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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development of a Practical Secondary Control for Hardware Microgrids

Practical, vendor-agnostic interoperability guidelines for the secondary control architecture of microgrids (MGs) with multiple grid-forming (GFM) inverter-based resources (IBRs) have not yet been developed. Therefore, this paper proposes a generic and vendor-agnostic secondary control architecture that operates with all GFM IBRs and synchronous generators. This secondary control does not require the use of additional measurement devices in the MG and utilizes the inherent communication systems of the GFM units, such as Modbus TCP/IP. The practical challenges of Modbus registers, such as packet loss and quantization error, and their detrimental impacts on secondary control actions are investigated. The proposed three-stage modification for any secondary control architecture to mitigate these impacts includes: 1) averaging the data read, 2) situational event-triggering of the controller, and 3) finite iteration of the controlling action. The proposed method is validated using a 3-..phi.., 480 V, 60 Hz, 500 kVA laboratory hardware microgrid with commercial two GFM IBRs and one diesel generator. The experimental results corroborates the fact the proposed modification in the secondary control architecture is advantageous for practical usage under erroneous measurements.

communication systems↗
DOE OSTI2023

Gridtrust: Electricity Grid Root-of-Trust Decentralized Supply Chain Cyber-Security (Final Scientific/Technical Report)

GridTrust represents a departure from reliance on a single organization or a single person to multiple organizations and therefore multiple people across organizational structures. The motivating idea behind involving multiple organizations is the increase in security due to human factors. More specifically, the requirement that distinct people in different organizations sign off on a change or an update makes a cyberattack much less likely due to the inherent requirement that both organizations be penetrated and fooled. GridTrust focuses on the software update process as the primary exemplar for the research and development work. A novel hardware-based technology referred to as a Physical Unclonable Function (PUF) provides a microchip Root-of-Trust (RoT), i.e., a starting point for verifying that the hardware being communicated with is the hardware the control center believes the hardware to be. As a result, staff at power grid control centers can ensure the accurate and reliable identification of hardware devices from the outset. The GridTrust protocol introduces two key innovations, as detailed in this report. Firstly, the utilization of a PUF as a root-of-trust in the initial phase of a software or firmware update. Secondly, the application of multiple cryptographic signatures from two or more organizations to the update binary. These signatures are verified before implementing the update on a power grid device in the field. In terms of GridTrust hardware design, this report outlines two main components. The first is the GridTrust Native Device, integrating PUF technology intrinsically into the hardware device itself. The second is the GridTrust Interfacing Device, which incorporates PUF technology and multiple cryptographic signatures. These signatures are cross-checked within a separate hardware positioned between the power grid control center and the legacy power grid device, functioning as an intermediary. While the GridTrust Interfacing Device offers the advantage of being applicable to existing power grid equipment, it may have reduced security if the intermediary component is targeted. On the other hand, the GridTrust Native Device boasts increased security due to protocol integration within a unified form factor. The effectiveness of GridTrust technology has been extensively demonstrated, with multiple external red-team attackers unable to breach GridTrust's security measures. This was observed both in controlled laboratory settings during Phase 1 of the project and in real-world conditions within a City of Marietta substation during Phase 2 of the project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

We report ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility's distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood's load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes' energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community's demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Leveraging PMU for Protection and Control

This presentation discusses the application of synchronized measurement in transmission system protection. The proposed wide area system protection (WASP) scheme uses PMU data to perform zonal current differential protection for the whole transmission system with high IBR penetration. This novel protection concept uses synchronized measurement, which is one of the key tasks proposed in the award DE-EE0010655.

14 SOLAR ENERGY↗
DOE OSTI2021

Cascaded systems and methods for controlling energy use during a demand limiting period

A cascaded control system is configured to control power consumption of a building during a demand limiting period. The cascaded control system includes an energy use setpoint generator and a feedback controller. The energy use setpoint generator is configured to use energy pricing data and measurements of a variable condition within the building to generate an energy use setpoint during the demand limiting period. The feedback controller is configured to use a difference between the energy use setpoint and a measured energy use to generate a control signal for building equipment that operate to affect the variable condition within the building during the demand limiting period.

