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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Region-Based Stability Analysis of Resilient Distribution Systems with Hybrid Grid-Forming and Grid-Following Inverters

In this paper, distribution system stability considering mixed grid-forming (GFM) and grid-following (GFL) inverters is discussed. A holistic small-signal model of the distribution feeder accommodating both GFM and GFL inverters is derived. In contrast to conventional point-by-point stability analysis, a region-based stability assessment approach is proposed and implemented to evaluate small-signal system stability with both GFM and GFL controls. Furthermore, to enhance the computational efficiency, an Artificial Intelligence (AI) assisted Kernel Ridge Regression (KRR) approach is developed to obtain the stability region boundary. Therefore, with the derived stability region, the impact of critical parameters on system stability is intuitively shown, and more importantly, the relationship between the maximum penetration level and the corresponding feasible range of the selected control parameters can be quantified. The proposed approach has been validated using MATLAB/Simulink.

grid-following↗
DOE OSTI2021

TPCPF: Three-Phase Continuation Power Flow Tool for Voltage Stability Assessment of Distribution Networks With Distributed Energy Resources

This article presents a three-phase unbalanced continuation power flow algorithm for voltage stability assessment of distribution systems with high penetration of distributed energy resources (DERs). Analyzing distribution system voltage stability with DER will allow high penetration of renewable energy necessary for the sustainability goals. The developed algorithm can analyze voltage stability for both the meshed and radial systems and the balanced and unbalanced three-phase distribution systems. The developed tool allows the voltage stability analysis to facilitate the planning, operation, control, and distribution system management. The impact of DER on the voltage stability of several test cases has been analyzed considering constant power (P Q) and regulated-voltage (P V ) modes of operation for DER units. Moreover, different voltage stability case studies are presented to demonstrate the impact of unbalance, load increment, and network topology on the maximum loading capacity. Finally, results using the IEEE 13-node feeder, the 18-bus balanced shipboard system, the 13-node CIGRE benchmark system, and the 136-bus redial distribution feeder demonstrate that the developed continuation power flow tool can efficiently perform voltage stability analysis for active distribution systems.

42 ENGINEERING↗
DOE OSTI2025

AutoFocus: AI/ML-driven real-time wavefront diagnostics to autonomously align and optimize X-ray optics

We present an integrated system that combines advanced wavefront diagnostics with artificial intelligence (AI) to automate and optimize X-ray optics at synchrotron beamlines. This system couples real-time wavefront sensing with AI-driven control algorithms to achieve precise beam alignment, stabilization, and performance optimization. A key feature is the use of multi-fidelity transfer learning, which enables knowledge gained from both real-world beamline optimizations and ultra-realistic digital twin simulations to be effectively applied to in situ optimization. By leveraging multi-objective bayesian optimization, the system continuously refines its performance, reducing optimization time and minimizing the need for manual adjustments. Designed for seamless deployment, it operates with existing beamline hardware and provides an intuitive graphical interface. Initial deployments at the advanced photon source beamlines have demonstrated its ability to enhance beam stability, improve reproducibility, and significantly streamline alignment procedures. This AI-enhanced control framework represents a significant step toward fully autonomous beamline operation in next-generation synchrotron facilities.

Rebuffi, Luca [Argonne National Laboratory (ANL), ↗
DOE OSTI2022

Learning Stochastic Parametric Differentiable Predictive Control Policies

We present a scalable unsupervised learning-based method for obtaining explicit control policies for model predictive control problems for stochastic linear systems with additive uncertainties subject to nonlinear chance constraints. We call the proposed method stochastic parametric differentiable predictive control (SP-DPC), which extends the recently proposed deterministic DPC policy optimization algorithm. We formulate the SP-DPC as a deterministic approximation to the stochastic parametric constrained optimal control problem via independent sampling of the problem's parameters and uncertainties. This formulation allows us to directly compute the policy gradients via automatic differentiation of the problem's value function, evaluated over sampled parameters and uncertainties. In particular, the computed expectation of the problem's value function is backpropagated through the finite-time closed-loop system rollouts parametrized by a known nominal system dynamics model and neural control policy. We also provide theoretical probabilistic guarantees on closed-loop stability and chance constraints satisfaction for systems controlled by learned neural policies. We demonstrate the computational efficiency and scalability of the proposed policy optimization algorithm in three numerical examples, including systems with a large number of states or subject to nonlinear constraints.

