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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Investigating Oscillations in Bulb Turbine Plant During Islanded black start Operation

This paper investigates the frequency oscillatory behavior displayed by the bulb turbine-based run-of-river (ROR) hydropower system under islanded operation. These oscillations prevent higher loading of these generators (under islanded conditions) and hence reduce the black start capability of these generators. To investigate the problem, first, a transfer function model of the bulb-turbine system, sensitive to the effects of head variation, blade angle, and other non-linearities pertaining to turbine characteristics is derived. Next, by analyzing this transfer function model and through simulations, it is determined that system inertia along with other parameters could be responsible for these oscillations. Also, through simulations it is shown that the same ROR system’s behavior is different under islanded mode compared to grid-connected mode.

13 HYDRO ENERGY↗
DOE OSTI2024

Impacts of Control, Penetration, and Distribution of Embedded Storage Network in Bulk Power System

The current shift in generation mix from fossil fuel plants towards variable and intermittent renewable energy sources is poised to create a future grid with reduced physical inertia and mismatch between generation and demand. Embedded storage, which is a concept of a coordinated network of storage units sited at the interface between the transmission and distribution system, is proposed as a mechanism to provide a buffer between generation and demand. This paper proposes an automated framework to model and integrate embedded storage in large-scale power systems with industry-grade grid-following (GFL) and grid-forming (GFM) control technologies. More importantly, the developed framework is used to explore the impacts of embedded storage control, penetration, location, and capacity in providing fast frequency response to the grid under contingency events such as generator trips and faults. The framework and study are conducted using the transient-stability simulation tool PSS/E and a realistic model of the Puerto Rico grid as a chosen test system. The simulation results show that GFL and GFM embedded storage, distributed throughout the system, with sufficient penetration and capacity, can effectively improve primary frequency response of the system under the studied contingency events.

Battery Energy Storage, embedded storage, grid-for↗
DOE OSTI2025

Design Principles for Resonant Wave Energy Converters: Benchmarking Power Capture and Flow

Control co-design (CCD) in Wave Energy Converters (WECs) integrates the controller, power take-off (PTO), and buoy models during system design to optimize power output. Using the bi-conjugate impedance matching principle, this study models the PTO as a two-port network, revealing impedance matching conditions at the input and output ports as a function of the buoy, PTO, and controller. Here, this study examines the pairing of a flywheel-type pitch resonator PTO within a given buoy constrained by limited space and ballast capacity. The results show that physical constraints imposed by the buoy affect PTO performance. While controller tuning achieves optimal output impedance matching and flywheel inertia is maximized within the buoy's limitations, the PTO's input impedance remains smaller than the complex conjugate of the buoy's intrinsic impedance. This mismatch limits the PTO's ability to generate sufficient reaction torque, particularly outside the resonance frequency, resulting in narrow-band power transfer. The findings emphasize the need for PTO design modifications to improve input power transfer. Pendulum-based PTO mechanisms are proposed as alternatives to couple with multiple buoy motion modes and improve wave-to-wire efficiency while respecting system constraints.

Control Co-Design↗
DOE OSTI2024

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↗
DOE OSTI2021

Electric Water Heaters for Transactive Systems: Model Evaluations and Performance Quantification

Electric water heaters (EWHs) are opportune appliances for implementing demand-side control. EWH models serve as a fundamental step toward accurately estimating EWH flexibility potential and designing proper control strategies. Existing studies have adapted numerous modeling approaches in evaluating the potential of EWHs for a variety of grid applications. This paper presents an analytical study that evaluates the performance of state-of-art EWH models in terms of accuracy and computational complexity for adaptation in evaluation studies for the transactive system. The work proposes a transactive control strategy that optimally utilizes the thermal inertia of EWHs for providing grid services. Here, the performance of the control strategy and the impact of modeling accuracy is evaluated for device-level and feeder-level use cases using the IEEE 123 node test distribution system appropriately populated with EWHs. The simulation results illustrate the effectiveness of the control strategy in reducing the feeder demand during peak period by 13% and also quantities the impact of using simplified modeling approaches for determining the potential of EWHs for providing grid services.