Wenzel, Michael J.↗
DOE OSTI2021

A Novel Decentralized PWM Interleaving Technique for Ripple Minimization in Series-Stacked DC-DC Converters

Cascaded dc-dc converters are commonly used in applications where distributed energy sources or loads are connected to elevated voltage levels for power transfer. In such systems, it is advantageous to minimize the ripple on the bus current and voltage by proper phase shifting of the pulse-width modulation (PWM) pulses among the converters via a method known as interleaving. Existing approaches use either a centralized controller or separate communication lines among the stacked converters to control their relative PWM switch transitions. The key drawbacks are that these methods entail significant wiring, the central controller acts as a single point of failure, and implementation on very large numbers of units is impractical. In this paper, we introduce a decentralized interleaving control (DIC) strategy that acts on local current measurements at every converter and achieves communication-free PWM interleaving among the series-stacked converters. The proposed controller is simple in structure and is shown to converge asymptotically to the interleaved state irrespective of clock drifts among the digital signal processors. Experimental results are provided for a system of five series-connected converters showing a 10× reduction in the current ripple compared to normal operation.

cascaded converter↗
DOE OSTI2021

A Novel Decentralized PWM Interleaving Technique for Ripple Minimization in Series-Stacked DC-DC Converters: Preprint

Cascaded dc-dc converters are commonly used in applications where distributed energy sources or loads are connected to elevated voltage levels for power transfer. In such systems, it is advantageous to minimize the ripple on the bus current and voltage by proper phase shifting of the pulse-width modulation (PWM) pulses among the converters via a method known as interleaving. Existing approaches use either a centralized controller or separate communication lines among the stacked converters to control their relative PWM switch transitions. The key drawbacks are that these methods entail significant wiring, the central controller acts as a single point of failure, and implementation on very large numbers of units is impractical. In this paper, we introduce a decentralized interleaving control (DIC) strategy that acts on local current measurements at every converter and achieves communication-free PWM interleaving among the series-stacked converters. The proposed controller is simple in structure and is shown to converge asymptotically to the interleaved state irrespective of clock drifts among the digital signal processors. Experimental results are provided for a system of five series-connected converters showing a 10 times reduction in the current ripple compared to normal operation.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Vegetation Warming Experiment: Leaf Mass Area, Leaf Carbon and Nitrogen Content, Utqiagvik (Barrow), Alaska, 2018

Leaf mass per area (LMA), leaf carbon and nitrogen content of vegetation (Arctagrostis latifolia, Petasites frigidus) within warming chambers and paired control plots. Samples include gas exchange measurement leaves and an end of season bulk harvest. The files included in this data package are in .csv format, and include 2 data files and 4 metadata files. See related datasets for plant physiology, phenology and environmental conditions of these samples. These data were collected in 2018 as part of a series of single-season warming experiments on tundra vegetation on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. A different plant species was targeted each year, over four experimental years from 2017–2021. Each year, five warming chambers and paired ambient control plots were deployed from around the time of snowmelt in mid-June through to mid-September. Average seasonal warming of 3–4°C was achieved using Zero Power Warming (ZPW) chambers (Lewin et al, 2017).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Local Phasor-Based Control of DER Inverters for Voltage Regulation on Distribution Feeders

We introduce a new control paradigm termed Phasor-Based Control (PBC) to coordinate Distributed Energy Resources (DER) for improved voltage regulation and other objectives. PBC is a multi-layer control framework where the state of the distribution grid is represented by voltage phasors, and Phasor Measurement Units (PMUs) measure the state at critical points in the distribution grid. In the PBC paradigm, a supervisory controller (S-PBC) sets phasor targets which local controllers track. In this paper, we propose a Proportional Integral (PI) implementation for the local control layer (LPBC), to regulate real and reactive power output of distributed inverters to track a voltage phasor target computed by the supervisory layer. We tune the PI controller gains offline with a genetic algorithm that yields better performance than the Ziegler-Nichols method. We benchmark the proposed L-PBC controller against droop volt-var control (DVVC) and observe improved voltage regulation in simulation on the IEEE 13 node unbalanced test feeder (IEEE 13NF). Furthermore, by means of numerical simulation we observe the response of the L-PBC controllers to small and large grid disturbances. Simulations on larger feeders, IEEE 123-node and 647-node, demonstrate challenges with tuning controllers in setups with different amounts of power-voltage coupling.

