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At least 19 records

Dynamic consensus and extended high gain observers as a tool to achieve practical frequency synchronization in power systems under unknown time-varying power demand

In this paper, we consider the frequency synchronization problem in a network of lossless, connected, and network-reduced power system. Frequency synchronization is an important problem in power systems as frequency deviation can lead to degraded power quality, tripping of generators, etc. We present a load-estimator-based consensus algorithm in a network of fourth-order generator models that achieves practical frequency synchronization in the presence of unknown time-varying power demand. We do not assume that the demand is generated by a known model. We follow a multiple time-scale approach for the stability analysis. It is shown that synchronization is achieved for the case of constant power demand, by showing that the system is exponentially stable. Furthermore, for the case of time-varying power demand, we show the error trajectories are ultimately bounded, and the synchronization error is proportional to an upper bound on the derivative of the time-varying power demand. We simulate the controller performance on a four area network which is equivalent to the IEEE New England 39-Bus system.

42 ENGINEERING↗

Improving scalability of parallel CNN training by adaptively adjusting parameter update frequency

Synchronous SGD with data parallelism, the most popular parallelization strategy for CNN training, suffers from the expensive communication cost of averaging gradients among all workers. The iterative parameter updates of SGD cause frequent communications and it becomes the performance bottleneck. In this paper, we propose a lazy parameter update algorithm that adaptively adjusts the parameter update frequency to address the expensive communication cost issue. Our algorithm accumulates the gradients if the difference of the accumulated gradients and the latest gradients is sufficiently small. Here, the less frequent parameter updates reduce the per-iteration communication cost while maintaining the model accuracy. Our experimental results demonstrate that the lazy update method remarkably improves the scalability while maintaining the model accuracy. For ResNet50 training on ImageNet, the proposed algorithm achieves a significantly higher speedup (739.6 on 2048 Cori KNL nodes) as compared to the vanilla synchronous SGD (276.6) while the model accuracy is almost not affected (<0.2% difference).

97 MATHEMATICS AND COMPUTING↗

Grid Forming Control Tuning for a Hybrid Inverter-Based Resource Power Plant

A hybrid inverter-based resource (IBR) power plant consists of grid-following (GFL) and grid-forming inverter-based resources (GFM-IBR) connected in parallel. Here, this research focuses on how to design and tune GFM's control parameters to ensure stable operation of the hybrid power plant for weak and strong grid conditions. We consider two design cases: one where the GFL-IBR does not provide frequency support, and one where it does. It is found that the GFM's power-frequency synchronizing system can lose stability when the power-frequency droop constant is large and/or the grid is strong. Additionally, if the GFL has its frequency support enabled, oscillation stability worsens. To explain the mechanism of the interactions, we construct a feedback system for the synchronizing loop, which consists of the GFM's power-frequency droop control that generates the GFM's synchronizing angle, the GFL's phase-locked loop that measures the voltage phase angle, the GFL's frequency-power control that generates its power order, and the rest of the system. The feedback system is effective in illustrating the potential stability risks. Successful design ensures that the hybrid power plant can operate smoothly and ride through grid disturbances.

feedback systems↗

Empirical Evaluation of GPS Clock Accuracy for Isochronous Droop-Based Inverters: Preprint

Grid-forming inverters rely upon an internal reference to regulate the grid’s voltage and frequency. Without a reliable reference, issues such as loss of synchronism, frequency instability, and unequal power sharing can occur. One proposed internal phase reference for grid-forming inverters is generated by the controller’s clock, but this is affected by nonidealities in the crystal oscillator leading to time drift in the phase reference. To improve the controller’s clock accuracy, the Global Positioning System (GPS) can be used to calibrate the internal clock. Previously, GPS-based clock calibration was explored theoretically and various methods were developed for mitigating frequency/phase drift at the power system level. This paper experimentally validates the direct performance of GPS time-calibration at the controller level and justifies its use in maintaining an accurate phase reference for droop-based grid-forming inverters.

clock drift↗

Empirical Evaluation of GPS Clock Accuracy for Isochronous Droop-based Inverters

Grid-forming inverters rely upon an internal reference to regulate the grid 's voltage and frequency. Without a reliable reference, issues such as loss of synchronism, frequency instability, and unequal power sharing can occur. One proposed internal phase reference for grid-forming inverters is generated by the controller's clock, but this is affected by nonidealities in the crystal oscillator leading to time drift in the phase reference. To improve the controller's clock accuracy, the Global Positioning System (GPS) can be used to calibrate the internal clock. Previously, GPS-based clock calibration was explored theoretically and various methods were developed for mitigating frequency/phase drift at the power system level. This paper experimentally validates the direct performance of GPS time-calibration at the controller level and justifies its use in maintaining an accurate phase reference for droop-based grid-forming inverters.

