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At least 1,243 records · Page 69

Vacuum arc behavior and its voltage characteristics in drawing process controlled by composite magnetic fields along axial and transverse directions

In this research, drawing vacuum arc (VA) experiments were conducted using composite contacts under currents ranging from 5 kA to 20 kA root mean square (rms). The new type of contact comprised an axial magnetic field (AMF) configuration and a transverse magnetic field (TMF) configuration. The TMF plate was in the center, surrounded by the AMF plate. The contact generated both AMFs and TMFs simultaneously. VA appearances and arc voltages were recorded, and the VA was modeled as a conductor for electromagnetic force analysis in ANSYS software. The results showed that the coaxiality of operating mechanisms significantly influenced arc behavior just as the arc was ignited. When arc brightness did not increase after ignition, there was a voltage drop accompanied with diffusion of the VA. As to VA development, when an arc was ignited on an AMF plate, it spread on the plate and rotated. Over time the arc current increased, the constricting arc forms, and the arc column rotated on the TMF plate under the action of Ampere's force. With regard to the influence of a magnetic field on a VA at different stages, in the initial drawing arc stage the TMF was dominant, and the arc started to rotate under the action of Ampere's force. Afterwards, the AMF was dominant, with a steadily burning arc. As for contact melting, in the initial arcing period, a contracted short arc caused severe melting and erosion of the contact plate. When the ignition spot or root was close to the slot of plate, the electromagnetic force pushed the arc toward slot and contact edge, resulting in local erosion of the slot region.

42 ENGINEERING↗

Structural insights into binding of STAC proteins to voltage-gated calcium channels

Excitation–contraction (EC) coupling in skeletal muscle requires functional and mechanical coupling between L-type voltage-gated calcium channels (Ca V 1.1) and the ryanodine receptor (RyR1). Recently, STAC3 was identified as an essential protein for EC coupling and is part of a group of three proteins that can bind and modulate L-type voltage-gated calcium channels. Here, we report crystal structures of tandem-SH3 domains of different STAC isoforms up to 1.2-Å resolution. These form a rigid interaction through a conserved interdomain interface. We identify the linker connecting transmembrane repeats II and III in two different Ca V isoforms as a binding site for the SH3 domains and report a crystal structure of the complex with the STAC2 isoform. Here, the interaction site includes the location for a disease variant in STAC3 that has been linked to Native American myopathy (NAM). Introducing the mutation does not cause misfolding of the SH3 domains, but abolishes the interaction. Disruption of the interaction via mutations in the II–III loop perturbs skeletal muscle EC coupling, but preserves the ability of STAC3 to slow down inactivation of Ca V 1.2.

59 BASIC BIOLOGICAL SCIENCES↗

Voltage cycling process for the electroconversion of biomass-derived polyols

Electrification of chemical reactions is crucial to fundamentally transform our society that is still heavily dependent on fossil resources and unsustainable practices. In addition, electrochemistry-based approaches offer a unique way of catalyzing reactions by the fast and continuous alteration of applied potentials, unlike traditional thermal processes. In this work, we show how the continuous cyclic application of electrode potential allows Pt nanoparticles to electrooxidize biomass-derived polyols with turnover frequency improved by orders of magnitude compared with the usual rates at fixed potential conditions. Moreover, secondary alcohol oxidation is enhanced, with a ketoses-to-aldoses ratio increased up to sixfold. The idea has been translated into the construction of a symmetric single-compartment system in a two-electrode configuration. Its operation via voltage cycling demonstrates high-rate sorbitol electrolysis with the formation of H 2 as a desired coproduct at operating voltages below 1.4 V. The devised method presents a potential approach to using renewable electricity to drive chemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cavallo's multiplier for in situ generation of high voltage

Here, a classic electrostatic induction machine, Cavallo's multiplier, is suggested for in situ production of very high voltage in cryogenic environments. The device is suitable for generating a large electrostatic field under conditions of very small load current. Operation of the Cavallo multiplier is analyzed, with quantitative description in terms of mutual capacitances between electrodes in the system. A demonstration apparatus was constructed, and measured voltages are compared to predictions based on measured capacitances in the system. The simplicity of the Cavallo multiplier makes it amenable to electrostatic analysis using finite element software, and electrode shapes can be optimized to take advantage of a high dielectric strength medium such as liquid helium. A design study is presented for a Cavallo multiplier in a large-scale, cryogenic experiment to measure the neutron electric dipole moment.