42 ENGINEERING↗
DOE OSTI2024

Distributed Temperature Profiles of Silicon Carbide Catalyst Bed in a Microwave Reactor using Fiber-optic Sensor

Microwave heating is of great interest for reducing greenhouse gas emissions of catalytic chemical conversion processes because it can heat up the reactants rapidly and efficiently and accelerate reaction rates. In microwave-assisted catalytic thermochemical conversion processes, accurate internal temperature measurement would help facilitate effective process control. Metallic thermocouples interfere and spark in the microwave heating environment, so they are not an option. Infrared pyrometers typically provide a single temperature value by averaging over a finite surface area of the catalyst bed. In this work, we use fiber-optic sensors passing through the catalyst bed to provide more accurate temperatures along the height of the catalyst bed. The fiber optic sensors are immune to the electromagnetic microwave radiation and provide temperature profiles along their length. Here, custom fiber-optic sensors were coupled to the optical distributed temperature sensing devices to measure the temperature profiles along the height of the catalyst bed at high temperatures with ~1 mm spatial resolution. The sensing devices use optical frequency domain reflectometry (OFDR) technique for distributed temperature measurement. This work shows the temperature profiles along the height of the silicon carbide powder catalyst bed in the variable and fixed frequency microwave reactors.

Thapa, Juddha↗
DOE OSTI2022

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗
DOE OSTI2024

Formation of a spherical plasma liner for plasma-jet-driven magneto-inertial fusion

Plasma-jet-driven magneto-inertial fusion is an alternative approach to controlled nuclear fusion, which aims to utilize a line-replaceable dense plasma liner as a repetitive spherical compression driver. In this experiment, first measurements of the formation of a spherical argon plasma liner formed from 36 discrete pulsed plasma jets are obtained on the Plasma Liner Experiment. Properties including liner uniformity and morphology, plasma density, temperature, and ram pressure are assessed as a function of time throughout the implosion process and indicate an apparent transition from initial kinetic inter-jet interpenetration to collisional regime near stagnation times, in accordance with theoretical expectation. A lack of primary shock structures between adjacent jets during flight implies that arbitrarily smooth liners may be formed by way of corresponding improvements in jet parameters and control. The measurements facilitate the benchmarking of computational models and understanding the scaling of plasma liners toward fusion-relevant energy density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Designing an Intrusion Proof Adjustable Speed Drive System Controlling a Critical Process

In this paper, an intrusion proof adjustable speed drive system controlling a critical process in an industrial control system is detailed. In such a system, should the motor speed sensor signal data be compromised and/or altered via a cyber-attack, the system can potentially be unregulated, over speed and/or malfunction thereby disrupting the critical process. The proposed active detection scheme detailed in this paper introduces a private (secret) random signal termed as "watermark" into the inverter control signal that determines the PWM gating signals of the DC-AC inverter powering the motor. The watermarking signal introduced into the PWM modulation for the DC-AC inverter is shown to propagates its unique signature, which appears in all sensors signals at the inverter output such as voltage/current/speed used to control the motor. Now employing the measured data (from sensors), two statistical variance tests are conducted to identify anomalies if any in the presence of the watermarking signal. It is shown when an intrusion occurs to manipulate the sensor data to disturb and/or destabilize the process, the proposed tests immediately display a high value indicating a compromise in sensor data. It is shown that the proposed system is capable of immediate detection of a sophisticated attacks such as record/reply attack in which the actual speed sensor is disconnected and a prerecorded speed signal from the past of the same magnitude is played back to the controller. Several types of cyber-attacks such as speed reduction/increase including vibration have been tested. Extensive simulation results verify the proposed concepts. Experimental results will be discussed in the conference presentation.

Alotaibi, Faris↗
DOE OSTI2020

Method and apparatus for evaluating superconducting tunnel junction detector noise versus bias voltage

A technique for characterizing the noise behavior of a superconducting tunnel junction (STJ) detector as a function of its applied bias voltage Vb by stepping the STJ's bias voltage across a predetermined range and, at each applied bias, making multiple measurements of the detector's current, calculating their mean and their standard deviation from their mean, and using this standard deviation as a measure of the STJ detector's noise at that applied bias. Because the method is readily executed under computer control, it is particularly useful when large numbers of STJ detectors require biasing, as in STJ detector arrays In a preferred implementation, the STJ is measured under computer control by attaching it to a digital spectrometer comprising a digital x-ray processor (DXP) coupled to a preamplifier that can set the STJ's bias voltage Vb using a digital-to-analog converter (DAC) controlled by the DXP.