clock drift↗

Injection locking and coupling dynamics in superconducting nanowire-based cryogenic oscillators

Oscillators designed to function at cryogenic temperatures play a critical role in superconducting electronics and quantum computing by providing stable, low-noise signals with minimal energy loss. Here, in this work, we present a comprehensive numerical study of injection locking and mutual coupling dynamics in superconducting nanowire (ScNW)-based cryogenic oscillators. Using the design space of a standalone ScNW-based oscillator, we investigate two critical mechanisms that govern frequency synchronization and signal coordination in cryogenic computing architectures: (1) injection locking induced by an external AC signal with a frequency near the oscillator's natural frequency, and (2) the mutual coupling dynamics between two ScNW oscillators under varying coupling strengths. We identify key design parameters—such as shunt resistance, nanowire inductance, and coupling strength—that govern the locking range. Additionally, we examine how the amplitude of the injected signal affects the amplitude of the locked oscillation, offering valuable insights for power-aware oscillator synchronization. Furthermore, we analyze mutual synchronization between coupled ScNW oscillators using capacitive and resistive coupling elements. Our results reveal that the phase difference between oscillators can be controlled by tuning the coupling strength, enabling programmable phase-encoded information processing. These findings could enable building ScNW-based oscillatory neural networks, synchronized cryogenic logic blocks, and on-chip cryogenic resonator arrays.

Artificial neural networks↗

Synchronous High-frequency Distributed Readout For Edge Processing At The Fermilab Main Injector And Recycler

The Main Injector (MI) was commissioned using data acquisition systems developed for the Fermilab Main Ring in the 1980s. New VME-based instrumentation was commissioned in 2006 for beam loss monitors (BLM)[2], which provided a more systematic study of the machine and improved displays of routine operation. However, current projects are demanding more data and at a faster rate from this aging hardware. One such project, Real-time Edge AI for Distributed Systems (READS), requires the high-frequency, low-latency collection of synchronized BLM readings from around the approximately two-mile accelerator complex. Significant work has been done to develop new hardware to monitor the VME backplane and broadcast BLM measurements over Ethernet, while not disrupting the existing operations critical functions of the BLM system. This paper will detail the design, implementation, and testing of this parallel data pathway.

43 PARTICLE ACCELERATORS↗

Using Disorder to Overcome Disorder: A Mechanism for Frequency and Phase Synchronization of Diode Laser Arrays

Noise and disorder are known, in certain circumstances and for certain systems, to improve the level of coherence over that of the noise-free system. Examples include cases in which disorder enhances response to periodic signals, and those where it suppresses chaotic behavior. We report a new type of disorder-enhancing mechanism, observed in a model that describes the dynamics of external cavity-coupled semiconductor laser arrays, where disorder of one type mitigates (and overcomes) the desynchronization effects due to a different disorder source. Here, we demonstrate stabilization of dynamical states due to frequency locking and subsequently frequency locking-induced phase locking. Here, we have reduced the equations to a potential model that illustrates the mechanism behind the misalignment-induced frequency and phase synchronization.

42 ENGINEERING↗

Timestamp Error Detection and Estimation for PMU Data based on Linear Correlation between Relative Phase Angle and Frequency

Time synchronization is essential to synchro-phasor-based applications. However, Timestamp Error (TE) in synchrophasor data can result in application failures. This paper proposes a method for TE detection based on the linear correlation between frequency and relative phase angle. The TE converts the short-term relative phase angle from noise-like signal to one that linear with the frequency. Pearson Correlation Coefficient (PCC) is applied to measure the linear correlation and then detect the timestamp error. The time error is estimated based on the variation of frequency and relative phase angle. Case studies with actual synchrophasor data demonstrate the effectiveness of TE detection and excellent accuracy of TE estimation.

Yu, Wenpeng↗

Vulnerability of a VOC-Based Inverter Due to Noise Injection and Its Mitigation

Even though virtual oscillator control (VOC)-based inverters do not communicate with each other, they need to make local measurements for control. The impact of tampering with these measured or sensed signals on the performance of a VOC-based inverter and synchronization of multiple such inverters is an important but open-ended issue. As such, this letter explores the impact of intentional side-channel noise intrusion (SNI) on the synchronization of VOC-based communication-free self-synchronizing inverters (CFSIs). Two different scenarios are investigated via experimental and analytical studies using a half-bridge neutral point clamped (NPC) single-phase CFSI. Furthermore, they address the impact of SNI on the ability of a CFSI to ensure a stable 60-Hz limit cycle and on the parallel operation of two such CFSIs to ensure synchronism to a common 60-Hz load frequency.