Drgona, Jan↗
DOE OSTI2023

Inter-Area Oscillation Damping with Type-5 Wind Power Plant: Preprint

This paper investigates the potential of using brushless excitation (BLE) for not only riding through the fault but also to damp inter-area power oscillation with the help of a synchronous generator (SG) used in Type 5 Wind Power Plant (WPP). In BLE, an auxiliary synchronous generator (ASG) behaving like an exciter is coupled and driven by the rotor of the main SG. The BLE's field current's ASG is fed by two separate loops of the automatic voltage regulator (AVR) and Power System Stabilizer (PSS). The AVR system implements a control loop to regulate the generator terminal voltage, VT. For the PSS, the kinetic energy of the wind turbine is utilized according to the estimated rotational speed of the synchronous generator shaft of the SG. It mitigates the necessity of any curtailment of active power for damping. The effectiveness of the proposed control scheme is verified with a three-phase short circuit fault in a two-area power system.

brushless↗
DOE OSTI2021

Stabilizing the Power System in 2035 and Beyond: Evolving from Grid-Following to Grid-Forming Distributed Inverter Controllers (Final Technical Report)

Under existing grid operations, large synchronous generators provide sufficient rotational inertia to form a rigid backbone for the bulk power system. With photovoltaics (PV) forecasted to provide more than 600 GW of generation by 2050 under the U.S. Department of Energy’s SunShot Initiative objectives, however, it is clear that power electronic inverters will play a dominant role in future systems, and low-inertia stability must be ensured to maintain system reliability. Today, the risks to system stability can be observed on geographically small islands, such as Hawaii, which contain a relatively large amount of installed PV. These risks stem from a fundamental shortcoming of contemporary control strategies—existing inverter controllers cannot guarantee grid stability. Given that future power systems driven by sustainable resources will be characterized by low inertia, locations such as Hawaii provide a glimpse into the obstacles facing future power systems. Considering these challenges, the aim of this project was to develop and demonstrate distributed inverter controllers that enable the reliable control of low-inertia power systems with hundreds of gigawatts of integrated PV.

14 SOLAR ENERGY↗
DOE OSTI2022

A Lyapunov-Based Generalized Dc-Side Controller Design for PV-Connected Systems

The objective of this paper is to realize a universal dc-side controller for photovoltaic (PV) systems where the control is agnostic to the downstream converter configuration. To achieve this, the downstream power converter and its controls are manipulated into an effective power control loop that is then cast into a generalized multi-loop design framework. On the dc side, a nonlinear small-signal model of the PV input is realized exclusively in terms of PV datasheet parameters (i.e., open-circuit voltage, short-circuit current, and maximum power point). Finally, a linear controller is used to modulate the dc-side PV system with the generic downstream power controller. A Lyapunov candidate is proposed to analyze the stability of the interconnected system and provide a streamlined approach for the controller design. The proposed design is validated on a 1k VA experimental setup that interfaces a PV module to the grid.

generalized PV controller↗
DOE OSTI2023

ATRP Enhances Structural Correlations In Polymerization–Induced Phase Separation**

Synthetic methods to control the structure of materials at sub–micron scales are typically based on the self–assembly of structural building blocks with precise size and morphology. On the other hand, many living systems can generate structure across a broad range of length scales in one step directly from macromolecules, using phase separation. Here, we introduce and control structure at the nano– and microscales through polymerization in the solid state, which has the unusual capability of both triggering and arresting phase separation. In particular, we show that atom transfer radical polymerization (ATRP) enables control of nucleation, growth, and stabilization of phase–separated poly–methylmethacrylate (PMMA) domains in a solid polystyrene (PS) matrix. ATRP yields durable nanostructures with low size dispersity and high degrees of structural correlations. Furthermore, we demonstrate that the length scale of these materials is controlled by the synthesis parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Bridging 20 Years of Soil Organic Matter Frameworks: Empirical Support, Model Representation, and Next Steps

