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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Voltage Injection-Based Current Harmonics Suppression Strategy for Six-Phase PMSM With Nonsinusoidal Back EMF

This article presents a voltage injection-based current harmonic minimization method for wide bandgap device-based six-phase permanent magnet synchronous machine (PMSM) drives. The presence of low-order harmonics is common in the back EMF of PMSMs with low slot and high pole numbers. The back EMF harmonics generate low-order harmonic currents that increase torque ripples. Furthermore, zero-sequence current (ZSC) is also observed if all six phases are connected to a common neutral point. ZSC does not affect the torque ripple but reduces the system efficiency. A special technique is required to reduce ZSC for variable speed drives as direct ac component to synchronous reference frame (SRF) dc transformation is not possible for ZSC. In this article, a voltage injection-based current harmonics reduction method is proposed. The injected harmonic voltage coefficients are calculated from the harmonic estimations of back EMF and updated using closed-loop harmonic compensators to improve steady-state performance. For ZSC reduction, third harmonics power controller, and for 6n ± 1 (n = 1, 2,...) order harmonic current reduction, SRF current controllers are presented in this article. Furthermore, the current harmonics minimization method is experimentally verified using a GaN-based three-level active neutral point clamped inverter-driven six-phase PMSM.

42 ENGINEERING↗
DOE OSTI2021

Dynamic P-Q Capability and Abnormal Operation Analysis of a Wind Turbine with Doubly-Fed Induction Generator

After several accidents occurred in wind farms in the United States and around the world, the subsynchronous oscillation (SSO) issues in grid-connected wind farms have gained serious attention. Particularly, these issues have caused significant challenges to wind turbines with a doubly fed induction generator (DFIG) because it is connected to the grid via both its stator and rotor paths. Traditionally, a P-Q capability chart is utilized to assure the safe operation boundary for a synchronous generator. But the energy conversion characteristics of a DFIG wind turbine are completely different. A critical factor to affect the reliable operation of a DFIG wind turbine is the rated current and pulse-width modulation (PWM) saturation constraints of its power converters. These constraint conditions can be affected by the wind turbine rotating speed and grid conditions. However, a detailed study of DFIG P-Q capability from these perspectives has not been conducted, which has hindered adequate understanding of many abnormal wind turbine operations reported in the literature and the development of advanced control technologies to overcome the challenges. The proposed study in this paper considers vector control implementation to DFIG power electronic converters in the dq reference frame, and the models and algorithms developed for the P-Q capability study have addressed specific DFIG power converter constraints that are different from those of a traditional synchronous generator. The paper especially focuses on exploring the dynamic natures of DFIG P-Q capability under uncertain and variable conditions to explore the root causes of many abnormal operations of DFIG wind turbines reported in the literature. The proposed study is validated through an electromagnetic transient simulation model of a grid-connected DFIG wind turbine. The proposed study has the potential to lead to the development of new DFIG control technologies that can help overcome the challenges for many abnormal operations of DFIG wind turbines.

17 WIND ENERGY↗
DOE OSTI2022

CONGO²: Scalable Online Anomaly Detection and Localization in Power Electronics Networks

Rapid and accurate detection and localization of electronic disturbances simultaneously are important for preventing its potential damages and determining potential remedies. Existing anomaly detection methods are severely limited by the low accuracy, the expensive computational cost and the need for highly trained personnel. There is an urgent need for a scalable online algorithm for in-field analysis of large-scale power electronics networks. Here in this paper, we propose a fast and accurate algorithm for anomaly detection and localization of power electronics networks: stratified colored-node graph (CONGO2). This algorithm hierarchically models the change of correlated waveforms and then correlated sensors using the colored-node graph. By aggregating the change of each sensor with its neighbors’ inputs, we can spontaneously identify and localize the anomaly that cannot be detected by data collected from a single sensor. As our proposed method only focuses on the changes within a short time frame, it is highly computational efficient and only needs small data storage. Thus, our method is ideal for online and reliable anomaly detection and localization of large-scale power electronic networks. Compared to existing anomaly detection methods, our method is entirely data-driven without training data, highly accurate and reliable for wide-spectrum anomalies detection, and more importantly, capable of both detection and localization. Thus, it is ideal for infield deployment for large-scale power electronic networks. As illustrated by a distributed energy resources (DERs) power grid with 37-node, our method can effectively detect and localize various cyber and physical attacks.

