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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25

Deadband Voltage Control and Power Buffering for Extreme Fast Charging Station

Voltage fluctuation is one of the most common challenges that electric vehicle charging station (EVCS) may introduce to the power grid. Local reactive power compensation (Q-compensation) capability of bi-directional electric vehicle (EV) chargers can mitigate the steady-state voltage violations caused by the EV charging itself or changes in the neighboring loads. Power buffering, using energy storage system (ESS), can be utilized to address the voltage transients (sags and swells) as a result of EV charging at the EVCS. To address PI controller’s ‘hunting’ issue, this paper proposes a Q-sign triggered deadband voltage control (V-control) method at the point of common coupling (PCC). In addition, to ensure the ramp rate of EV charging is within the allowable limits set forth by the grid code, a ramp rate control is proposed that uses the ESS as a ‘power buffer’. Lastly, different from most reported work in the literature where no explicit limit of the power electronic converters (PECs) is considered, this work considers a reasonable apparent power capacity limit of the PECs when achieving the V-control. This limit also affects the amount of active power that can be obtained from the grid, and subsequently may require ESS to function as ‘load sharing’ device to provide supplemental active power to satisfy EV load. A case study simulated in MATLAB (interfaced with PLECS) is presented to demonstrate the effectiveness of the proposed approaches for EVCS operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Wind turbine performance enhancement with minimal structural load penalty: A design philosophy

The performance benefits of using tip devices on wind turbines has been well-documented. However, previous studies show that adding blade tip devices such as winglets leads to a significant increase in blade root bending moment, potentially requiring structural reinforcement with cost and weight drawbacks. A new and unique design philosophy for retrofit blade tip devices for wind turbines is presented. By balancing generated aerodynamic and centrifugal loads, these devices offer an increase in power production without the need for structural reinforcement. Predicted performance and cost benefits of using retrofit blade tip devices on the National Renewable Energy Laboratory 5 MW reference wind turbine are shown. Finally, the addition of blade tip devices resulted in significant improvements in the coefficient of power (C p ) and annual energy production (AEP).

17 WIND ENERGY↗

MODELING, IMPLEMENTATION AND CONTROL OF A CVT BASED PTO FOR A SMALL SCALE MHK-TURBINE IN LOW FLOW SPEED OPERATION

Modeling, implementation, field testing and control of a power takeoff (PTO) device equipped with a ball-type continuously variable transmission (B-CVT) for a small marine hydrokinetic (MHK) turbine deployed from a floating unmanned autonomous mobile catamaran platform is described. The turbine is a partially submerged multi-blade undershot waterwheel (USWW). A validated numerical torque model for the MHK turbine has been derived and a speed controller has been developed, implemented and tested in the field. The dependance of the power generated as a function of number and submergence level of turbine blades has been investigated and the number of blades that maximizes power production is determined. Bench and field testing in support of characterizing the power conversion capabilities of MHK turbine and PTO are described. Detailed results of the final torque and power coefficient models, the controls architecture, and the MHK turbine performance with varying numbers of blades are provided.

Pimentel, Hugo↗

The Role of SnO2 Processing on Ionic Distribution in Double-Cation-Double Halide Perovskites

Moving toward a future of efficient, accessible, and less carbon-reliant energy devices has been at the forefront of energy research innovations for the past 30 years. Metal-halide perovskite (MHP) thin films have gained significant attention due to their flexibility of device applications and tunable capabilities for improving power conversion efficiency. Serving as a gateway to optimize device performance, consideration must be given to chemical synthesis processing techniques. Therefore, how does common substrate processing techniques influence the behavior of MHP phenomena such as ion migration and strain? Here, we demonstrate how a hybrid approach of chemical bath deposition (CBD) and nanoparticle SnO2 substrate processing significantly improves the performance of (FAPbI3)0.97(MAPbBr3)0.03 by reducing micro-strain in the SnO2 lattice, allowing distribution of K+ from K-Cl treatment of substrates to passivate defects formed at the interface and produce higher current in light and dark environments. X-ray diffraction reveals differences in lattice strain behavior with respect to SnO2 substrate processing methods. Through use of conductive atomic force microscopy (c-AFM), conductivity is measured spatially with MHP morphology, showing higher generation of current in both light and dark conditions for films with hybrid processing. Additionally, time-of-flight secondary ionization mass spectrometry (ToF-SIMS) observed the distribution of K+ at the perovskite/SnO2 interface, indicating K+ passivation of defects to improve the power conversion efficiency (PCE) and device stability. We show how understanding the role of ion distribution at the SnO2 and perovskite interface can help reduce the creating of defects and promote a more efficient MHP device.

