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

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At least 361 records · Page 20

Holistic Small-Signal Stability Analysis for Large-Scale Inverter-Intensive Power Systems with Coupled and Full-Order Dynamics from Control Systems and Power Networks

The increasing penetration of inverter-based resources (IBRs) into the existing power systems introduces tremendous benefits for enhanced sustainability but also poses inevitable challenges in terms of insufficient inertia, potential instability, and complex network dynamics, among others. However, the additional coupling introduced by the interactions among gridfollowing (GFL) and grid-forming (GFM) IBRs and the other components (i.e., synchronous generators [SGs], loads, and network, etc.) has not been clearly explored. A holistic, scalable, and quantitative stability analysis framework with the control systems and power networks is still missing. Here, in this paper, to fill in the technical gaps, a holistic small-signal model of the entire system with both rotating generation units and IBRs is established. An extended power flow model with operation dynamics from both generator control schemes and power networks is proposed to provide the varying steady-state operating points for small-signal modeling. The proposed method is compared with MATLAB solvers, and the results show that the proposed approach has a minimum calculation time, which can be less than 12 seconds for a large-scale power system with up to 2,000 buses. Furthermore, a quantitative method is developed to identify the impacts of IBRs on system performance with emphases on the potential stability issues with GFL IBRs, additional benefits of employing GFM IBRs, the feasibility of replacing SGs with GFM IBRs, and the impact of penetration level of different kinds of generation units. Finally, a field island power system is used to verify the proposed approach, and hardware-in-the-loop (HIL) tests are provided to further demonstrate the effectiveness of the proposed analysis.

14 SOLAR ENERGY↗

Multi-level inverter with mixed device types

Provided is a novel multi-level inverter with mixed device types and methods of controlling same. This novel multi-level inverter topology and control method allows the use of high frequency switching devices for controlled PWM switching, while also using lower frequency switching devices for directional switches. This combination of high frequency PWM switching devices with low frequency directional switching devices allows a cost reduction without a significant performance degradation.

Mekonnen, Ezana T.↗

Multi-level inverter with mixed device types

Provided is a novel multi-level inverter with mixed device types and methods of controlling same. This novel multi-level inverter topology and control method allows the use of high frequency switching devices for controlled PWM switching, while also using lower frequency switching devices for directional switches. This combination of high frequency PWM switching devices with low frequency directional switching devices allows a cost reduction without a significant performance degradation.

Mekonnen, Ezana T.↗

Analysis and performance of paralleling circuits for modular inverter-converter systems

As part of a modular inverter-converter development program, control techniques were developed to provide load sharing among paralleled inverters or converters. An analysis of the requirements of paralleling circuits and a discussion of the circuits developed and their performance are included in this report. The current sharing was within 5.6 percent of rated-load current for the ac modules and 7.4 percent for the dc modules for an initial output voltage unbalance of 5 volts.

Birchenough, A. G.↗

Decentralized Voltage Control of Large-Scale Distribution System with PVs Based on MADRL

This paper proposes a model-free decentralized control framework for the voltage regulation of large-scale distribution systems through the coordinated control of PV inverters. This is achieved by developing a novel interaction mechanism between the surrogate model and the centralized training and decentralized execution multiagent deep reinforcement learning framework. Specifically, the sparse Gaussian processes regression method is first utilized to develop the surrogate model of the original distribution system for reward calculation during the training stage, where each agent represents a sub-region in the centralized fashion for coordination strategy learning. After that, the learned control rules are used to inform controllers within each sub-region for real-time decisions with only local measurements. Comparative tests among various methods on the EPRI Ckt5 test system demonstrate the effectiveness of the proposed method.

distribution system↗

Customized open source renewable energy models validated through PHIL lab experiments

Energy models for power systems require ongoing updates to reflect advancements in equipment technology and the increasing complexity of power electronic devices. This study utilizes a Power Hardware-in-the-Loop (PHIL) experimental setup to validate custom photovoltaic (PV) inverter models, aiming to enhance and expedite the development of advanced renewable energy models. The research compares the performance of a physical inverter with generic Renewable Energy Source (RES) models recommended by the Western Electricity Coordinating Council (WECC). As inverter-based renewable energy sources become more prevalent in modern electrical grids, it is crucial that dynamic models accurately represent their real-world behavior. Accurate models improve our understanding of these energy resources and their interactions with the grid. The proposed model enhancements are designed to better reflect real inverter performance, based on insights from PHIL experiments. These models are developed using the open source Modelica language and the OpenIPSL Modelica Library, allowing integration across various simulation tools without re-implementation. The paper concludes with a thorough assessment, comparing the enhanced models with PHIL experiments on a real PV inverter in a controlled laboratory setting. As a result, the study provides the enhanced WECC RES models and validation data as open source resources, facilitating further research and development.