47 OTHER INSTRUMENTATION↗

The High Voltage distribution system of the ATLAS Tile Calorimeter and its performance during data taking

This study documents the characteristics of the high voltage (HV) system of the hadronic calorimeter TileCal of the ATLAS experiment. Such a system is suitable to supply reliable power distribution into particles physics detectors using a large number of PhotoMultiplier Tubes (PMTs). Measurements performed during the 2015 and 2016 data taking periods of the ATLAS detector show that its performance, in terms of stability and noise, fits the specifications. In particular, almost all the PMTs show a voltage instability smaller than 0.5 V corresponding to a gain stability better than 0.5%. A small amount of channels was found not working correctly. To diagnose the origin of such defects, the results of the HV measurements were compared to those obtained using a Laser system. The analysis shows that less than 0.2% of the about 10 thousand HV channels were malfunctioning.

47 OTHER INSTRUMENTATION↗

Wideband precision stabilization of the -18.6kV retarding voltage for the KATRIN spectrometer

The Karlsruhe Tritium Neutrino Experiment (KATRIN) measures the effective electron anti-neutrino mass with an unprecedented design sensitivity of 0.2 eV (90 % C.L.). In this experiment, the energy spectrum of beta electrons near the tritium decay endpoint is analyzed with a highly accurate spectrometer. To reach the KATRIN sensitivity target, the retarding voltage of this spectrometer must be stable to the ppm (1 × 10 -6 ) level and well known on various time scales (μs up to months), for values around -18.6 kV. A custom-designed high-voltage regulation system mitigates the impact of interference sources in the absence of a closed electric shield around the large spectrometer vessel. In this article, we describe the regulation system and its integration into the KATRIN setup. Independent monitoring methods demonstrate a stability within 2 ppm, exceeding KATRIN's specifications.

47 OTHER INSTRUMENTATION↗

Modular Isolated Soft-Switching Medium Voltage String Inverter for Large-Scale PV Farm

This paper presents a single-stage modular isolated soft-switching medium voltage string inverter (MVSI) with tri-port configuration to interconnect PV and storage to medium voltage (MV) grid. The modular MVSI provides advanced functionalities such as energy storage elements integration without additional converters, connection to MV grid resulting in lower distribution losses in the PV farm, high-frequency galvanic isolation, independent control of PV, storage and grid power, high modularity and scalability. The topology of the MVSI, operation principle and model-predictive priority-switching (MPPS) control to achieve fast dynamic balancing across stacked modules are discussed. The independent power control is validated in PLECS simulation and the operation of stacked MVSI with MPPS control is verified through Hardware-in-the-loop (HIL) simulation. Here, the hardware prototype of 25 kVA MVSI building block is developed. 18 kW experimental results of single building block verifying tri-ports operation and 20 kW experimental results of two modules stacked operation are presented. A clean sinusoidal waveform with negligibly low THD in both tests is obtained. A low dv/dt of <; 1kV/us and soft-switching are achieved.

30 DIRECT ENERGY CONVERSION↗

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗

Comprehensive Efficiency Analysis of Seven-Switch Current-Source Inverter Based on Voltage-Boost Function and Genetic Algorithm

This paper investigates the voltage-boost features of the emerging seven-switch current-source inverter (H7-CSI) to improve the efficiency of the CSI-based motor drive system. The switching transient and power loss model of the H7-CSI topology during voltage-boost operation are analyzed in detail. The effects of the boost function on the switching and conduction loss of the H7-CSI topology are investigated. A genetic algorithm has been introduced that makes it possible to optimize the H7-CSI’s modulation index to minimize its power loss. Experimental results for the H7-CSI unit show that this optimization can reduce the power loss by 10.6%.

42 ENGINEERING↗

Techno-Economic Analysis for Grid Edge Intelligence: A Preliminary Study on Smart Voltage Regulator Controls

Grid edge intelligence has been of interest in both industrial and academic research spaces as the penetration level of distributed energy resources increases. This paper discusses the application of a framework that can perform techno-economic analyses for integrating intelligent autonomous controls into the distribution grid. The framework has been used to provide cost-benefit studies for two smart voltage regulator control algorithms that come as black-box applications. These applications are evaluated within the framework using quasistatic time-series simulations. Results are presented in terms of performance metrics and costs incurred for these two smart voltage regulator control techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Time Sequence Machine Learning-Based Data Intrusion Detection for Smart Voltage Source Converter-Enabled Power Grid

Smart inverters of distributed energy resources can enable cloud computing, condition monitoring, result visualization, remote control, and peer-to-peer energy trading in advanced power systems. However, the advent of data injection attacks in the communication architecture can alter measurement characteristics of power grids and have devastating consequences. In this article, we propose a time sequence machine learning-based anomaly detection methodology for detecting cyber intrusion into control signal setpoints and dc voltage signal measurement bias of the voltage source converter (VSC) in wind generators. We first investigated the effects of four types of denial of service, tampering signal, and stealthy-type data intrusion attacks on smart VSCs and overall wind farms. We then proposed a novel time sequence machine learning-based intrusion detection framework that can be implemented to detect different cyberattacks in the VSCs. The performance of the proposed framework has been compared with that of autoencoder and clustering-based intrusion detection framework. The proposed framework was validated by using the IEEE 39 bus power system in the presence of four wind farms in different locations. Using several metrics for intrusion detection performance, we validated the effectiveness of the proposed framework.