conductive atomic force microscopy↗

Wave energy conversion incorporating actuated geometry

Described herein are wave energy conversion systems including actuated geometry components. An example system may include at least one body portion configured to transfer wave energy to a power take off device, and at least one actuated geometry component that is connected to the at least one body portion, the at least one actuated geometry component operable to modify a geometric profile of the system.

16 TIDAL AND WAVE POWER↗

Validation of Microgrid Algorithms using At-Scale Simulation and Emulation Real-Time (ASSERT) Framework

This paper presents a novel framework for validating microgrid algorithms using a At-Scale Simulation and Emulation Real-Time (ASSERT) setup. The proposed universal microgrid validation framework was developed at Advanced Research on Integrated Energy Systems (ARIES) platform at National Renewable Energy Laboratory in Golden, Colorado, USA. As the number of intercommunicating devices grow in power systems, along with more integration of inverter-based resources, developing and validating microgrid operation and control algorithms is becoming complex and time-consuming task. The ASSERT framework is designed to provide a comprehensive, accurate, and efficient solution for validating microgrid algorithms. It combines at-scale simulations and real-time emulation to create a virtual environment that closely mimics the behavior of a physical microgrids which are characteristic of future smart distribution systems, such as: (1) increasing variability in the physical size of new energy technologies; (2) requiring control large numbers of interconnected devices, and (3) integrating diverse technologies that have not previously worked together. The paper describes the technical details of the ASSERT framework, its validation process, and its benefits over traditional validation methods. The framework's ability to validate the performance of various algorithms is demonstrated through a case study, which shows that it can effectively identify the weaknesses of an algorithm and optimize its performance. Overall, the ASSERT framework is a promising tool that can significantly enhance the development and validation of microgrid algorithms, leading to more reliable and efficient microgrid operation.

at-scale↗

Merged-Element Transmon

Transmon qubits are ubiquitous in the pursuit of quantum computing using superconducting circuits. However, they have some drawbacks that still need to be addressed. Most importantly, the scalability of transmons is limited by the large device footprint needed to reduce the participation of the lossy capacitive parts of the circuit. In this work, we investigate and evaluate losses in an alternative device geometry, namely, the merged-element transmon (mergemon). To this end, we replace the large external shunt capacitor of a traditional transmon with the intrinsic capacitance of a Josephson junction and achieve an approximately 100 times reduction in qubit dimensions. We report the implementation of the mergemon using a sputtered Nb–amorphous-Si–Nb trilayer film. In an experiment below 10 mK, the frequency of the readout resonator, capacitively coupled to the mergemon, exhibits a qubit-state-dependent shift in the low-power regime. The device also demonstrates the single-photon and multiphoton transitions that represent a weakly anharmonic system in two-tone spectroscopy. The transition spectra are explained well with master-equation simulations. Here, a participation-ratio analysis identifies the dielectric loss of the amorphous-Si tunnel barrier and its interfaces as the dominant source for qubit relaxation. We expect the mergemon to achieve high coherence for relatively small device dimensions when implemented with a low-loss, epitaxially grown, and lattice-matched trilayer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Tantalum alloy–based resonators for quantum information systems