42 ENGINEERING↗

Study of synchronous RF pulsing in dual frequency capacitively coupled plasma

Low-pressure multi-frequency capacitively coupled plasmas (CCPs) are used for numerous etch and deposition applications in the semiconductor industry. Pulsing of the radio-frequency (RF) sources enables control of neutral and charged species in the plasma on a millisecond timescale. The synchronous (i.e. simultaneous, in-phase) pulsing of both power sources in a dual frequency CCP is examined in this article. Due to the low gas pressure, modeling has been done using the electrostatic particle-in-cell/Monte Carlo collision method. Here, the objective of this work is to investigate the sensitivity of the plasma properties to small changes in timing during synchronous pulsing of the two RF sources. It is demonstrated that small deviations in the on and off times of the two RF sources can lead to major changes in the plasma characteristics. This high sensitivity is of concern for process repeatability but can be utilized to enable better control of the dynamics of plasma-surface interaction. In the simulations, the pulsing parameters (on and off times and ramp rates) are varied and the temporal evolution of plasma characteristics such as electron density (n e ), species current at the electrode, and electron temperature are examined. It is demonstrated that if the low-frequency (LF) source is turned off a few μs before (or after) the high-frequency source, n e during the off-state is significantly higher (or lower) due to the frequency coupling effect. Similarly, turning on the LF source with a small delay results in a sharp increase in the plasma density when the RF sources are turned on.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Joint scheduling of energy, fast and primary frequency response reserves in integrated transmission–distribution networks

Inverter-based distributed energy resources (DERs) connected to distribution networks (DNs) can provide fast frequency support, but their reserve deliverability depends on feeder constraints and differs from synchronous primary frequency response (PFR). Existing transmission–distribution coordination studies usually treat reserve generically or neglect feeder-level feasibility, while frequency-security scheduling studies rarely represent distribution feeders explicitly. This paper develops a bi-level day-ahead scheduling framework for integrated transmission–distribution networks that jointly clears energy, transmission-side PFR, and distribution-side fast frequency response (FFR) under exogenous hourly inertia and largest-loss inputs from an external unit commitment (UC) schedule. The transmission problem is modeled with DC-optimal power flow (OPF) and closed-form second-order cone (SOC) frequency-security constraints, whereas each DN is represented by a reserve-aware branch-flow AC-OPF so that scheduled fast reserves remain deliverable during activation. The bi-level problem is reformulated through Karush–Kuhn–Tucker (KKT) conditions into a mixed-integer SOC program, and a penalty term is used to tighten the distribution-network relaxation. In the reduced test system, lower exogenous inertia increased the required primary response from 179.64 MW to 191.08 MW, distribution-side fast response reduced total frequency-response procurement by up to 4.9%, and neglecting distribution constraints overstated the combined distribution-side energy and reserve award by up to 18%. In the expanded study, the largest case was solved in 2.02 s with a 0.00% optimality gap. Time-domain simulations kept the frequency nadir above 59.0 Hz in all tested hours. These results demonstrate the value of fast-response modeling and distribution-feasible reserve delivery in coordinated market clearing.

Noh, Seung-Gil↗

Hierarchical Power Flow Control in Smart Grids: Enhancing Rotor Angle and Frequency Stability with Demand-Side Flexibility

Large-scale integration of renewables in power systems gives rise to new challenges for keeping synchronization and frequency stability in volatile and uncertain power flow states. To ensure the safety of operation, the system must maintain adequate disturbance rejection capability at the time scales of both rotor angle and system frequency dynamics. This calls for flexibility to be exploited on both the generation and demand sides, compensating volatility and ensuring stability at the two separate time scales. This article proposes a hierarchical power flow control architecture that involves both transmission and distribution networks as well as individual buildings to enhance both small-signal rotor angle stability and frequency stability of the transmission network. The proposed architecture consists of a transmission-level optimizer enhancing system damping ratios, a distribution-level controller following transmission commands and providing frequency support, and a building-level scheduler accounting for quality of service and following the distribution-level targets. Furthermore, we validate the feasibility and performance of the whole control architecture through real-time hardware-in-loop tests involving real-world transmission and distribution network models along with real devices at the Stone Edge Farm Microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Resonant amplification of enzymatic chemical oscillations by oscillating flow

