applied to two test problems drawn from combustion kinetics. The comparisons show that LSODE is the fastest code available for the integration of combustion kinetic rate equations. It is shown that an iterative solution of the algebraic energy conservation equation to compute the temperature can be more efficient then evaluating the temperature by integrating its time-derivative.

Radhakrishnan, K.↗

DOE OSTI2022

Toward a Fully Integrated Multiphysics Simulation Framework for Fusion Blanket Design

Fusion is an attractive clean-energy solution, thanks to its various advantages, such as reduced radioactivity, little high-level nuclear waste, ample fuel supplies, and increased safety. However, the harsh operating environment introduced by a complex fusion plasma system makes design and integration of fusion blankets incredibly challenging and time-consuming. This work focuses on developing a fully integrated multiphysics simulation framework based on an advanced open-source platform—the Multiphysics Object-Oriented Simulation Environment (MOOSE)—to alleviate the difficulties in fusion blanket design and integration. MOOSE is a massively parallel finite element/volume multiphysics simulation platform that has been widely adopted within the nuclear fission community. Even though fission and fusion are fundamentally different, they involve similar multiphysics phenomena. A fully integrated open-source multiphysics simulation framework tailored for the fusion blanket design will be implemented by leveraging the well-established multiphysics capabilities in MOOSE. Once successfully developed, this fully integrated framework will rapidly evaluate a blanket design concept and offer insights for subsequent iterations. As the first step, we will mainly aim to integrate neutronics analysis, system thermal hydraulics simulation, and full 3-D heat transfer calculations. The efficacy of the integrated framework will be verified using an innovative solid ceramic blanket design. While the project’s final goal is to enable a fully integrated multiphysics simulation platform for various fusion blanket concepts, here this work, as a preliminary step, will mainly focus on a solid ceramic breeder helium-cooled blanket.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Integration of Electrolysis Systems Into Isolated Microgrid Systems at Extreme Cold Climates

Isolated microgrid systems are generally used to power communities in remote locations where transmission line installations are cost prohibitive. These systems are usually powered by diesel generators, delivering expensive energy with high carbon emissions. However, most of these communities have special geographic access to renewable energy. These special conditions make it interesting to investigate the deployment of renewable energies and storage solutions. Within this scope, this paper analyses the integration of water electrolysis systems into off-grid communities, simulating the electrolyzer as well as the whole electrical grid in real time.

digital real-time simulation↗

DOE OSTI2024

3D Integrated Sensing Solutions

We will present the proposed research project to develop 3D-integrated sensors using advanced manufacturing capability for novel sensors, heterogeneously integrated with energy efficient readout circuits. The lack of precision timing in particle tracking detectors and the absence of low power, high throughput communications solutions to read them out limits progress in multiple fields of fundamental science. The aim of the project is to develop technology to enable large-scale particle detectors with 3D-integrated ASIC designs to simultaneously achieve 10 μm position resolution and 10 ps precision timing, with low-power consumption and high throughput rates. This research program leverages the unique combination of facilities and cross-disciplinary expertise of scientists and engineers at SLAC, FNAL, and LLNL and industrial partners.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Development of Energy Storage: Cost models

Energy storage technologies offer a promising solution to electric grid stability issues associated with the integration of variable renewable generators. The capability to match the electrical power output to instantaneous fluctuations in grid demand is crucial to ensure continuity of service. Including energy storage capability in an integrated energy system (IES) can provide the flexibility needed to meet variable electric demand and reduce the load following demands place on the reactor. In this report, economic data collected for energy storage (ES) technologies are described to support the objective of assessing the profitability of ES integration within the IES framework. In particular, there is a growing interest in thermal energy storage (TES) given its unique capability for long-duration storage for improving electricity reliability at a low levelized cost. It is common practice to evaluate the total lifetime cost and profitability before commercializing new technologies. In this report we identify and examine the models needed to better understand the economics of thermal energy storage. We extend the TES cost model in RAVEN in the context of a balance of plant (BOP) that incorporates thermal storage. To focus the discussion, following a general overview of the most promising TES technologies, we consider a use case that involves a sensible heat, two-tank, molten-salt system. Structural and operational details are reported to identify the source of construction capital expenditure and operation and maintenance cost. A detailed description of the different cost items is provided as well as the cost scaling with different storage capacity and power ratings for capacity optimization purpose. In addition, the capital expenditure and the recurring cost of representative two-tank, molten salt coupled with concentrated solar plants are provided for readers’ reference. The ES use case is noteworthy as it is in the pilot stage of commercialization. We identify those areas that would benefit from an increased economic focus to obtain a more complete compilation of cost data. We also describe the thermal coupling issues that arise from integration of the two-tank molten salt thermal energy storage system with a BOP, which is the subject of our current research. Some components of costs will need to be evaluated through dedicated technoeconomic analysis in future modeling activities using modeling procedures proposed in this report. With the data presented and the procedures described in this report, sufficiently accurate models can be implemented for the solution of both the power dispatch and the capacity expansion problems within the RAVEN-based HYBRID framework.

25 ENERGY STORAGE↗

NASA NTRS1984

A comparison of the efficiency of numerical methods for integrating chemical kinetic rate equations

A comparison of the efficiency of several algorithms recently developed for the efficient numerical integration of stiff ordinary differential equations is presented. The methods examined include two general-purpose codes EPISODE and LSODE and three codes (CHEMEQ, CREK1D, and GCKP84) developed specifically to integrate chemical kinetic rate equations. The codes are applied to two test problems drawn from combustion kinetics. The comparisons show that LSODE is the fastest code currently available for the integration of combustion kinetic rate equations. An important finding is that an iterative solution of the algebraic energy conservation equation to compute the temperature can be more efficient than evaluating the temperature by integrating its time-derivative.

Radhakrishnan, K.↗