Utilizing tantalum (Ta) in superconducting circuits has led to significant improvements, such as high qubit lifetime (T 1 ) and quality factors in both qubits and resonators, suggesting that material optimization plays an important role in the development of superconducting circuits. Thus we here explore superconducting gap engineering in Ta-based devices as a powerful strategy for expanding the range of suitable host materials. By alloying 20 atomic percent (at.%) hafnium into Ta thin films, we achieve a superconducting transition temperature (T c ) of 6.09 K as observed in direct current (DC) transport measurements, reflecting an increase in the superconducting gap. We systematically vary deposition conditions to control film orientation and transport properties of Ta-Hf alloy thin films. We then confirm the enhancement in T c via microwave measurements at millikelvin temperatures. We verify the ~40 increase in T c relative to bare Ta devices, while the loss contributions from two-level systems and quasi-particles remain unchanged in the low temperature regime. These findings emphasize the promise of material engineering in superconducting circuits and point to many potential material candidates for further exploration.

Ta-Hf alloy thin films↗

In-situ measurement of irradiation behavior in LiNbO 3

In-situ measurement of LiNbO 3 based surface acoustic wave (SAW) crystal resonator device under irradiation was demonstrated and used to characterize the impact of radiation on physical properties of this material. The resonant frequency of the SAW device was monitored as the output power of the reactor was varied. Upon step increase of the reactor power, a gradual shift in the device’s resonant frequency was observed. This frequency shift initially exhibits a linear growth and eventually reaches an equilibrium value proportional to the reactor power. The observed behavior can be attributed to two competing processes: increase of temperature due to gamma heating or accumulation of irradiation induced defects. In both cases, the response is attributed to changes in the physical properties of LiNbO 3 , particularly the elastic constants. This demonstrated ability to measure materials properties under irradiation is attractive for development of sensors and performing materials science under irradiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Double-null power-sharing dynamics in MAST-U

Maintaining an effective double-null (DN) configuration is expected to be challenging in reactor-scale tokamak devices. As divertor power-sharing is closely linked to the magnetic topology, even minor variations can lead to fast power-sharing fluctuations which exacerbate the already daunting exhaust challenge. While the static aspects of DN power-sharing have been extensively studied across various devices, this paper presents the first detailed investigation of its dynamic behaviour. We employ dedicated H-mode experiments in MAST-U, in Super-X divertor configuration, featuring perturbation frequencies up to 200 Hz. Our results clearly show no significant dynamic damping of the power-sharing within this frequency range: the divertor responds equally to both fast and slow perturbations. Moreover, the dynamic response also aligns with quasi-static results from slow ramps, implying that static power-sharing models remain valid even for fast fluctuations. Occasionally, some deviations from the otherwise mainly linear behaviour are observed, alongside notable scatter and asymmetries between upwards and downwards trajectories. These observations are likely linked to changes in core conditions, though the underlying mechanisms remain unclear and require further study.

divertor↗

Port Impedance Measurement and Current Injection Response Analysis for PLCs

Programmable Logic Controllers (PLCs) are used to control devices throughout the power system since they have fast control capabilities and can utilize multiple types of communication interfaces. Therefore, studying and mitigating their vulnerabilities to electromagnetic pulse is important for the reliability of PLC operations. Here, in this paper, an effective impedance measurement scheme is proposed and demonstrated for three PLCs to estimate their susceptibility to an electromagnetic pulse. The equivalent non-uniform transmission line model is established to eliminate the impact of the fixture in the de-embedding process. Then different parameters of the impedance measurement setup are explored. Based on the measured impedance, the equivalent circuit is established to calculate the response of the device when subjected to the electromagnetic pulse. The voltage and current responses of different interfaces are compared utilizing the developed pulsed Current Injection (CI) method. Finally, the impedance measurement scheme is verified through testing using three measuring instruments. And the CI simulation experiments reveal the characteristics and susceptibilities of different PLCs interfaces, indicating that some protection measures are required for the reliable operation of the PLC.