42 ENGINEERING↗
DOE OSTI2020

A Dynamically-Reconfigurable Burst-Mode Link Using a Nanosecond Photonic Switch

Fast optical circuit switching has great potential to solve scaling issues with traditional packet-switch based networks and improve bandwidth and power efficiency in datacenter and high-performance computing applications. One difficultly in utilizing a fast optical switch is that the optical signal must be rapidly reacquired after each switching event so as to not significantly impact the overall throughput of the system. In this work we present a system-level integration of a nanosecond-scale $2 \times 2$ silicon photonic switch with a 25-Gbps burst-mode receiver that can lock in 31 ns. A novel FPGA-based control plane was used to generate test data, control the silicon photonic switch and burst-mode receiver, and measure bit errors at 12.5 and 20 Gbps. Error-free links (BER $< 10^{-12}$ ) with system-level reconfiguration times below 60 ns (at 20 Gbps) and 90 ns (at 12.5 Gbps) including bit- and frame-synchronization are demonstrated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load

Quasi-static structural finite-element models of an aluminum-framed crystalline silicon photovoltaic module and a glass-glass thin-film module were constructed and validated against experimental measurements of deflection under uniform pressure loading. Specific practices in the computational representation of module assembly were identified as influential to matching experimental deflection observations. Additionally, parametric analyses using Latin hypercube sampling were performed to propagate input uncertainties related to module materials, dimensions, and tolerances into uncertainties in simulated deflection. Sensitivity analyses were performed on the uncertainty quantification datasets using linear correlation coefficients and variance-based sensitivity indices to elucidate key parameters influencing module deformation. Results identified edge tape and adhesive material properties as being strongly correlated to module deflection, suggesting that optimization of these materials could yield module stiffness gains at par with the conventionally structural parameters, such as glass thickness. This exercise verifies the applicability of finite-element models for accurately predicting mechanical behavior of solar modules and demonstrates a workflow for model-based parametric uncertainty quantification and sensitivity analysis. Finally, applications of this capability include the assessment of field environment loads, derivation of representative loading conditions for reduced-scale testing, and module design optimization, among others.

42 ENGINEERING↗
DOE OSTI2021

Comparison of Surface Phenomena Created by Underground Chemical Explosions in Dry Alluvium and Granite Geology From Fully Polarimetric VideoSAR Data

Phase I of the Source Physics Experiment (SPE) series involved six underground chemical explosions, all of which were conducted at the same experimental pad. Research from the sixth explosion of the series (SPE-6) demonstrated that polarimetric synthetic aperture radar (PolSAR) is a viable technology for monitoring an underground chemical explosion when the geologic structure is Cretaceous granitic intrusive. It was shown that a durable signal is measurable by the H/A/α polarimetric decomposition parameters. After the SPE-6 experiment, the SPE program moved to the Phase II location, which is composed of dry alluvium geology (DAG). The loss of wavefront energy is greater through dry alluvium than through granite. In this article, we compare the SPE-6 analysis to the second DAG (DAG-2) experiment. We hypothesize that despite the geology at the DAG site being more challenging than at the Phase I location, combined with the DAG-2 experiment having a 3.37 times deeper scaled depth of burial than the SPE-6, a durable nonprompt signal is still measurable by a PolSAR sensor. We compare the PolSAR time-series measures from videoSAR frames, from the SPE-6 and DAG-2 experiments, with accelerometer data. We show which PolSAR measures are invariant to the two types of geology and which are geology dependent. We compare a coherent change detection (CCD) map from the DAG-2 experiment with the data from a fiber-optic distributed acoustic sensor to show the connection between the spatial extent of coherence loss in CCD maps and spallation caused by the explosion. Finally, we also analyze the spatial extent of the PolSAR measures from both explosions.

42 ENGINEERING↗
DOE OSTI2021

Antarctic Water Masses and Ice Shelves: Visualizing the Physics

High-resolution simulation of global climate physics enables us to model how the climate may change under a variety of future scenarios. Such simulations produce vast amounts of information and dense datasets. If interrogated in tandem, these datasets can provide holistic, vital information on Earth’s many integrated systems by revealing the manifold interrelated properties of the atmosphere, ocean, and polar ice, framed by real-world terrain in three-dimensional space as they vary over time. To accomplish this, climate scientists have joined with computer scientists and an artist to develop techniques enabling scientists to see these relationships. Finally, the impact of ocean water properties on Antarctic ice shelves illustrates the benefit of this analysis in understanding land ice melt rates and thus sea-level rise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

In Their Shoes: Persona-Based Approaches to Software Quality Practice Incentivization

Many teams struggle to adapt and right-size software engineering best practices for quality assurance to fit their context. Introducing software quality is not usually framed in a way that motivates teams to take action, thus resulting in it becoming a “check the box for compliance” activity instead of a cultural practice that values software quality and the effort to achieve it. When and how can we provide effective incentives for software teams to adopt and integrate meaningful and enduring software quality practices? Here, we explored this question through a persona-based ideation exercise at the 2021 Collegeville Workshop on Scientific Software in which we created three unique personas that represent different scientific software developer perspectives.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Research Software Engineering: Introducing a New Computing in Science & Engineering Department

Here, this article introduces the new Research Software Engineering (RSEng) department at Computing in Science & Engineering. Through a conversation with the department coeditors, we highlight why RSEng matters, how it differs from industrial software engineering, what it means to be an RSE, and the scholarly and practical questions that lie ahead. Along the way, we draw on emerging literature, case studies, and community perspectives to frame the profession and practice of RSEng within computational science and engineering.