42 ENGINEERING↗
DOE OSTI2024

Autonomous Grid Support Functionality in Variable-Speed Drive-Based End-Use Loads

High penetration of inverter-based resources into power systems causes lower inertia, and it becomes more challenging to maintain grid stability during contingency events. While conventional demand response and shedding at the load side suffer from slow response, impact by unavailability, and issues from communication, variable-speed drives (VSDs) are becoming strong candidates for fast frequency response (FFR) thanks to their fast response and reduced user impact from variable power adjustment capability. In this letter, we propose an autonomous frequency support control method for a residential refrigerator with a VSD, a promising target small end-use load for FFR. We analyze the effect of the proposed controller on grid stability, and we verify the performance through laboratory experiments with a commercially available refrigerator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A Stable and Ultrafast Control for Multiparallel Grid-Tied SiC Inverters With LVRT Capability Considering Cable Impedance

The stability of multiparalleled grid-tied inverters remains a challenging issue especially during low-voltage ride-through (LVRT) in the presence of grid impedance. SiC device-based grid-tied inverters can achieve advantages such as higher efficiency, reduced size of interface filters, and fast dynamics; however, they can exacerbate this stability issue particularly when LVRT occurs along with high inrush current due to their low inertia characteristics. In this article, a direct deadbeat control method without any PI control loop is proposed for multiparallel grid-tied SiC inverters. The proposed control achieves instantaneous current regulations within switching cycles. In addition, it mitigates high inrush currents and maintains stability during LVRT transients without requiring mode transitions between normal and LVRT operation modes, thereby achieving an ultrafast response and seamless operation through this unified control method. The Lyapunov method is applied to analyze the multiparallel inverter stability in the presence of grid impedance with proposed deadbeat control method. The inverter V-I trajectories during LVRT transients are derived to illustrate the ultrafast and stable feature of proposed control. Finally, the experimental results of two grid-tied SiC inverters operating at LVRT transients are provided to verify the advantages of the proposed control method.

14 SOLAR ENERGY↗
DOE OSTI2022

Practical Event Location Estimation Algorithm for Power Transmission System Based on Triangulation and Oscillation Intensity

Event location in power systems is quite essential information for system operators to enhance control-room situational awareness capability. Therefore, it is of great importance to develop an event location estimation algorithm for transmission systems with high accuracy. With the development of wide-area measurement system (WAMS) such as FNET/GridEye, and the synchrophasor measurement devices (SMDs) such as frequency disturbance recorders (FDRs), the synchronous measurement data including frequency, voltage amplitude and phase angle can be collected and used for event location estimation. First, the phase angle and rate of change of frequency (RoCoF) trajectories are respectively used for determining two sets of wave arrival time associated with each FDR. Then, a convolutional neural network (CNN) is utilized to determine the wave arrival order to select the more suitable set of wave arrival times for a given case and to perform corresponding modifications. Next, the oscillation intensity associated with each FDR is determined based on phase angle trajectories in the center of inertia (COI) coordinate system. Finally, the multiple criteria for event location estimation are represented. In conclusion, case studies and comparisons between the proposed and previous algorithms using actual and confirmed cases in U.S. power systems are performed to demonstrate the effectiveness and improvement of the proposed algorithm in practical applications.

frequency disturbance recorder (FDR)↗
DOE OSTI2020

Microgrid Stability Definitions, Analysis, and Examples

This document is a summary of a report prepared by the IEEE PES Task Force (TF) on Microgrid Stability Definitions, Analysis, and Modeling [1], which defines concepts and identifies relevant issues related to stability in microgrids. In this paper, definitions and classification of microgrid stability are presented and discussed, considering pertinent microgrid features such as voltage-frequency dependency, unbalancing, low inertia, and generation intermittency. A few examples are also presented, highlighting some of the stability classes defined in the paper. Further examples, along with discussions on microgrid components modeling and stability analysis tools can be found in the TF report.