42 ENGINEERING↗

Equalization of Intensity-Modulated Fiber-Optic Voltage Sensors for Power Distribution Systems

We test fiber-optic voltage sensors based on optical reflection from a piezoelectric transducer. Our specific devices possess a 2 kHz fundamental resonance, and we verify a readily usable frequency band from approximately 10 Hz to 3 kHz, with a dynamic range of 60 dB for a detection system integrating over this entire band. Additionally, we demonstrate a digital signal processing approach to equalize the measured frequency response, enabling accurate retrieval of short-pulse inputs. These results suggest the value and applicability of intensity-modulated fiber-optic voltage sensors for measuring both steady-state waveforms and broadband transients which, coupled with the straightforward and compact design of the sensors, should make them effective tools in electric grid monitoring.

42 ENGINEERING↗

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops a machine learning based approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurement. The machine learning model is developed by using random forest algorithm. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

advanced metering infrastructure↗

Load Shedding for Voltage Regulation With Probabilistic Agent Compliance

With the increased observability and controllability of distribution systems, the share of behind-the-meter systems is trending upwards rapidly. As a consequence, the impact of human behaviors on system performance can no longer be ignored and should be reflected in the energy management system models. In this paper, we discuss the problem of distribution system voltage control by active power curtailment where the agent compliance of the load curtailment signal is probabilistic. We discuss the modeling of the optimal voltage control problem with probabilistic agent compliance as a chance-constrained optimization problem, its tractable safe approximation using convex restriction, and a scenario-based mixed-integer reformulation as well as the associated solution method based on augmented Lagrangian method. The numerical simulation on IEEE test system validates the effectiveness of the proposed approach in obtaining high-quality feasible load curtailment signal with low computational cost, which makes it a viable tool for real time decision making.

augmented Lagrangian method↗

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a two-agent soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak demand reduction. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operations to enhance control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment and reduce peak load demand from feeder's head.

deep reinforcement learning↗

A Voltage Inference Framework for Real-Time Observability in Active Distribution Grids

Active distribution grids are gaining traction to meet the growing environmental, socio-economic, and sustainability targets. Various advanced smart grid technologies facilitate the integration of Distributed Energy Resources (DERs) by supporting the bi-directional power flow. The limited observability of distribution grids, primarily related to their location at the very edge of power system infrastructure, brings challenges to optimal grid management. Moreover, only a limited number of measurements at regular intervals are usually available. This paper presents a novel inference framework, referred to as “Voltage Inference”, to overcome the observability issues. The proposed framework employs a prediction step based on the Multivariate Taylor series approximation, followed by a corrector step that minimizes the estimation error to infer the otherwise unknown voltages from the available measurements. Furthermore, numerical results on the IEEE 13-bus test feeder validate the accuracy and computational performance of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Online Model-Free Chance-Constrained Distribution System Voltage Control Using DERs

This paper proposes an online data-driven distributed energy resource management system (DERMS) optimization method using chance-constrained formulation to address distribution system voltage regulation. This is achieved via the local sensitivity factor (LSF)-enabled reformulation of the DER control into a linear programming (LP) problem, which is easy and computationally efficient to solve. The LSF is estimated using online measurements and does not need the assumption of node load information. The latter is usually required for existing optimization-based methods but is difficult to obtain in practice. To mitigate measurement uncertainties, a scenario-based chance-constrained formulation is constructed. Compared with other control methods, the results carried out in a realistic distribution system show that the proposed method can effectively eliminate voltage violation issues.

chance-constrained optimization↗

Voltage-Matched Strings using 3-Terminal Tandems: Fundamentals and End Losses

Strings constructed from 3-terminal tandem (3TT) cells can provide some of the performance benefits of voltage-matching with less cell complexity than strings based on 4-terminal tandem cells. However, the circuitry for a 3TT string can become more complex, making circuit analysis more challenging. Here we illustrate the essential features of single-polarity voltage-matched (VM) 3TT strings using representative examples. End losses are intrinsic to this type of string, but can be reduced by minimizing m and n in the Vtop/Vbot VM ratio m/n, and further mitigated by increasing the string length. This analysis agrees with preliminary experimental results.

3TT↗