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DOE OSTI2025

A Comprehensive Study of the Impact of Inverter-Based Resource (IBR) Modeling and Control on Protection Relay Elements

Inverter-based resources (IBRs) exhibit fault responses that differ significantly from those of synchronous generators, which can challenge the reliable operation of many commonly used power system protection elements. The fault response of IBRs is primarily influenced by their control algorithms and configurations, but the impact of these controls on protection relays is not yet fully understood. This presentation provides a comprehensive study of how IBR modeling and controls affect transmission line protection. Key modeling and control aspects include the DC source, inverter model, power level control, current control, and current limiting. The study reveals that certain aspects - such as the type of DC source (battery, PV, or hybrid), inverter model (average vs. switching), and power level control methods (PQ dispatch vs. Vdc-Vac control for grid-following IBRs, and droop vs. VSM for grid-forming IBRs) - do not significantly affect relay response. However, faster control loops, such as current control and current limiting, do influence the relay behavior. Additionally, the study explores the effects of other factors, including momentary cessation, operating points, fast/slow current responses, and grid strength on relay performance. Finally, the study offers recommendations for both IBR and protection engineers to improve IBR fault response and enhance the reliability of protection systems.

14 SOLAR ENERGY↗

DOE OSTI2026

Frequency Control and Dynamics (Part 1) [Slides]

This presentation provides an introductory overview of system dynamics and frequency control in electric power systems, with a focus on concepts relevant to small and interconnected grids such as those in Malawi. It explains foundational principles of AC system frequency, the relationship between generation-demand balance and frequency deviations, and the operational limits of generators and end-use equipment. The deck discusses frequency stability within broader system stability classifications and illustrates how inertia and turbine-governor dynamics shape system response to disturbances. It then outlines the tiered approach to frequency control - primary, secondary, and tertiary - detailing the roles, characteristics, timescales, and response mechanisms of each. Special emphasis is placed on hydro and thermal unit behavior, area control error (ACE), automatic generation control (AGC), and the operational implications of interconnecting small systems with larger grids. The material was developed to support Malawi's electricity sector and the establishment of the Southern Africa Battery Energy Storage Center of Excellence (SABESS CoE).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Frequency Control and Dynamics (Part 2) [Slides]

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Soil gas probes for monitoring trace gas messengers of microbial activity

Abstract Soil microbes vigorously produce and consume gases that reflect active soil biogeochemical processes. Soil gas measurements are therefore a powerful tool to monitor microbial activity. Yet, the majority of soil gases lack non-disruptive subsurface measurement methods at spatiotemporal scales relevant to microbial processes and soil structure. To address this need, we developed a soil gas sampling system that uses novel diffusive soil probes and sample transfer approaches for high-resolution sampling from discrete subsurface regions. Probe sampling requires transferring soil gas samples to above-ground gas analyzers where concentrations and isotopologues are measured. Obtaining representative soil gas samples has historically required balancing disruption to soil gas composition with measurement frequency and analyzer volume demand. These considerations have limited attempts to quantify trace gas spatial concentration gradients and heterogeneity at scales relevant to the soil microbiome. Here, we describe our new flexible diffusive probe sampling system integrated with a modified, reduced volume trace gas analyzer and demonstrate its application for subsurface monitoring of biogeochemical cycling of nitrous oxide (N 2 O) and its site-specific isotopologues, methane, carbon dioxide, and nitric oxide in controlled soil columns. The sampling system observed reproducible responses of soil gas concentrations to manipulations of soil nutrients and redox state, providing a new window into the microbial response to these key environmental forcings. Using site-specific N 2 O isotopologues as indicators of microbial processes, we constrain the dynamics of in situ microbial activity. Unlocking trace gas messengers of microbial activity will complement -omics approaches, challenge subsurface models, and improve understanding of soil heterogeneity to disentangle interactive processes in the subsurface biome.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

DOE OSTI2021

NFD Methodology Report

The NetFlow Dynamics (NFD) model was developed for estimating the availability of a commodity supplied by a national- or regional-scale infrastructure following unexpected disruption of one or more of its components. The large scope of the disruptions of interest produce changes in availability lasting days to weeks. Consequently, the model does not resolve daily variations in system state and does not include the long-term processes that cause infrastructures to evolve as assets are added and removed according to owners ’planning decisions. NFD simulates fluid flow, including petroleum and other incompressible fluids, as well as natural gas and other compressible fluids, through pipeline networks characterized by limits on transmission capacity and storage. It was designed to enable efficient exploration of possible transmission system responses to large-scale disruptions lasting for days or longer. The model formulation reflects constraints on transmission and storage capacity imposed by the physical system assets. Those capacity limits are input parameters and are not derived from more basic system properties such as pipeline diameters and compressor power. A system’s response to a large disruption is controlled by operational decisions as well as damage to physical assets. The NFD model formulation allows users to efficiently consider alternative scenarios about the way remaining capacity might be used so that the analysis result appropriately reflects uncertainties about operator response.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Quantum Memristors in Frequency-Entangled Optical Fields