Farrokhabadi, Mostafa↗
DOE OSTI2020

Distributed Small-Signal Stability Conditions for Inverter-Based Unbalanced Microgrids

The proliferation of inverter-based generation and advanced sensing, controls, and communication infrastructure have facilitated accelerated deployment of microgrids. A coordinated network of microgrids can maintain reliable power delivery to critical facilities during extreme events. Low-inertia offered by the power-electronics–interfaced energy resources, however, can present significant challenges to ensuring stable operation of the microgrids. In this work, distributed small-signal stability conditions for inverter-based microgrids are developed that involve the droop-controller parameters and the network parameters (e.g. line impedances, loads). The distributed closed-form parametric stability conditions derived in this paper can be verified in a computationally efficient manner, facilitating reliable design and operations of networks of microgrids. Dynamic phasor models have been used to capture the effects of electromagnetic transients. Furthermore, numerical results are presented, along with PSCAD simulations, to validate the analytical stability conditions. Effects of design choices, such as the conductor types, and inverter sizes, on the small-signal stability of inverter-based microgrids are investigated to derive useful engineering insights.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Renewable Integration in Hybrid ac-dc Systems using Multi-port Autonomous Reconfigurable Solar power plant (MARS)

To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.

14 SOLAR ENERGY↗
DOE OSTI2022

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is an imperative need to enhance grid emergency control to maintain system reliability and security. Towards this end, great progress has been made in developing deep reinforcement learning (DRL) based grid control solutions in recent years. However, existing DRL-based solutions have two main limitations: 1) they cannot handle well with a wide range of grid operation conditions, system parameters, and contingencies; 2) they generally lack the ability to fast adapt to new grid operation conditions, system parameters, and contingencies, limiting their applicability for real-world applications. Here, in this paper, we mitigate these limitations by developing a novel deep meta-reinforcement learning (DMRL) algorithm. The DMRL combines the meta strategy optimization together with DRL, and trains policies modulated by a latent space that can quickly adapt to new scenarios. We test the developed DMRL algorithm on the IEEE 300-bus system. We demonstrate fast adaptation of the meta-trained DRL polices with latent variables to new operating conditions and scenarios using the proposed method, which achieves superior performance compared to the state-of-the-art DRL and model predictive control (MPC) methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Synchro-Waveform-Based Event Identification Using Multi-Task Time-Frequency Transform Networks

Influenced by the transient dynamics and reduced inertia characteristics of high-penetration renewable energy systems, power system events frequently exhibit distinct characteristics such as high-frequency components including wide-band oscillations and hyper-harmonics. This makes standard systems face challenges including significant latency and reduced accuracy due to limited data resolution. However, current methods face significant limitations, including insufficient pattern capture ability, low noise immunity, limited feature learning, and restricted localization capabilities, thereby hindering real-time performance. To tackle this issue, this paper proposed a novel synchro-waveform-based event identification approach via a Multi-task Time-frequency Transform Network (MTTNet). Initially, a Time-frequency Transform Block (TTB) is developed to extract both local and global information. The TTB leverages both Fourier and S-transforms to derive comprehensive time-frequency information from synchro-waveforms. Subsequently, a multi-task learning strategy is employed to identify the type and distinguish localization of events. Integrating the TTB and multi-task learning, the MTTNet is designed for synchro-waveform-based event identification, incorporating an adaptive weighting strategy and simplified computation for the S-transform. Two different datasets, comprising simulated and actual synchro-waveforms, are collected from the IEEE 123 bus system and a real-world high-penetration renewable energy system using a universal grid analyzer. Extensive experiments on various conditions are carried out. In conclusion, results demonstrated that the MTTNet consistently surpasses both basic and advanced baselines, with maximum improvements of 13.24% and 9.86%, respectively, while reducing the calculation burden by 15-19 times to achieve real-time event identification.

