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Results for “power system simulation”

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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Revealing conductivity of p-type delta layer systems for novel computing applications

This project uses a quantum simulation technique to reveal the true conducting properties of novel atomic precision advanced manufacturing materials. With Moore's law approaching the limit of scaling for the CMOS technology, it is crucial to provide the best computing power and resources to National Security missions. Atomic precision advanced manufacturing-based computing systems can become the key to the design, use, and security of modern weapon systems, critical infrastructure, and communications. We will utilize the state-of-the-art computational methodology to create a predictive simulator for p-type atomic precision advanced manufacturing systems, which may also find applications in counterfeit detection and anti-tamper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Simplification of the Grid Model and its Impact on the Analysis of Electrical Power Systems

Here, this paper analyzes the impact of the use of Kron reduction on the state variables of a three-phase electrical system, even when it does not meet the necessary conditions for its application. Reduction is applied to a power line model to eliminate the equation corresponding to the neutral conductor of the line. The ATP program is used to model and simulate the behavior of an electrical system considering different degrees of disequilibrium as a reference for the comparison of results. The results show that under certain conditions of disequilibrium the Kron reduction can lead to significant errors in the state variables of the system.

Electric Power Systems↗
NASA NTRS2001

Numerical Propulsion System Simulation: A Common Tool for Aerospace Propulsion Being Developed

The NASA Glenn Research Center is developing an advanced multidisciplinary analysis environment for aerospace propulsion systems called the Numerical Propulsion System Simulation (NPSS). This simulation is initially being used to support aeropropulsion in the analysis and design of aircraft engines. NPSS provides increased flexibility for the user, which reduces the total development time and cost. It is currently being extended to support the Aviation Safety Program and Advanced Space Transportation. NPSS focuses on the integration of multiple disciplines such as aerodynamics, structure, and heat transfer with numerical zooming on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS development includes using the Common Object Request Broker Architecture (CORBA) in the NPSS Developer's Kit to facilitate collaborative engineering. The NPSS Developer's Kit will provide the tools to develop custom components and to use the CORBA capability for zooming to higher fidelity codes, coupling to multidiscipline codes, transmitting secure data, and distributing simulations across different platforms. These powerful capabilities will extend NPSS from a zero-dimensional simulation tool to a multifidelity, multidiscipline system-level simulation tool for the full life cycle of an engine.

Follen, Gregory J.↗
NASA NTRS1984

Minimum time and fuel flight profiles for an F-15 airplane with a Highly Integrated Digital Electronic Control (HIDEC) system

A simulation study was conducted to optimize minimum time and fuel consumption paths for an F-15 airplane powered by two F100 Engine Model Derivative (EMD) engines. The benefits of using variable stall margin (uptrim) to increase performance were also determined. This study supports the NASA Highly Integrated Digital Electronic Control (HIDEC) program. The basis for this comparison was minimum time and fuel used to reach Mach 2 at 13,716 m (45,000 ft) from the initial conditions of Mach 0.15 at 1524 m (5000 ft). Results were also compared to a pilot's estimated minimum time and fuel trajectory determined from the F-15 flight manual and previous experience. The minimum time trajectory took 15 percent less time than the pilot's estimate for the standard EMD engines, while the minimum fuel trajectory used 1 percent less fuel than the pilot's estimate for the minimum fuel trajectory. The F-15 airplane with EMD engines and uptrim, was 23 percent faster than the pilot's estimate. The minimum fuel used was 5 percent less than the estimate.

Haering, E. A., Jr.↗
DOE OSTI2024

Impact of K-factor on Short Circuit Program Convergence for Inverter-Based Resources during Faults

Classical short-circuit programs that linearize the power network are no longer applicable for inverter based resources (IBRs), necessitating an iterative approach. Phasor domain programs can model the IBRs using an iterative approach considering nonlinear fault responses. In phasor domain models, the IBR can be modeled as a voltage controlled current source (VCCS) in tabular form with positive, negative, and zero sequence information for balanced and unbalance short-circuit faults. In the VCCS modeling of the IBR, positive and negative incremental reactive current, also known as the k-factor, plays an important role in short circuit program convergence. In this work, a few approaches: conventional VCCS modeling with a k-factor of 2, conventional VCCS modeling with a k-factor of 2 with modified pre-fault voltages, VCCS characteristics based on the power flow solution with a k-factor of 2, and VCCS characteristics based on the power flow solution with a k-factor of 1 are investigated for short circuit program convergence under higher IBR penetration. The IEEE 39 bus New England Test System is taken as the test system, and simulations are carried out in PSS®CAPE 15.0.26 simulation software. Simulation results demonstrate that IBR penetration is higher for the VCCS model, which corresponds to the power flow solution with k-factor 1, compared to other approaches.