A quantum memristor is a passive resistive circuit element with memory, engineered in a given quantum platform. It can be represented by a quantum system coupled to a dissipative environment, in which a system–bath coupling is mediated through a weak measurement scheme and classical feedback on the system. In quantum photonics, such a device can be designed from a beam splitter with tunable reflectivity, which is modified depending on the results of measurements in one of the outgoing beams. Here, we show that a similar implementation can be achieved with frequency-entangled optical fields and a frequency mixer that, working similarly to a beam splitter, produces state superpositions. We show that the characteristic hysteretic behavior of memristors can be reproduced when analyzing the response of the system with respect to the control, for different experimentally attainable states. Since memory effects in memristors can be exploited for classical and neuromorphic computation, the results presented in this work could be a building block for constructing quantum neural networks in quantum photonics, when scaling up.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Oxygen-responsive bacterial gene switch

The invention provided herein relates to sequence determinants that elicit certain levels of gene expression and methods for obtaining engineered ligand-responsive gene switches comprising these sequence determinants. More particularly, the invention provided herein relates to molecular building blocks (i.e., discrete nucleotide sequences), synthetic ligand-responsive gene switches comprising an assembly of these molecular building blocks, and methods of using synthetic ligand-responsive gene switches as customizable and controllable expression systems and sensors.

Kiley, Patricia J.↗

DOE OSTI2021

System and method for compact, adaptive optical sensor for obtaining areal images

The present disclosure relates to an imaging system which may make use of an electronic controller, a digital micromirror array, an aperture control system and a detector to image a desired scene. The digital micromirror array has a plurality of micromirror elements responsive to control signals generated by the electronic controller for electronically aiming the micromirror elements in a desired direction to image the desired area, and for receiving and reflecting light emanating from the desired area. The aperture control system receives light reflected from the digital micromirror array and passes a predetermined subportion of the received light therethrough. The detector is responsive to the predetermined subportion of light.

Panas, Robert Matthew↗

DOE OSTI2022

Cyber-Physical Dynamic System (CPDS) Modeling for Frequency Regulation and AGC Services of Distributed Energy Resources

The substantial integration of renewable energy brings significant challenges to balance the system in real time because of the variability and intermittency of renewable power. For the reliable system operation, the frequency regulation service is used to stabilize the system frequency through automatically balancing the system generation and load. On one hand, with the substantially increasing deployment of renewable energy in electricity system, the requirement of frequency regulation (FR) services increases significantly. On the other hand, the current main resource of FR services, the controllable conventional generation, is continuously decreasing in the system generation mix. This means that in the future high renewable penetration power system, additional and alternative reliable FR services providers such as distributed energy storage (DES) resources should be explored. Although the capability of utility-scale energy storage to provide FR services has been demonstrated, the integrated control and dynamic modeling of distributed energy resource (DER) providing frequency regulation grid services has been rarely explored. There are several challenges to adopt DERs to provide reliable grid services as illustrated in FERC 755. First, the distributed installation of DES requires a comprehensive cyber-physical dynamic system (CPDS) modeling to fully consider the impacts of the communication latency variability on its real time FR provision capability. Unlike the conventional generators, there are two-layer communication between DERs and system operators which increase the communication delay. Second, unlike the conventional generators whose dynamic models have been comprehensively studied, the difference among individual DER components' power-dynamic characteristic brings challenges in the accurate dynamic AGC modeling of its power-frequency relationship. Third, the temporal dependent state of charge uncertainty of DERs challenges DERs' power and frequency regulation capacities scheduling in the look-ahead generation scheduling. Therefore, the aggregator should optimize the frequency regulation provision from individual DER in real time. To overcome these challenges, this project proposes a cyber-physical dynamic system (CPDS) model to handle the uncertainty of DERs two-layer communication latency and power dynamics. The variability of DERs' communication delay and dynamic constraints will be comprehensively modeled. The DERs' AGC model with communication delay is designed to validate DESs' frequency regulation services. Like current performance-based frequency regulation evaluation, the delivery of DERs' frequency regulation will be assessed through post-analysis of the actual AGC response with respect to the AGC control signal from system operators. Consequently, the reliability improvement with DERs providing reliable frequency regulation services can be evaluated from a comprehensive perspective considering all the dynamics of communication and power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Pressure feedback control of electro-hydraulic actuators using fixed displacement hydraulic machines