Warburton, William K.↗
DOE OSTI2020

Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes

Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disruption of operation, financial losses, and equipment damage. In particular, false data attacks initiated during power systems transients caused due to abrupt changes in load and generation can fool the conventional model-based detection methods relying on thresholds comparison to trigger an anomaly. In this paper, we propose a Koopman mode decomposition (KMD) based algorithm to detect and identify false data attacks in real-time. The Koopman modes (KMs) are capable of capturing the nonlinear modes of oscillation in the transient dynamics of the power networks and reveal the spatial embedding of both natural and anomalous modes of oscillations in the sensor measurements. The Koopman-based spatio-temporal nonlinear modal analysis is used to filter out the false data injected by an attacker. The performance of the algorithm is illustrated on the IEEE 68-bus test system using synthetic attack scenarios generated on GridSTAGE, a recently developed multivariate spatio-temporal data generation framework for simulation of adversarial scenarios in cyber-physical power systems.

Nandanoori, Sai Pushpak↗
DOE OSTI2020

Taxonomic and nutrient controls on phytoplankton iron quotas in the ocean

Abstract Phytoplankton iron contents (i.e., quotas) directly link biogeochemical cycles of iron and carbon and drive patterns of nutrient limitation, recycling, and export. Ocean biogeochemical models typically assume that iron quotas are either static or controlled by dissolved iron availability. We measured iron quotas in phytoplankton communities across nutrient gradients in the Pacific Ocean and found that quotas diverged significantly in taxon‐specific ways from laboratory‐derived predictions. Iron quotas varied 40‐fold across nutrient gradients, and nitrogen‐limitation allowed diatoms to accumulate fivefold more iron than co‐occurring flagellates even under low iron availability. Modeling indicates such “luxury” uptake is common in large regions of the low‐iron Pacific Ocean. Among diatoms, both pennate and centric genera accumulated luxury iron, but the cosmopolitan pennate genus Pseudo‐nitzschia maintained iron quotas 10‐fold higher than co‐occurring centric diatoms, likely due to enhanced iron storage. Biogeochemical models should account for taxonomic and macronutrient controls on phytoplankton iron quotas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Thermodynamic stability and contributions to the Gibbs free energy of nanocrystalline Ni 3 Fe

In this work, the heat capacities of nanocrystalline Ni 3 Fe and control materials with larger crystallites were measured from 0.4–300 K. The heat capacities were integrated to obtain the enthalpy, entropy, and Gibbs free energy and to quantify how these thermodynamic functions are altered by nanocrystallinity. From the phonon density of states (DOS) measured by inelastic neutron scattering, we find that the Gibbs free energy is dominated by phonons and that the larger heat capacity of the nanomaterial below 100 K is attributable to its enhanced phonon DOS at low energies. Besides electronic and magnetic contributions, the nanocrystalline material has an additional contribution at higher temperatures, consistent with phonon anharmonicity. The nanocrystalline material shows a stronger increase with temperature of both the enthalpy and entropy compared to the bulk sample. Its entropy exceeds that of the bulk material by 0.4 $k_B$/atom at 300 K. This is insufficient to overcome the enthalpy of grain boundaries and defects in the nanocrystalline material, making it thermodynamically unstable with respect to the bulk control material.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Validation of new and existing methods for time-domain simulations of turbulence and loads

We seek to obtain a second-by-second match between the simulated and measured structural loads of a utility-scale wind turbine. To obtain the one-to-one load simulations, we start with the furthest upstream component of the modeling chain: the turbulent inflow. We consider new and existing methods to generate constrained-turbulence flow fields. The new method is based on large-eddy simulations (LES) and machine learning (ML). The existing methods include Kaimal-based TurbSim and the superstatistical wind field model. The inflow measurements used to constrain these simulations are obtained with a nacelle-mounted scanning lidar. We compare the flow fields for the different inflow simulation approaches and validate their associated load predictions against measurements collected in the Rotor Aero-dynamics, Aeroelastics, and Wake (RAAW) field campaign. We find that the rotor-position control developed for this study is key in enabling the time match between measurements and simulations. When this control approach is used, the load simulation performance tracks with the inflow simulation fidelity, with LES+ML yielding errors ≤ 4% for the damage-equivalent loads of flapwise bending moment, and tower fore-aft bending moments.

17 WIND ENERGY↗