42 ENGINEERING↗
DOE OSTI2022

Performance Evaluation of Distributed Energy Resource Management Algorithm in Large Distribution Networks

This paper presents performance evaluation of hierarchical optimization and control for distributed energy resource management system (DERMS) in large distribution networks via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory envi-ronment, including the accurate modeling of a full-scale dis-tribution system of 11,000 nodes, the DERMS software con-troller, and 90 power hardware photovoltaics (PVs) and bat-tery inverters. The applied DERMS algorithm is designed based on a real-time optimal power flow algorithm and im-plemented with acceleration design that performs fast dis-patch of simulated PVs and real physical hardware DER devices every 4 seconds.

distributed energy management system (DERMS)↗
DOE OSTI2021

Hot Raman amplification

A parameter regime is identified for Raman amplification at high temperatures, where deleterious laser–plasma instabilities that limit current amplification experiments are avoided, yet sufficient gain for an effective power amplifier is attained. Furthermore, calculations and kinetic simulations show that even at high temperatures, an amplifier is able to satisfy the criteria set forth to present a proof-of-principle system scalable to high powers, where energy transfer efficiencies are ≥30%, intensity gains are ≥10, and output intensities are ≥100× the pump intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1980

Space environmental interactions with biased spacecraft surfaces

Large, high-voltage space power systems are being proposed for future space missions. These systems must operate in the charged-particle environment of space, and interactions between this environment and the high-voltage surfaces are possible. Ground simulation testing has indicated that dielectric surfaces that usually surround biased conductors can influence these interactions. For positive voltages greater than 100 V, it has been found that the dielectrics contribute to discharges. Using these experimental results a large, high-voltage power system operating in geosynchronous orbit was analyzed with the NASCAP code. Results of this analysis indicated that very strong electric fields exist in these power systems. A technology investigation is required to understand the interactions and develop techniques to alleviate any impact on power system performance.

Stevens, N. J.↗
DOE OSTI2024

Is a Generator the Only Solution When the Grid Fails? Optimizing Systems for Resiliency and Carbon Reduction: Preprint

Traditionally, buildings are dependent on utility infrastructure, and when a grid failure happens, end users rely on the closest source of energy storage to sustain operation until power is restored. For buildings, that typically means using an electric generator. This electric generator either uses on-site energy storage such as fossil fuels in a tank or a gas connection which is, in turn, tied to gas wells—also a form of energy storage. Generators are popular for their ease of implementation and low capital costs; however, they have limited value outside of disruptions, and they are a source of scope 1 emissions, or direct greenhouse gas emissions from sources controlled by the building owner. In contrast, some power generation and storage systems, such as photovoltaic (PV) panels and battery energy storage systems (BESS), can serve the same purpose during grid disruptions while presenting advantages outside of power failure. This paper explores methods for storing and converting energy on-site to increase building resiliency, focusing on solutions that minimize scope 1 emissions. We analyze the cost and carbon impacts of energy efficiency measures, PV arrays, and BESS, with and without generators, in a simulation test case. We find significant benefits can be achieved both during and outside of power failure events when designing systems that integrate the on-demand capability of generators, the low carbon energy supplied by PV, and the storage capabilities of BESS. Specifically, adding even minimal BESS and PV can result in downsizing the generator, increasing generator efficiency and requiring less fuel.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Dynamometer Facts

The National Renewable Energy Laboratory's (NREL's) Flatirons Campus features two dynamometers in the Water Power Systems Laboratory that can perform research validation on marine and hydrokinetic energy devices as well as wind turbine systems from 100 watts to 15 kilowatts (kW) in size. These capabilities can also be combined with programmable loads, blue economy (nrel.gov/water/powering-blue- economy.html) application simulators, and microgrid emulators to test an extensive range of system operation and technology integration. The dynamometers replicate realistic operational conditions to assess power take-of systems and advance the technical readiness of innovations.

dynomometer↗
DOE OSTI2020

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2010

Advanced Stirling Convertor Dynamic Test Approach and Results

The U.S. Department of Energy (DOE), Lockheed Martin Corporation (LM), and NASA Glenn Research Center (GRC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. As part of the extended operation testing of this power system, the Advanced Stirling Convertors (ASC) at NASA GRC undergo a vibration test sequence intended to simulate the vibration history that an ASC would experience when used in an ASRG for a space mission. This sequence includes testing at workmanship and flight acceptance levels interspersed with periods of extended operation to simulate prefueling and post fueling. The final step in the test sequence utilizes additional testing at flight acceptance levels to simulate launch. To better replicate the acceleration profile seen by an ASC incorporated into an ASRG, the input spectra used in testing the convertors was modified based on dynamic testing of the ASRG Engineering Unit (ASRG EU) at LM. This paper outlines the overall test approach, summarizes the test results from the ASRG EU, describes the incorporation of those results into the test approach, and presents the results of applying the test approach to the ASC-1 #3 and #4 convertors. The test results include data from several accelerometers mounted on the convertors as well as the piston position and output power variables.

Meer, David W.↗
DOE OSTI2023

Modeling Tool Development and Validation for Solar Industry Process Heat Using Particle Thermal Energy Storage

U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.

concentrated solar thermal↗
DOE OSTI2024

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. Furthermore, this supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.

42 ENGINEERING↗
DOE OSTI2024

A High-Fidelity Electromagnetic Transient Model of Inverter-based Resources Integrated to an IEEE-9 Bus System for Benchmarking Studies

An inverter-based resource (IBR) is a source of electricity that is asynchronously connected to the electrical grid via an electronic power converter. These power sources lack the intrinsic behaviors of the standard power plants, presenting specific challenges to system stability. These power sources lack the intrinsic behaviors of the standards power plants and their features are almost entirely defined by the control strategy used on them, presenting specific challenges to system stability as their penetration increases into the already fragile Bulk Power System (BPS). Utilizing renewable energy has a great upside but the electrical industry needs to understand the requirements like performing electromagnetic transient (EMT) simulation studies in planning and/or in interconnection studies. This paper presents the development of a high-fidelity EMT model based on commercial equipment and field parameters, which at the same time aims to study the increasing penetration of IBRs and their impact on the actual BPS. The open-source EMT model developed will be a benchmarking example that can be used to evaluate algorithms in the power grid (including evaluating grid-forming controls, power system monitoring and operation, etc.).

Martinez Montejano, Misael↗