42 ENGINEERING↗

Benchmarking Quantum Chemistry Computations with Variational, Imaginary Time Evolution, and Krylov Space Solver Algorithms

Quantum chemistry is a key application area for noisy-intermediate scale quantum (NISQ) devices, and therefore serves as an important benchmark for current and future quantum computer performance. Previous benchmarks in this field have focused on variational methods for computing ground and excited states of various molecules, including a benchmarking suite focused on the performance of computing ground states for alkali-hydrides under an array of error mitigation methods. State-of-the-art methods to reach chemical accuracy in hybrid quantum-classical electronic structure calculations of alkali hydride molecules on NISQ devices from IBM are outlined here. Here it is demonstrated how to extend the reach of variational eigensolvers with symmetry preserving Ansätze. Next, it is outlined how to use quantum imaginary time evolution and Lanczos as a complementary method to variational techniques, highlighting the advantages of each approach. Finally, a new error mitigation method is demonstrated which uses systematic error cancellation via hidden inverse gate constructions, improving the performance of typical variational algorithms. These results show that electronic structure calculations have advanced rapidly, to routine chemical accuracy for simple molecules, from their inception on quantum computers a few short years ago, and they point to further rapid progress to larger molecules as the power of NISQ devices grows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗

Protection System Validation Using Post-Event Anomaly Classification with Machine Learning

Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Protection System Validation with Machine Learning Anomaly Classification

A poster for the Early Career Poster Session. Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Thermal conductivity of rutile germanium dioxide

Power electronics seek to improve power conversion of devices by utilizing materials with a wide bandgap, high carrier mobility, and high thermal conductivity. Due to its wide bandgap of 4.5 eV, b-Ga 2 O 3 has received much attention for high-voltage electronic device research. However, it suffers from inefficient thermal conduction that originates from its low-symmetry crystal structure. Rutile germanium oxide (r-GeO 2 ) has been identified as an alternative ultra-wide-bandgap (4.68 eV) semiconductor with predicted high electron mobility and ambipolar dopability; however, its thermal conductivity is unknown. Here, we characterize the thermal conductivity of r-GeO 2 as a function of temperature by first-principles calculations, experimental synthesis, and thermal characterization. The calculations predict an anisotropic phonon-limited thermal conductivity for r-GeO 2 of 37W m –1 K –1 along the a direction and 58W m –1 K –1 along the c direction at 300K where the phonon-limited thermal conductivity predominantly occurs via the acoustic modes. Experimentally, we measured the value of 51W m –1 K –1 at 300K for hot-pressed, polycrystalline r-GeO2 pellets. The measured value is close to our directionally averaged theoretical value, and the temperature dependence of ~1/T is also consistent with our theory prediction, indicating that thermal transport in our r-GeO 2 samples at room temperature and above is governed by phonon scattering. Furthermore, our results reveal that high-symmetry UWBG materials, such as r-GeO 2 , may be the key to efficient power electronics.

36 MATERIALS SCIENCE↗

Post-Event Fault Identification with Machine Learning for Protection System Validation

Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by accidental improper relay settings or deliberate malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that their performance falls within expectations. Relays that fail to isolate a fault or trip when there is no system disturbance can be flagged for settings review in situations where this behavior may not have been noticed due to manual restoration or backup protection operations. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by identifying fault events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Smart Meter Pinging and Reading Through AMI Two-Way Communication Networks to Monitor Grid Edge Devices and DERs

Today’s power distribution system is changing to a power-electronics-enabled distribution system, especially with the increasing penetration of distributed energy resources (DERs). To monitor and manage those electronic devices and DERs at the grid edge, the advanced metering infrastructure (AMI) with two-way communications presents great potential. At present, extensive research explores the upstream communication from smart meters to electric utilities (e.g., meter reading) but few examine the downstream communication from the utilities to smart meters (e.g., meter pinging). This article discusses the AMI two-way communication and its recent industrial practice in the U.S., especially for applying the smart meter pinging functionality to monitor grid-edge devices and DERs. This paper then develops the two-way communication model and the network calculus method to quantify the impact of the two-way communication on the AMI network. In the end, the proposed method is validated with ns-3 simulation using the modified 13-node test feeder and real-world feeder systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