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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 199 records · Page 11

Modeling and Feedback Compensator Design for Power-Hardware-in-the-Loop System for Medium-Voltage Grid-Connected Power Converters

Hardware-in-the-loop (HIL) evaluation is a method in which the test subject is split into a physical part and a simulated part, and these parts are connected with interfaces to form a combined physical-numerical system. Power-hardware-in-the-loop (PHIL) systems, where actual hardware is connected to a real-time model, can exhibit issues of instability, inaccuracy and errors when operating in a closed-loop. The challenges of generating a PHIL setup are that, first, because of the limited dynamic response of the different parts of the system, the test results might be inaccurate, and, second, because of the high frequency noise introduced by the sensors to the closed-loop system, it can be difficult to design a compensator for the real-time emulator response, while stabilizing the closed-loop system at the same time. In this paper, different parts of a PHIL system are characterized, and the feedback compensator system design is proposed for the stable operation of the closed-loop PHIL system. The issues as observed in a PHIL system without any compensator are demonstrated using experimental results, and the effectiveness of a first order phase lead compensator is validated.

compensator design↗

Development of Supervisory Control System for Thermal Energy Distribution System

The integrated energy system (IES) refers to the combination of nuclear energy generation with other energy sources to enable the efficiency and reliability of power generations. To create technologically viable and economically competitive systems, supervisory control strategies are critical for optimizing performance and ensuring stability across different energy generation, transportation, and utilization. This work focuses on the control strategies for the thermal energy distribution system (TEDS), which is a cornerstone of the Dynamic Energy Transport and Integration Laboratory at Idaho National Laboratory. TEDS currently relies on operators to coordinate across different components to manage energy storage and ensure efficiency. This work demonstrates the use of model predictive control (MPC) with surrogate models in determining optimal setpoints for major TEDS components. The capability of MPC-based supervisory control system is evaluated by autonomously matching the power outputs from a Dymola-based TEDS with target heat demands.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Stability and Fidelity of Power-Hardware-in-the-Loop Using NREL's CGI

The presentation focuses on dynamic analysis of power hardware-in-the-loop (PHIL) experiments using National Renewable Energy Laboratory Flatirons Campus' grid simulator - 7MVA Controllable Grid Interface (CGI). A control diagram of typical PHIL experiment is described, and transfer functions of critical components are explained. An impedance-based definition of PHIL experiment bandwidth is defined using open loop transfer functions of the system. Further an example resistive divider circuit is introduced that is used to explain implication of PHIL on accuracy of simulation by comparing measured results against ideal expected signals. At the end the real-life PHIL simulation using Maui power system model is described showing various oscillation modes observed and discussing the meaning of these in context of dynamic bandwidth of simulation.

grid simulator↗

Efficient and Robust Dynamic Simulation of Power Systems With Holomorphic Embedding

Dynamic simulation is vitally important in power system analysis, but traditional approaches based on numerical integration over small time steps are time-consuming. Also, the Newton-Raphson method suffers from difficulty in convergence when solving nonlinear algebraic equations. In this paper, we propose a novel dynamic simulation approach based on holomorphic embedding. By obtaining a high-order approximation of system dynamics, it achieves a much larger time step and thus enhances the computational efficiency significantly. In addition, the new approach avoids non-convergence issues in solving algebraic equations, which improves robustness. The approach includes flexible modeling of synchronous generators and controllers, and we propose a method for modeling generator coordinate transformations. The approach is tested on the IEEE 39-bus, 10-generator system and a Polish 2383-bus, 327-generator system. The results demonstrate promising computational efficiency and satisfactory numerical robustness for the analysis of large-scale power systems.

42 ENGINEERING↗

Properties of earthquakes generated by fault dynamics

A model for fault dynamics consisting of a uniform chain of blocks and springs pulled slowly across a rough surface is presented. The only nonlinear element of the model is a slip-stick friction force between the blocks and the surface. It is found that this model gives rise to events of all sizes. The numerical evaluation of the distribution of earthquake magnitudes results in a power-law spectrum similar to what is observed in nature. Like certain other dissipative dynamical systems, the observed large fluctuations in earthquake magnitude persist because the system is in a state of marginal stability.

