278 research outputs found
Prediction of switching transients in high voltage air-insulated substations
Describes the process of prediction of switching transients in high voltage air-insulated substations
Time domain analysis of switching transient fields in high voltage substations
Switching operations of circuit breakers and disconnect switches generate transient currents propagating along the substation busbars. At the moment of switching, the busbars temporarily acts as antennae radiating transient electromagnetic fields within the substations. The radiated fields may interfere and disrupt normal operations of electronic equipment used within the substation for measurement, control and communication purposes. Hence there is the need to fully characterise the substation electromagnetic environment as early as the design stage of substation planning and operation to ensure safe operations of the electronic equipment. This paper deals with the computation of transient electromagnetic fields due to switching within a high voltage air-insulated substation (AIS) using the finite difference time domain (FDTD) metho
Monitoring contamination level on insulator materials under dry condition with a microwave reflectometer
Current techniques used for monitoring the levels of contamination on high voltage insulators, such as leakage current and infrared, are not effective in dry conditions since they require the surface of the insulator to be wetted by fog, rain or snow. If a buildup of contamination occurs during a prolonged dry period prior to a weather change there will be a significant risk that flashover may occur before there is time to implement preventative maintenance. Previous work has demonstrated the use of microwave radiometry to determine the levels of contamination on an insulator material under dry conditions, however practical applications are limited by low sensitivity. This paper reports the development of a novel technique based on microwave reflectometry to detect the power levels reflected from the surface of the insulator material. The level of contamination is then determined as a function of received power. A theoretical model establishes the relationship between equivalent salt deposit density levels on insulator surface and the dielectric properties of the contamination layer. A Finite Difference Time Domain (FDTD) model is used to simulate the total loss as a function of the contamination level. Experimental results verify the FDTD model and demonstrate the sensitivity of the reflectometer system to be approximately 100 times greater than the radiometer system. Therefore, the reflectometry system has considerably greater potential for practical applications to provide advance warning of the future failure of insulators under dry conditions for both HVDC and HVAC systems
Feasibility study on application of microwave radiometry to monitor contamination level on insulator materials
This paper introduces a novel method for monitoring contamination levels on high voltage insulators based on microwave radiometry. Present contamination monitoring solutions for high voltage insulators are only effective in predicting flashover risk when the contamination layer has been wetted by rain, fog or condensation. The challenge comes where the pollution occurs during a dry period prior to a weather change. Under these conditions, flashover can often occur within a short time period after wetting and is not predicted by measurements taken in the dry period. The microwave radiometer system described in this paper measures energy emitted from the contamination layer and could provide a safe, reliable, contactless monitoring method that is effective under dry conditions. The relationship between equivalent salt deposit density and radiometer output is described using a theoretical model and experimentally verified using a specially designed X-band radiometer. Results demonstrate that the output from the radiometer is able to clearly distinguish between different levels of contamination on insulator materials under dry conditions. This novel contamination monitoring method could potentially provide advance warning of the future failure of wet insulators in climates where insulators can experience dry conditions for extended periods
Radio Location of Partial Discharge Sources: A Support Vector Regression Approach
Partial discharge (PD) can provide a useful forewarning of asset failure in electricity substations. A significant proportion of assets are susceptible to PD due to incipient weakness in their dielectrics. This paper examines a low cost approach for uninterrupted monitoring of PD using a network of inexpensive radio sensors to sample the spatial patterns of PD received signal strength. Machine learning techniques are proposed for localisation of PD sources. Specifically, two models based on Support Vector Machines (SVMs) are developed: Support Vector Regression (SVR) and Least-Squares Support Vector Regression (LSSVR). These models construct an explicit regression surface in a high dimensional feature space for function estimation. Their performance is compared to that of artificial neural network (ANN) models. The results show that both SVR and LSSVR methods are superior to ANNs in accuracy. LSSVR approach is particularly recommended as practical alternative for PD source localisation due to it low complexity
Azimuthal anisotropy at RHIC: the first and fourth harmonics
We report the first observations of the first harmonic (directed flow, v_1),
and the fourth harmonic (v_4), in the azimuthal distribution of particles with
respect to the reaction plane in Au+Au collisions at the Relativistic Heavy Ion
Collider (RHIC). Both measurements were done taking advantage of the large
elliptic flow (v_2) generated at RHIC. From the correlation of v_2 with v_1 it
is determined that v_2 is positive, or {\it in-plane}. The integrated v_4 is
about a factor of 10 smaller than v_2. For the sixth (v_6) and eighth (v_8)
harmonics upper limits on the magnitudes are reported.Comment: 6 pages with 3 figures, as accepted for Phys. Rev. Letters The data
tables are at
http://www.star.bnl.gov/central/publications/pubDetail.php?id=3
Pion, kaon, proton and anti-proton transverse momentum distributions from p+p and d+Au collisions at GeV
Identified mid-rapidity particle spectra of , , and
from 200 GeV p+p and d+Au collisions are reported. A
time-of-flight detector based on multi-gap resistive plate chamber technology
is used for particle identification. The particle-species dependence of the
Cronin effect is observed to be significantly smaller than that at lower
energies. The ratio of the nuclear modification factor () between
protons and charged hadrons () in the transverse momentum
range GeV/c is measured to be
(stat)(syst) in minimum-bias collisions and shows little
centrality dependence. The yield ratio of in minimum-bias d+Au
collisions is found to be a factor of 2 lower than that in Au+Au collisions,
indicating that the Cronin effect alone is not enough to account for the
relative baryon enhancement observed in heavy ion collisions at RHIC.Comment: 6 pages, 4 figures, 1 table. We extended the pion spectra from
transverse momentum 1.8 GeV/c to 3. GeV/
Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events
The - oscillation frequency has been measured with a sample of
23 million \B\bar B pairs collected with the BABAR detector at the PEP-II
asymmetric B Factory at SLAC. In this sample, we select events in which both B
mesons decay semileptonically and use the charge of the leptons to identify the
flavor of each B meson. A simultaneous fit to the decay time difference
distributions for opposite- and same-sign dilepton events gives ps.Comment: 7 pages, 1 figure, submitted to Physical Review Letter
Role of genetic testing for inherited prostate cancer risk: Philadelphia prostate cancer consensus conference 2017
Purpose: Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-dri
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