Using theory and simulation, we analyzed the resonant amplification of chemical oscillations that occur due to externally imposed oscillatory fluid flows. The chemical reactions are promoted by two enzyme-coated patches located sequentially on the inner surface of a pipe that transports the enclosed chemical solution. In the case of diffusion-limited systems, the period of oscillations in chemical reaction networks is determined by the rate of the chemical transport, which is diffusive in nature and, therefore, can be effectively accelerated by the imposed fluid flows. In this work, we first identify the natural frequencies of the chemical oscillations in the unperturbed reaction–diffusion system and, then, use the frequencies as a forcing input to drive the system to resonance. We demonstrate that flow-induced resonance can be used to amplify the amplitude of the chemical oscillations and to synchronize their frequency to the external forcing. In particular, we show that even 10% perturbations in the flow velocities can double the amplitude of the resulting chemical oscillations. Particularly, effective control can be achieved for the two-step chemical reactions where during the first half-period, the fluid flow accelerates the chemical flux toward the second catalytic patch, while during the second half-period, the flow amplifies the flux to the first patch. The results can provide design rules for regulating the dynamics of coupled reaction–diffusion processes and can facilitate the development of chemical reaction networks that act as chemical clocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NIR fluorescence lifetime macroscopic imaging with a time-gated SPAD camera

The performance of SwissSPAD2 (SS2), a large scale, widefield time-gated CMOS SPAD imager developed for fluorescence lifetime imaging, has recently been described in the context of visible range and fluorescence lifetime imaging microscopy (FLIM) of dyes with lifetimes in the 2.5 – 4 ns range. Here, we explore its capabilities in the NIR regime relevant for small animal imaging, where its sensitivity is lower and typical NIR fluorescent dye lifetimes are much shorter (1 ns or less). We carry out this study in a simple macroscopic imaging setup based on a compact NIR picosecond pulsed laser, an engineered diffuser-based illumination optics, and NIR optimized imaging lens suitable for well-plate or small animal imaging. Because laser repetition rates can vary between models, but the synchronization signal frequency accepted by SS2 is fixed to 20 MHz, we first checked that a simple frequency-division scheme enables data recording for different laser repetition rates. Next, we acquired data using different time gate widths, including gates with duration longer than the laser period, and analyzed the resulting data using both standard nonlinear least-square fit (NLSF) and phasor analysis. We show that the fixed synchronization rate and large gate widths characterizing SS2 (10 ns and over) are not an obstacle to accurately extracting lifetime in the 1 ns range and to distinguishing between close lifetimes. As a result, SS2 and similar very large gated SPAD imagers appear as a versatile alternative to other widefield time-resolved detectors for NIR fluorescence lifetime imaging, including preclinical molecular applications.

FLIM↗

Performance Evaluation of a Microgrid System with Grid-Forming and Grid-Following Inverters with Diesel Generators: Insights From Hardware Experiments

This paper presents a comprehensive performance evaluation of a microgrid system integrating grid-forming (GFM) inverters, grid-following (GFL) inverters, and a diesel generator, focusing on their interactions and behavior under various dynamic events. The study is conducted using a pure hardware setup comprising two GFM inverters, one GFL inverter, a diesel generator, load banks, a point of common coupling (PCC), and an emulated main grid. The evaluation specifically examines dynamic scenarios, including voltage jumps, phase jumps, rate of change of frequency (ROCOF), synchronization, and islanding operations, which pose critical challenges to system stability. Among all the tests conducted, the overloading and phase jump tests proved to be the most challenging. The capacity of the DC side is crucial for withstanding overloading and grid disturbance tests; otherwise, GFM inverters frequently trip due to DC undervoltage. Throughout all grid disturbance tests, the diesel generator consistently stands out as the most robust and reliable GFM unit in the system. Overall, insights from these hardware experiments shed light on the response characteristics of different generation types during grid disturbances and identify potential stability concerns in such hybrid microgrid systems.

14 SOLAR ENERGY↗

Power System Event Classification and Localization Using a Convolutional Neural Network

Detection and timely identification of power system disturbances are essential for situation awareness and reliable electricity grid operation. Because records of actual events in the system are limited, ensemble simulation-based events are needed to provide adequate data for building event-detection models through deep learning; e.g., a convolutional neural network (CNN). An ensemble numerical simulation-based training data set have been generated through dynamic simulations performed on the Polish system with various types of faults in different locations. Such data augmentation is proven to be able to provide adequate data for deep learning. The synchronous generators’ frequency signals are used and encoded into images for developing and evaluating CNN models for classification of fault types and locations. With a time-domain stacked image set as the benchmark, two different time-series encoding approaches, i.e., wavelet decomposition-based frequency-domain stacking and polar coordinate system-based Gramian Angular Field (GAF) stacking, are also adopted to evaluate and compare the CNN model performance and applicability. The various encoding approaches are suitable for different fault types and spatial zonation. With optimized settings of the developed CNN models, the classification and localization accuracies can go beyond 84 and 91%, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