Modelica↗

Integrated-Circuit Controller For Brushless dc Motor

Generic circuit performs commutation-logic and power-switching functions for control of brushless dc motor. Controller includes commutation-logic and associated control circuitry, power supply, and inverters containing power transistors. Major advantages of controller are size, weight, and power consumption can be made less than other brushless-dc-motor controllers.

Le, Dong Tuan↗

Studying the Impact of IBR Modeling on the Commonly Applied Transmission Line Protective Elements

It is a well-accepted fact that detailed inverter-based resource (IBR) models are needed for electromagnetic transient (EMT) studies, especially for protection studies and protection designs. However, it is not clear which modeling aspects should be included in the EMT model to accurately represent the IBR fault responses. Therefore, this paper addresses this gap by evaluating the impact of key modeling aspects (DC source, inverter model, power control, current/voltage control, and current limiting) on the response of protective relay elements both qualitatively and quantitatively. Both grid-following (GFL) and grid-forming (GFM) IBR models are comprehensively evaluated through a simplified real-world transmission network by varying the IBR modeling aspects, fault locations, and types. The insights and findings from this paper will benefit the power system protection community because this work provides modeling requirements and guidelines for IBR modeling so that correct IBR models will be used for protection scheme settings design.

grid-following inverter↗

Improved transistorized AC motor controller for battery powered urban electric passenger vehicles

An ac motor controller for an induction motor electric vehicle drive system was designed, fabricated, tested, evaluated, and cost analyzed. A vehicle performance analysis was done to establish the vehicle tractive effort-speed requirements. These requirements were then converted into a set of ac motor and ac controller requirements. The power inverter is a three-phase bridge using power Darlington transistors. The induction motor was optimized for use with an inverter power source. The drive system has a constant torque output to base motor speed and a constant horsepower output to maximum speed. A gear shifting transmission is not required. The ac controller was scaled from the base 20 hp (41 hp peak) at 108 volts dec to an expanded horsepower and battery voltage range. Motor reversal was accomplished by electronic reversal of the inverter phase sequence. The ac controller can also be used as a boost chopper battery charger. The drive system was tested on a dynamometer and results are presented. The current-controlled pulse width modulation control scheme yielded improved motor current waveforms. The ac controller favors a higher system voltage.

Peak, S. C.↗

An Inner-Loop Control Method for the Filter-less, Voltage Sensor-less, and PLL-less Grid-Following Inverter-Based Resource

This paper presents a novel inner-loop control method for the inverter-based resource (IBR). The innovative concepts include removing the voltage sensors at the point of common coupling (PCC), removing the inverter interface inductance, and removing the traditional phase-locked loop (PLL) circuits. Simulation is conducted to verify the feasibility of the method. Furthermore, the virtual impedance is applied to the control loop to improve the current THD and dynamics. Compared to the traditional control, the proposed one helps offload the system by reducing the bulky inductors and voltage sensors without compromising the control performance.

grid-forming inverter, inner-loop control, filterl↗

Grey-Box System Identification of Grid-Forming Inverters

This paper demonstrates the use of grey-box system identification methods for simplifying and understanding the nonlinear power dynamics of grid-forming inverters (GFMs). The power and frequency outputs of complex high-order GFM models are fed into system identification software in order to fit them to a predetermined LTI system and learn system parameters such as (synthetic) inertia and droop constants. The same process is then run for a high-order synchronous generator model, and the outputs are fit to the same set of LTI equations. Simulation of a network of GFM inverters with diverse control architecture is also performed for the same process. The intent is threefold: first, to demonstrate the appropriateness of unified LTI models for describing the power and frequency dynamics of individual resources and connected networks, in order to facilitate analysis of larger heterogeneous networked systems; second, to discover the relationship between internal control parameters of GFMs and their externally observed values; and third, to validate that grey-box data-driven system identification techniques can be a valuable tool to discover the values of important parameters in the absence of explicit vendor models.

analytical models↗

Gray-Box Modeling for Distribution Systems With Inverter-Based Resources: Integrating Physics-Based and Data-Driven Approaches

Here, in this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation accuracy by taking advantages of both physics-based (white-box) and data-driven (black-box) modeling approaches. To this end, we utilize partial physical knowledge of the system, including the inverters’ structures and control diagrams, as well as the equivalent network model simplified through Kron reduction. The white-box model containing unknown parameters is then constructed with mathematical equations and an optimization-based method is subsequently employed to identify these unknown parameters within the white-box model. Next, the graybox modeling framework is then constructed by embedding the output variables of the white-box model into the input vector of a black-box model (represented using a neural network). Finally, the black-box section is trained using the collected input-output datasets and the gray-box model is then obtained. Furthermore, case studies demonstrate that our gray-box modeling approach effectively improves estimation accuracy compared to purely physics-based or data-driven methods.