This paper presents the development of a control strategy for Electro-Hydraulic Actuator (EHA) systems based on fixed displacement hydraulic machines. Although some previous studies on EHAs show benefits in terms of energy efficiency and regeneration capability compared to conventional hydraulic systems, few studies focus on the dynamic performance of EHAs. Unlike traditional valve-controlled systems, an EHA based on a fixed displacement pump typically relies on variation of the electric motor shaft speed to control the actuator velocity. This study shows that pressure feedback can be used to control the speed of the electric machine, thus achieving the required actuator/machine dynamic response. A simulation model is developed by including the EM, the hydraulic system, and the actuation system, which can give a realistic prediction of the EHA performance for a typical duty cycle. An open-circuit EHA previously proposed by the authors is used to validate the control strategy, and the simulation results show superior dynamic performance, exhibiting a reduction in response time and oscillatory behavior, compared to a feedforward EHA controller. Following the method presented in this study, it is possible to design a controller with a pressure feedback strategy for EHA systems with different size and actuation requirements

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

On Building Predictive Digital Twin Incorporating Wave Predicting Capabilities: Case Study on UMaine Experimental Campaign - FOCAL

The response of floating wind turbines (FWT) are susceptible to stochastic wave variations. For the optimal operation of FWT, a comprehensive understanding of the phaseresolved wave dynamics and the consequential system response is crucial for real-time monitoring and control. A multi-variate, multi-step, long short term memory (MLSTM), a type of recurrent neural network (RNN) is used to capture complex system dynamics for real-time application. Results indicate that the integration of a wave prediction-reconstruction (WRP) model substantially enhances prediction accuracy by 50% on average relative to the baseline model. The improvement is consistent across various wave extremity and prediction horizons, thereby significantly broadening the scope for timely and precise predictive capabilities.

17 WIND ENERGY↗

DOE OSTI2022

Design Considerations for Controlling Silicon Nanoparticle Nucleation and Growth in a Nonthermal Plasma

Controlling the nucleation and growth of nanoparticles in low temperature plasma systems is imperative for controlling nanoparticle size distributions; and for some applications such as deposition and etching in microelectronic processing, preventing particle contamination. In this work, silicon nanoparticle (NP) production from silane is used as a model system to investigate the nucleation process. Although the mechanisms responsible for silicon NP nucleation and growth have been studied, it is unclear how controllable system parameters (e.g., pressure, system geometry, and gas composition) can be used to inhibit or promote NP formation. For example, the transport of reactive silane species is expected to significantly affect the feed fraction of silane required to nucleate silicon NP (the nucleation onset fraction) due to losses at the reactor walls. In this work, NP mass density was determined as a function of system pressure, gas composition, and reactor diameter for a tubular flow-through radiofrequency (RF) plasma using Ar/H2/He/SiH4 gas mixtures. A quartz crystal microbalance (QCM) impactor was developed to measure the total aerosol mass density downstream of the plasma and thereby identify the nucleation onset and its dependence on process parameters. Finally, a reaction mechanism was developed and incorporated into a global plasma chemistry model to better understand the nucleation onset and NP growth.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Power Grid Simulation Testbed for Transactive Energy Management Systems

To effectively engage demand-side and distributed energy resources (DERs) for dynamically maintaining the electric power balance, the challenges of controlling and coordinating building equipment and DERs on a large scale must be overcome. Although several control techniques have been proposed in the literature, a significant obstacle to applying these techniques in practice is having access to an effective testing platform. Performing tests at scale using real equipment is impractical, so simulation offers the only viable route to developmental testing at scales of practical interest. Existing power-grid testbeds are unable to model individual residential end-use devices for developing detailed control formulations for responsive loads and DERs. Furthermore, they cannot simulate the control and communications at subminute timescales. To address these issues, this paper presents a novel power-grid simulation testbed for transactive energy management systems. Detailed models of primary home appliances (e.g., heating and cooling systems, water heaters, photovoltaic panels, energy storage systems) are provided to simulate realistic load behaviors in response to environmental parameters and control commands. The proposed testbed incorporates software as it will be deployed, and enables deployable software to interact with various building equipment models for end-to-end performance evaluation at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Probability Density Function Control of Frequency Fluctuations in Renewable-Rich Power Systems