Lamprecht, Anna-Lena [Univ. of Potsdam (Germany)] ↗
DOE OSTI2025

Robustness: The Missing Ingredient in Generation Scheduling

This article highlights robustness as an essential factor to cope with the ever-increasing levels of uncertainty in generation scheduling under significant renewable energy penetration, as is the case in Brazil and Spain. To that end, robust generation scheduling is framed within the different optimization-based approaches that are available for uncertainty handling. In addition, the suitability of robust optimization to accommodate practical security criteria in generation scheduling is also emphasized. Interestingly, this article points out the existence of an effective algorithm allowing the discovery of critical or so-called umbrella scenarios, which paves the way for the implementation of robust generation scheduling in industry practice.

Street, Alexandre↗
DOE OSTI2021

In Situ Transmission Electron Microscopy: Signal processing challenges and examples

Transmission electron microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TEM have enabled high-volume and high-resolution data collection at a microsecond frame rate. Here, taking advantage of these advances in data collection rates requires the development and application of data processing tools, including image analysis, feature extraction, and streaming data processing techniques. In this article, we highlight a few areas in materials science that have benefited from combining signal processing and statistical analysis with data collection capabilities in TEM and present a future outlook on opportunities of integrating signal processing with automated TEM data analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoitaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗
DOE OSTI2024

Anomaly Detection and Mitigation for Dynamic Frequency Regulation in Hydropower-Battery Systems

Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the PJM Interconnection. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure to a multitude of cybersecurity threats. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a hydropower-integrated BESS topology, specifically analyzing the slow regulation signal (Reg A) coming from the PJM market. Our simulation results demonstrate that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's transient instability during the participation of hydropower and BESS in the regulation market.

battery energy storage system↗
DOE OSTI2024

Probing Signal-Based Inertia and Frequency Response Estimation for Power Systems With High Levels of Inverter-Based Resources

Power system inertia is the inherent capability of a power system to resist changes in its frequency during disturbances. Real-time inertia estimation technology has become more important due to the low-inertia issues caused by the increasing integration levels of inverter-based resources (IBRs) from renewable energy; however, existing inertia estimation methods hardly consider multiple frequency response controls that act within the same time frame as conventional inertial response, thus making measured inertia values vary under different testing conditions. To resolve this issue, this paper proposes a novel real-time estimation method to simultaneously estimate a power system's inertia constant and frequency response droop constant using a well-designed probing signal. First, we formulate the inertia and frequency response model of a power system with IBRs. Second, through the integration and manipulation of the developed model, we propose a multivariate linear regression-based estimation method that is resilient to measurement noise. Third, we design a probing signal that can be injected by IBRs to incite the required transients for estimation. Finally, we validate the proposed estimation method through comprehensive power-hardware-in-the-loop experiments using inverter hardware and a realistic island power system model. The results demonstrate that the proposed method can accurately estimate the inertia and droop value of the power system with grid-following IBRs and grid-forming IBRs with virtual synchronous machine control.

frequency response↗
DOE OSTI2023

DQ Admittance Extraction for Inverter-Based Resources

The power grid industry is pushing for electromagnetic transient (EMT)-based studies for generation interconnection and planning process due to high penetrations of inverter-based resource (IBRs). Vendor-specific and site-specific black-box IBR models are preferred in those simulation studies. For small-signal analysis, measurement-based admittance models are necessary. In this paper, we demonstrate the extraction of frequency-domain dq frame IBR models. These linear models are specific to operating conditions. We demonstrate two extraction methods: frequency scan and a step response-based method. The latter relies on converting time-domain responses to Laplace-domain expressions via eigensystem realization analysis (ERA). Both can lead to dq admittance representation and the latter is time saving.

admittance model↗
DOE OSTI2020

Validation of Advanced Photovoltaic Module Materials and Processes by Combined-Accelerated Stress Testing (C-AST)

Tessolar module technology was developed to allow the incorporation of 5 incremental module material innovations. Combined, these innovations may improve the efficiency and durability of the standard silicon cell module. The innovations evaluated are: electrically conductive adhesive (ECA) replacing soldering of tabbing ribbons, light-capturing ribbon (LCR), silicone encapsulant, 2 mm front glass with backsheet, and a polymer-composite module frame. Tessolar-constructed individually encapsulated cells incorporating the material innovations are used to assemble 60-cell modules. 2 x 2 cell mini-modules of the same materials were produced for combined-accelerated stress testing (C-AST). C-AST results demonstrate that the 2 x 2 cell mini-module of Tessolar construction out-performed mini-modules using both ECA with EVA and standard solder with EVA constructions in power production over 108 cycles of testing.

14 SOLAR ENERGY↗