Event identification↗
DOE OSTI2022

Phylogenetic conservatism of mycoparasitism and its contribution to pathogen antagonism

Abstract Closely related species are expected to have similar functional traits due to shared ancestry and phylogenetic inertia. However, few tests of this hypothesis are available for plant‐associated fungal symbionts. Fungal leaf endophytes occur in all land plants and can protect their host plant from disease by a variety of mechanisms, including by parasitizing pathogens (e.g., mycoparasitism). Here, we tested whether phylogenetic relatedness among species of Cladosporium , a widespread genus that includes mycoparasitic species, predicts the effect of this endophyte on the severity of leaf rust disease. First, we used congruence among different marker sequences (i.e., genealogical concordance phylogenetic species recognition criterion) to delimit species of Cladosporium . Next, in a controlled experiment, we quantified both mycoparasitism and disease modification for the selected Cladosporium species. We identified 17 species of Cladosporium ; all the species reduced rust disease severity in our experiment. Cladosporium phylogeny was a significant predictor of mycoparasitism. However, we did not observe a phylogenetic effect on disease severity overall, indicating that other mechanism/s operating independently of shared ancestry also contributed to endophyte effects on disease severity. Indeed, a second experiment showed that Cladosporium endophyte exudates (no live organism) from divergent species groups equally reduced disease severity. Our results reveal that multiple mechanisms contribute to the protective effects of an endophyte against a plant pathogen, but not all traits underlying these mechanisms are phylogenetically conserved.

Barge, Edward G.↗
DOE OSTI2024

Persistent urban heat

Urban surface and near-surface air temperatures are known to be often higher than their rural counterparts, a phenomenon now labeled as the urban heat island effect. However, whether the elevated urban temperatures are more persistent than rural temperatures at timescales commensurate to heat waves has not been addressed despite its importance for human health. Combining numerical simulations by a global climate model with a surface energy balance theory, it is demonstrated here that urban surface and near-surface air temperatures are significantly more persistent than their rural counterparts in cities dominated by impervious materials with large thermal inertia. Further use of these materials will result in even stronger urban temperature persistence, especially for tropical cities. The present findings help pinpoint mitigation strategies that can simultaneously ameliorate the larger magnitude and stronger persistence of urban temperatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Loss of a satellite could explain Saturn’s obliquity and young rings

The origin of Saturn’s ~26.7° obliquity and ~100-million-year-old rings is unknown. The observed rapid outward migration of Saturn’s largest satellite, Titan, could have raised Saturn’s obliquity through a spin-orbit precession resonance with Neptune. We use Cassini data to refine estimates of Saturn’s moment of inertia, finding that it is just outside the range required for the resonance. We propose that Saturn previously had an additional satellite, which we name Chrysalis, that caused Saturn’s obliquity to increase through the Neptune resonance. Destabilization of Chrysalis’s orbit ~100 million years ago can then explain the proximity of the system to the resonance and the formation of the rings through a grazing encounter with Saturn.

Science & Technology - Other Topics↗
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 OSTI2020

Skeletal tissue regulation by catalase overexpression in mitochondria

Accumulation of oxidative damage from excess reactive oxygen species (ROS) may contribute to skeletal aging and mediate adverse responses to physiological challenges. Wild-type (WT) mice and transgenic mice (male, 16 wk of age) with human catalase targeted to the mitochondria (mCAT) were analyzed for skeletal responses to the remodeling stimuli of combined hind-limb unloading and exposure to ionizing radiation ( 137 Cs, 2 Gy). Treatment for 2 wk caused lipid peroxidation in the bones WT but not mCAT mice, showing that transgene expression mitigated oxidative stress. Ex vivo osteoblast colony growth rate was 95% greater in mCAT than WT mice and correlated with catalase activity levels ( P < 0.005, r = 0.67), although terminal osteoblast and osteoclast differentiation were unaffected. mCAT mice had lower cancellous bone volume and cortical size than WT mice. Ambulatory control mCAT animals also displayed reduced cancellous and cortical structural properties compared with control WT mice. In mCAT but not WT mice, treatment caused an unexpectedly rapid radial expansion (+8% cortical area, +22% moment of inertia), reminiscent of compensatory bone growth during advancing age. In contrast, treatment caused similar structural deficits in cancellous tissue of mCAT and WT mice. In sum, mitochondrial ROS signaling via H 2 O 2 was important for the acquisition of adult bone structure and catalase overexpression failed to protect cancellous tissue from treatment. In contrast, catabolic stimuli caused radial expansion in mCAT not WT mice, suggesting that mitochondrial ROS in skeletal cells act to suppress tissue turnover in response to remodeling challenges.

Cell Biology↗