Abstract In the past few decades, there has been an evolution in our understanding of soil organic matter (SOM) dynamics from one of inherent biochemical recalcitrance to one deriving from plant‐microbe‐mineral interactions. This shift in understanding has been driven, in part, by influential conceptual frameworks which put forth hypotheses about SOM dynamics. Here, we summarize several focal conceptual frameworks and derive from them six controls related to SOM formation, (de)stabilization, and loss. These include: (a) physical inaccessibility; (b) organo‐mineral and ‐metal stabilization; (c) biodegradability of plant inputs; (d) abiotic environmental factors; (e) biochemical reactivity and diversity; and (f) microbial physiology and morphology. We then review the empirical evidence for these controls, their model representation, and outstanding knowledge gaps. We find relatively strong empirical support and model representation of abiotic environmental factors but disparities between data and models for biochemical reactivity and diversity, organo‐mineral and ‐metal stabilization, and biodegradability of plant inputs, particularly with respect to SOM destabilization for the latter two controls. More empirical research on physical inaccessibility and microbial physiology and morphology is needed to deepen our understanding of these critical SOM controls and improve their model representation. The SOM controls are highly interactive and also present some inconsistencies which may be reconciled by considering methodological limitations or temporal and spatial variation. Future conceptual frameworks must simultaneously refine our understanding of these six SOM controls at various spatial and temporal scales and within a hierarchical structure, while incorporating emerging insights. This will advance our ability to accurately predict SOM dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Topology property analysis and application of stable time-delay regions for linear multiple time-delay systems

This study examines the relationship between the topology of stable time-delay regions and the stability analysis of an linear multiple time delay system. To analyze the topology of stable time-delay regions, we construct a function with a value equal to zero for the time-delay points on the boundaries of stable time-delay regions. The function is continuous and differentiable in the whole defining field with a global minimum of zero so that we can locate the boundaries by minimizing the value of the function. Based on the topology analysis, we proposed a performance validation approach for controllers that are designed to stabilize the system using feedback signals with time delays. The method based on the topology analysis is simple and reliable so that can deal with a linear time-invariant system with high order and multiple time delays (more than 3). The example case study shows that the above method is reliable and enables ultra-low latency coordination and control for the future power grid with ubiquitous power electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Large moments in BCC FExCOyMNz and other alloy thin films

Large magnetic moment compositions are formed by stabilizing ternary or other alloys with a epitaxial control layer. Compositions that are unstable in bulk specimen are thus stabilized and exhibit magnetic moments that are greater that a Slater-Pauling limit. In one example, FexCoyMnz layers are produced on an MgO(001) substrate with an MgO surface serving to control the structure of the FexCoyMnz layers. Magnetizations greater than 3 Bohr magnetons are produced.

Snow, Ryan L.↗
DOE OSTI2020

IEEE 1547-2018 Based Interoperable PV Inverter with Advanced Grid-Support Functions

Grid integration of photovoltaic (PV) inverters has been increasing in the past decade. As a result of the uncertainties introduced with high penetrations of PV, better monitoring and control of the PV inverters becomes crucial for improving overall system stability. This paper focuses on the communications capability of the inverter controller and on enabling interoperability. Multiple standards are available to enable interoperability in PV inverters. In this paper, an interoperable controller, enabled by Distributed Network Protocol 3 (DNP3) communications protocols, is developed for a grid-connected, three-phase PV inverter. The DNP3 server for the PV inverter is programmed on the real-time layer of the field-programmable gate array (FPGA)-based inverter controller. Set points for advanced inverter control functions, such as volt/VAr curves, ride-through curves, are sent from a DNP3 client, a simulated distribution management system application, to the PV inverter through DNP3. This communications capability of the inverter controller is validated using a controller-hardware-in-the-loop experimental setup. The code developed to achieve the interoperability is available in the public domain through open-source software licensing. This interoperability will enable smoother grid integration of smart PV inverters with advanced grid-support functions as well as allow better monitoring and control of PV inverters for grid stability.

14 SOLAR ENERGY↗
DOE OSTI2021

Data-Driven Adaptive Damping Controller for Wind Power Plants with Doubly-Fed Induction Generators

This paper presents an adaptive damping controller for wind power plants in which the turbines are equipped with doubly-fed induction generators. The controller is designed to respond to an input control signal that is triggered according to the system operating conditions. A processing unit continuously estimates the electromechanical modes of oscillation based on real-time streaming data acquired from a phasor measurement unit that is strategically positioned on the grid. The decision to trigger (or not trigger) the control signal is automatic, based on the relative damping of the dominant mode. The modes are estimated using the dynamic mode decomposition algorithm with time-delay embedding. Numerical simulations performed on the two-area system demonstrate that the proposed controller enhances the rotor angle stability for both small-signal and large disturbances, and is adaptive to changing grid conditions.

damping controller↗
DOE OSTI2025

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon↗
DOE OSTI2022

Small-Signal Stability Support from Dynamically Configurable Grid-Forming/Following Inverters for Distribution Systems: Preprint