Carlson, J. M.↗

Engineering information on an Analog Signal to Discrete Time Interval Converter (ASDT-IC)

An electronic control system for nondissipative dc power converters is presented which improves (1) the routinely attainable static output voltage accuracy to the order of + or - 1% for ambient temperatures from -55 to 100 C and (2) the dynamic stability by utilizing approximately one tenth of the feedback gain needed otherwise. Performance is due to a functional philosophy of deterministic pulse modulation based on pulse area control and to an autocompensated signal processing principle. The system can be implemented with commercially available unselected components.

Schwarz, F. C.↗

WRATS Integrated Data Acquisition System

The Wing and Rotor Aeroelastic Test System (WRATS) data acquisition system (DAS) is a 64-channel data acquisition display and analysis system specifically designed for use with the WRATS 1/5-scale V-22 tiltrotor model of the Bell Osprey. It is the primary data acquisition system for experimental aeroelastic testing of the WRATS model for the purpose of characterizing the aeromechanical and aeroelastic stability of prototype tiltrotor configurations. The WRATS DAS was also used during aeroelastic testing of Bell Helicopter Textron s Quad-Tiltrotor (QTR) design concept, a test which received international attention. The LabVIEW-based design is portable and capable of powering and conditioning over 64 channels of dynamic data at sampling rates up to 1,000 Hz. The system includes a 60-second circular data archive, an integrated model swashplate excitation system, a moving block damping application for calculation of whirl flutter mode subcritical damping, a loads and safety monitor, a pilot-control console display, data analysis capabilities, and instrumentation calibration functions. Three networked computers running custom-designed LabVIEW software acquire data through National Instruments data acquisition hardware. The aeroelastic model (see figure) was tested with the DAS at two facilities at NASA Langley, the Transonic Dynamics Tunnel (TDT) and the Rotorcraft Hover Test Facility (RHTF). Because of the need for seamless transition between testing at these facilities, DAS is portable. The software is capable of harmonic analysis of periodic time history data, Fast Fourier Transform calculations, power spectral density calculations, and on-line calibration of test instrumentation. DAS has a circular buffer archive to ensure critical data is not lost in event of model failure/incident, as well as a sample-and-hold capability for phase-correct time history data.

Piatak, David J.↗

Interaction of feel system and flight control system dynamics on lateral flying qualities

An experimental investigation of the influence of lateral feel system characteristics on fighter aircraft roll flying qualities was conducted using the variable stability USAF NT-33. Forty-two evaluation flights were flown by three engineering test pilots. The investigation utilized the power approach, visual landing task and up-and-away tasks including formation, gun tracking, and computer-generated compensatory attitude tracking tasks displayed on the Head-Up Display. Experimental variations included the feel system frequency, force-deflection gradient, control system command type (force or position input command), aircraft roll mode time constant, control system prefilter frequency, and control system time delay. The primary data were task performance records and evaluation pilot comments and ratings using the Cooper-Harper scale. The data highlight the unique and powerful effect of the feel system of flying qualities. The data show that the feel system is not 'equivalent' in flying qualities influence to analogous control system elements. A lower limit of allowable feel system frequency appears warranted to ensure good lateral flying qualities. Flying qualities criteria should most properly treat the feel system dynamic influence separately from the control system, since the input and output of this dynamic element is apparent to the pilot and thus, does not produce a 'hidden' effect.

Bailey, R. E.↗

Light induced ion migration studies in perovskite solar cell using nonlinear impedance spectroscopy

Complex interactions between mobile ions and charge carriers in perovskite solar cells (PSCs) make it challenging to fully understand their dynamic interplay. Exposure to light further complicates these interactions, altering the system’s dynamics and inducing nonlinear effects that lead to changes in the J−V curve. Understanding these effects is crucial for improving the operational stability of PSCs. Impedance spectroscopy (IS) is a powerful technique for evaluating relaxation processes in the frequency domain; however, it is limited in capturing nonlinear contributions. Here, in this work, nonlinear impedance spectroscopy (NLIS) is employed to analyze the higher harmonic response to AC perturbation, both in the dark and after short-term light exposure. A shift in the low-frequency (LF) higher harmonic peak is observed after open-circuit light exposure, attributed to an altered electric field suggesting ion re-distribution, whereas closed-circuit exposure shows no LF shift, indicating minimal ion movement. Additionally, light exposure reduces higher-order admittance, more notably in open-circuit conditions, suggesting decreased recombination. Temperature-dependent analysis was conducted to characterize the activation energy of migrating species, identifying iodide as the dominant migrating ion.