The stochastic nature of renewable energy sources (RESs) necessitates treating power system frequency response as a random process with a nonstationary probability density function (PDF). Here, based upon the stochastic distribution control theory originated by the second author, this paper proposes a novel stochastic controller to improve the frequency PDF in power grids when integrating a large amount of RESs, thereby minimizing the effects of uncertainties and enhancing overall system stability. The key idea is to manipulate the controllable power generation resources so that the frequency PDF is make to follow a target PDF by using the stochastic distribution control theory originated by the second author. The proposed method can easily be plugged into existing automatic generation controls for multi-area transmission grids. The proposed method is validated via a modified Kundar's two area system and 240-bus Western Electricity Coordinating Council systems. The simulation results show that the proposed control shapes the frequency PDF narrower and sharper, leading to a notable improvement toward minimizing the effects of randomness and uncertainty during grid operation.

frequency↗

DOE OSTI2021

TRUST Nonlinear Dynamics Testbed Assessment

The following assessment evaluates the efficacy of the control script for carrying out a linear signal to generate a linear mechanical response of the system: the TRUST nonlinear dynamics (TRUSTND) testbed. The hardware has three main components: the controller (NI PXIe 8861) embedded in the National Instruments chassis (NI PXIe 1092), the signal amplifier (The Modal Shop Linear Power Amplifier 2050E09) to amplify the output of a custom LabVIEW script, and a shaker (The Modal Shop Electrodynamic Exciter 2075E) where wave spring specimens live and are tested within the attached aluminum testbed (center mass). Different kinds of signals (single-tone, swept frequency and white noise) were sent through this hardware in the E-1 lab space at TA-53. First, the linearity of the setup was tested by specifying a sine wave in the control script and checking the quality of the oscillations in a wave spring (McMaster-Carr 9714K19 [1]). When passing a sine wave through the amplifier was succeeded, the frequency response of the wave spring was tested with white noise for comparison to finite-element model predictions. The testbed outputs a repeatable, linear response to the input excitation when used with the wave spring. These measurements reduce the uncertainty associated with the testbed and test procedure to better characterize uncertainty associated with material behavior (SX358 foam samples) in future tests

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Power System Frequency Dynamics Modeling, State Estimation, and Control using Neural Ordinary Differential Equations (NODEs) and Soft Actor-Critic (SAC) Machine Learning Approaches

With the global energy transition of the electric power system, grid control, supervision, and protection is becoming more challenging. With the increasing integration of renewable energy sources (RES), the system dynamics are changing, causing traditional power system dynamic modeling with swing equation-based modeling approaches to fail. Additionally, the converter-dominated power grid is decreasing the system inertia, making the power system more fragile to the frequency swings. This paper first investigates and compares the application of a model-based Kalman filter state estimation approach with (i) a model-free machine learning approach --- neural ordinary differential equations (NODEs) --- and (ii) a data-driven system identification (SysId) approach to model and infer critical state values of the power system frequency dynamics. Then a model predictive control (MPC) framework is compared to a model-free Soft Actor-Critic (SAC) reinforcement learning (RL) control algorithm in providing efficient fast frequency response (FFR) to the power system frequency dynamics. The approaches are compared in terms of their performance goals as well as their per-timestep computational efficiency. Furthermore, the comparative study for state estimation shows that for the model-free requirement, both NODEs and SysId can provide accurate state estimates; however, with increasing model complexity, NODEs can be a better choice for model identification. Similarly, the results from the FFR comparative study show that the SAC RL-based FFR, once trained, outperforms MPC with better control signals and faster computation time, making the SAC RL-based FFR better option for providing FFR to the power system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Resilient Communication Scheme for Distributed Decision of Interconnecting Networks of Microgrids

Networking of microgrids can provide the operational flexibility needed for the increasing number of DERs deployed at the distribution level and supporting end-use demand when there is loss of the bulk power system. But, networked microgrids are vulnerable to cyber-physical attacks and faults due to the complex interconnections. As such, it is necessary To design resilient control systems to support the operations of networked microgrids in responses to cyber-physical attacks and faults. This paper introduces a resilient communication scheme for interconnecting multiple microgrids to support critical demand, in which the interconnection decision can be made distributedly by each microgrid controller even in the presence of cyberattacks to some communication links or microgrid controllers. This scheme blends a randomized peer-to-peer communication network for exchanging information among controllers and resilient consensus algorithms for achieving reliable interconnection agreement. The network of 6 microgrids divided from a modified 123-node test distribution feeder is used to demonstrate the effectiveness of the proposed resilient communication scheme.

Vu, Thanh Long↗