As the penetration of inverter-based resources (IBRs) continues to increase in modern power systems, system stability is challenged by the insufficient inertia induced by IBRs; hence, there is a need to develop various methods to address the potential instabilities. In this paper, grid-forming (GFM) and grid-following (GFL) controls are implemented for inverters with flexible-mode transitions between them. The operation mode transition between GFM and GFL controls is adopted as an additional degree of control flexibility to adjust the small signal stability margin. Further, a holistic and detailed small signal model of the entire system with the dynamics from both synchronous generators (SGs) and IBRs is derived. The effectiveness of the proposed work in adjusting the system small signal stability margin is validated by conducting case studies with varying penetration levels of IBRs. A test system with one SG and five inverters was implemented in MATLAB/Simulink to demonstrate the effectiveness of the proposed approach. Index Terms - grid-following control, grid-forming control, operation mode transition, small-signal stability analysis

grid-following control↗
DOE OSTI2021

Nonlinear Multiple Models Adaptive Secondary Voltage Control of Microgrids

This article proposes a model-free secondary voltage control (SVC) for microgrids (MG) using nonlinear multiple models adaptive control. Firstly, a linear robust adaptive controller is designed to guarantee the voltage stability in the bounded-input- bounded-output (BIBO) manner so as to meet the operation requirements of MGs. Secondly, a nonlinear adaptive controller is developed to improve the voltage tracking performance with the help of artificial neural networks (ANNs). A switching mechanism for coordinating such two controllers is designed to guarantee the closed-loop stability while achieving accurate voltage tracking. Here, by an online identification based on the input and output data of MGs, the proposed method does not resort to any apriori information of system model and primary control, thus exhibiting good robustness, ease of deployment and disturbance rejection.

17 WIND ENERGY↗
DOE OSTI2024

Wideband Impedance Passivation of MMCs for Suppressing Harmonic Oscillations

Harmonic instability and associated oscillation events have become one of the main concerns in MMC-based HVdc systems. These oscillations can appear in the range from a few hundred hertz to several kilohertz, and the root cause is identified as delay-induced negative damping of MMC impedance appearing at the system resonance frequency. Here, this paper introduces a wideband impedance reshaping method through MMC control to eliminate such negative damping for both grid-following (GFL) and grid-forming (GFM) MMCs, which makes the MMC impedance completely passive from the second harmonic frequency upward, thus preventing all harmonic oscillations. First, simplified impedance models of MMCs are derived for the harmonic stability analysis and the impedance reshaping control design. Next, a passivity-based impedance reshaping method is presented, as well as practical considerations for its implementation. In addition, to maintain the MMC's disturbance ride-through capability, an adaptive activation scheme is developed, which enables the wideband impedance reshaping control only in the presence of harmonic oscillation events. The effectiveness of the proposed method is validated by frequency domain analysis and by electromagnetic transient (EMT) simulations of two typical MMC-based power systems.

17 WIND ENERGY↗
DOE OSTI2024

Inverter Intensive Hybrid Power Plant Modeling with Small-Signal Stability Augmentation through Flexible Operation Mode Transition

Hybrid power plants (HPPs) prompt the penetration of inverter-based renewable energy sources (RES) in transmission systems; however, given their low-inertia nature, HPPs are dominated by power electronic inverters, so there are inevitable challenges in system stability when increasing numbers of HPPs are integrated into the modern power grids. To boost the penetration level of HPPs without jeopardizing system stability, it is desirable to equip them with operational characteristics (i.e., grid-forming capabilities) that are comparable to those of conventional power plants dominated by synchronous generators (SGs). In this paper, a holistic model of inverter intensive HPP is derived and a bi-level hierarchical control is developed to allow HPPs to flexibly switch among the designed operation modes (i.e., P-Q, P-V, and isochronous modes). Compared to SGs, which have limited controllability, the operation mode of each HPP could vary as requested. Such flexible mode transitions could be integrated into the secondary plant-level control and be leveraged as an additional control degree to further augment system stability. Further, the system small-signal stability margin is quantified with varying HPP operation modes. More importantly, modal analysis is thereby conducted to quantify the impacts of mode transition on the system oscillatory modes. The effectiveness of the proposed HPP bi-level hierarchical control is verified using extensive case studies based on the simplified real-world island power grid, and the results validate that the system small-signal stability margin can be enhanced with the additional degree of control flexibility enabled by HPP operation mode transition. The real-time hardware-in-the-loop (HIL) results are also provided to verify the proposed method.

grid-forming control↗