42 ENGINEERING↗

Aggregation of Inverter-Based Resources for Modeling and Simulation

In order to conduct system dynamic studies, it is necessary to have dynamic models of both inverter and plant levels. Detailed and aggregated modeling approaches are two essential options. The detailed modeling method involves capturing the dynamic characteristics of each individual device (e.g., wind turbine or PV array), as well as their interconnections. However, as the scale of the IBR plant increases, the complexity and computation time required for detailed modeling also increase. On the other hand, aggregated modeling offers a more efficient way of representing large-scale IBRs in power system dynamic studies. This approach involves aggregating a large number of wind turbines, PV arrays, inverters, and/or plant controllers into one or a smaller number of equivalent models. In order to analyze the impact of a high-level IBR penetration in power systems, it is important to develop accurate and computationally efficient models for both the detailed and aggregated methods.

14 SOLAR ENERGY↗

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A series-resonant silicon-controlled-rectifier power processor for ion thrusters

A program to develop a power processing system for ion thrusters is presented. Basic operation of the silicon controlled rectifier series inverter circuitry is examined. The approach for synthesizing such circuits into a system which limits the electrical stress levels on the power source, semiconductor switching elements, and the ion thruster load is described. Experimental results are presented for a 2.5-kW breadboard system designed to operate a 20-cm ion thruster.

Shumaker, H. A.↗

Neutron, gamma ray, and temperature effects on the electrical characteristics of thyristors

Experimental data showing the effects of neutrons, gamma rays, and temperature on the electrical and switching characteristics of phase-control and inverter-type SCR's are presented. The special test fixture built for mounting, heating, and instrumenting the test devices is described. Four SCR's were neutron irradiated at 300 K and four at 365 K for fluences up to 3.2 x 10 exp 13 n/sq. cm, and eight were gamma irradiated at 300 K only for gamma doses up to 5.1 Mrads. The electrical measurements were made during irradiation and the switching measurements were made only before and after irradiation. Radiation induced crystal defects, resulting primarily from fast neutrons, caused the reduction of minority carrier lifetime through the generation of R-G centers. The reduction in lifetime caused increases in the on-state voltage drop and in the reverse and forward leakage currents, and decreases in the turn-off time.

Frasca, A. J.↗

Neutron, gamma ray, and temperature effects on the electrical characteristics of thyristors

Experimental data showing the effects of neutrons, gamma rays, and temperature on the electrical and switching characteristics of phase-control and inverter-type SCR's are presented. The special test fixture built for mounting, heating, and instrumenting the test devices is described. Four SCR's were neutron irradiated at 300 K and four at 365 K for fluences up to 3.2 x 10 exp 13 pn/sq. cm, and eight were gamma irradiated at 300 K only for gamma doses up to 5.1 Mrads. The electrical measurements were made during irradiation and the switching measurements were made only before and after irradiation. Radiation induced crystal defects, resulting primarily from fast neutrons, caused the reduction of minority carrier lifetime through the generation of R-G centers. The reduction in lifetime caused increases in the on-state voltage drop and in the reverse and forward leakage currents, and decreases in the turn-off time.

Frasca, A. J.↗

Amyloplasts that sediment in protonemata of the moss Ceratodon purpureus are nonrandomly distributed in microgravity

Little is known about whether or how plant cells regulate the position of heavy organelles that sediment toward gravity. Dark-grown protonemata of the moss Ceratodon purpureus displays a complex plastid zonation in that only some amyloplasts sediment along the length of the tip cell. If gravity is the major force determining the position of amyloplasts that sediment, then these plastids should be randomly distributed in space. Instead, amyloplasts were clustered in the subapical region in microgravity. Cells rotated on a clinostat on earth had a roughly similar non-random plastid distribution. Subapical clusters were also found in ground controls that were inverted and kept stationary, but the distribution profile differed considerably due to amyloplast sedimentation. These findings indicate the existence of as yet unknown endogenous forces and mechanisms that influence amyloplast position and that are normally masked in stationary cells grown on earth. It is hypothesized that a microtubule-based mechanism normally compensates for g-induced drag while still allowing for regulated amyloplast sedimentation.

Non-NASA Center↗