14 SOLAR ENERGY↗

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗

A Self-Organizing Nano Grid (SONG) for Energy Access Clusters

In this paper, a bottom-up dc Self-Organizing Nano Grid (SONG) for rural electrification at ultra-low-cost through a flexible and scalable topology is presented. The proposed nano grid requires no communication and uses dc-bus signaling to convey excess energy in the system through the bus voltage, allowing independent agents to conduct energy transactions based on their needs in a decentralized manner. Moreover, this article proposes a concept that uses a novel multi-source, multi-segment droop control strategy with demand coordination, allowing for dynamic self-balancing of the system under fluctuating operating conditions. The unique use of a surplus photovoltaic (PV) power droop mode precisely estimates energy availability to minimize load chattering that helps in stabilizing the dc-bus. In addition, this architecture uses standard dc/dc converters for a low-cost, modular, Plug and Play ( PnP ) solution with highly automated operation, enabling local assembly, operation, and maintenance by non-technical personnel. The proposed SONG concept was validated in simulation and with a 700W, laboratory-scale, custom made nano grid system. The simulation and experimental test cases show the feasibility of the SONG system by demonstrating the proposed multi-source, multi-segment droop control strategy without load chattering under varying operating conditions.

dc-dc converter↗

DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems

This article develops a deep graph operator network (DeepGraphONet) framework that learns to approximate the dynamics of a complex system (e.g., the power grid or traffic) with an underlying subgraph structure. Here, we build our DeepGraphONet by fusing the ability of graph neural networks to exploit spatially correlated graph information and deep operator networks to approximate the solution operator of dynamical systems. The resulting DeepGraphONet can then predict the dynamics within a given short/medium-term time horizon by observing a finite history of the graph state information. Furthermore, we design our DeepGraphONet to be resolution independent. That is, we do not require the finite history to be collected at the exact/same resolution. In addition, to disseminate the results from a trained DeepGraphONet, we design a zero-shot learning strategy that enables using it on a different subgraph. Finally, empirical results on the transient stability prediction problem of power grids and traffic flow forecasting problem of a vehicular system illustrate the effectiveness of the proposed DeepGraphONet.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Intelligent Robotic Systems Study (IRSS), phase 3

This phase of the Intelligent Robotic Systems Study (IRSS) examines some basic dynamics and control issues for a space manipulator attached to its worksite through a compliant base. One example of this scenario is depicted, which is a simplified, planar representation of the Flight Telerobotic Servicer (FTS) Development Test Flight 2 (DTF-2) experiment. The system consists of 4 major components: (1) dual FTS arms to perform dextrous tasks; (2) the main body to house power and electronics; (3) an Attachment Stabilization and Positioning Subsystem (ASPS) to provide coarse positioning and stabilization of the arms, and (4) the Worksite Attachment Mechanism (WAM) which anchors the system to its worksite, such as a Space Station truss node or Shuttle bay platform. The analysis is limited to the DTF-2 scenario. The goal is to understand the basic interaction dynamics between the arm, the positioner and/or stabilizer, and the worksite. The dynamics and controls simulation model are described. Analysis and simulation results are presented.

Source record↗

AI-Based Faster-Than-Real-Time Stability Assessment of Large Power Systems with Applications on WECC System

Achieving clean energy goals will require significant advances in regard to addressing the computational needs for next-generation renewable-dominated power grids. One critical obstacle that lies in the way of transitioning today’s power grid to a renewable-dominated power grid is the lack of a faster-than-real-time stability assessment technology for operating a fast-changing power grid. This paper proposes an artificial intelligence (AI) -based method that predicts the system’s stability margin information (e.g., the frequency nadir in the frequency stability assessment and the critical clearing time (CCT) value in the transient stability assessment) directly from the system operating conditions without performing the conventional time-consuming time-domain simulations over detailed dynamic models. Since the AI method shifts the majority of the computational burden to offline training, the online evaluation is extremely fast. This paper has tested the AI-based stability assessment method using multiple dispatch cases that are converted and tuned from actual dispatch cases of the Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. The results show that the AI-based method could accurately predict the stability margin of such a large power system in less than 0.2 milliseconds using the offline-trained AI agent. Therefore, the proposed method has great potential to achieve faster-than-real-time stability assessment for practical large power systems while preserving sufficient accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dynamic Validation of CNN-Based Surrogate Models for Inverter-Based Resources in Open-Source Solvers

Traditionally, distribution system planning has focused on steady-state analyses, with limited consideration of dynamic behavior. However, as large or medium-scale inverter-based resources (IBRs), particularly grid-following (GFL) inverters in commercial or industry buildings, become more prevalent, understanding their dynamic impact is essential for grid planning and operation. This article presents an innovative deep-learning (DL)-approach using convolutional neural networks technique to model the GFL inverters. Developed from real grid-tied commercial IBR transient data, these dynamic DL models overcome proprietary constraints by requiring minimal knowledge of internal converter physics while maintaining high accuracy and flexibility. To demonstrate their applicability, the models were incorporated into GridLAB-D, an open-source, three-phase distribution analysis tool. This integration enables dynamic simulations of large-scale distribution networks with high IBR penetration stability analysis. Rigorous testing and validation, aligned with industry standards, confirmed the reliability and efficiency of this approach, paving the way for enhanced planning and operational assessments of modern power systems.

Deep-learning↗

Temperature and Dynamic Strain Measurements Using a Single SAWR Sensor

Dynamic strain sensing is relevant in numerous applications involving structural health monitoring, condition-based maintenance, operation efficiency preservation, and work environment safety. These sensors are particularly critical for high-temperature (HT) harsh-environment (HE) industries such as aerospace, automotive, power plants, and advanced manufacturing. In HT/HE, sensor implementation and measurement present challenges such as maintaining sensor stability, accounting for temperature cross-sensitivity, providing HT attachment, and packaging of the sensors and system. Surface acoustic wave resonator (SAWR) sensors can address these needs and offer additional benefits such as compact size and wireless interrogation capability. The SAWR sensitivity to dynamic strain is temperature dependent, making it necessary to measure the sensor temperature in order to use the correct dynamic strain calibration curve. In this work, a method for determining the temperature, dynamic strain magnitude, and dynamic strain spectral components using a single SAWR sensor is presented. Here, the established technique for determining operational temperature and dynamic strain magnitude/spectral components using only one SAWR simplifies the sensor measurement system, thus being very attractive for HT /HE applications.

47 OTHER INSTRUMENTATION↗

Integrated Power and Attitude Control System (IPACS)

Recent advances in materials, circuit integration and power switching have given the concept of dynamic energy and momentum storage important weight size, and operational advantages over the conventional momentum wheel-battery configuration. Simultaneous momentum and energy storage for a three axes stabilized spacecraft can be accomplished with a topology of at least four wheels where energy (a scalar) is stored or retrieved in such a manner as to keep the momentum vector invariant. This study, instead, considers the case of two counter-rotating wheels in one axis to more effectively portray the principles involved. General scalable system design equations are derived which demonstrate the role of momentum storage when combined with energy storage.

Michaelis, Theodore D.↗

Stabilizing Inverter-Based Transmission Systems: Power Hardware-in-the-Loop Experiments with a Megawatt-Scale Grid-Forming Inverter

This article presents what the authors believe to be the first experimental verification of the ability of grid-forming (GFM) inverters to stabilize a transmission electric power system that is otherwise unstable. The experiments described here were performed using power hardware-in-the-loop (PHIL) simulation to connect a megawatt-scale battery inverter to a real-time electromagnetic transient (EMT) simulation of the near-future Maui power system. This allows the dynamic interactions between the inverter and the power system to be observed without putting the real power system at risk. The ability to use the actual inverter hardware removes the need to rely on a computer model approximation of the inverter's behavior.

electromagnetic transient simulations↗