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7/29/2019 44098603 Modelling in High Voltage Equipment
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MODELLING UHF SIGNAL PROPAGATION IN HIGH VOLTAGE
EQUIPMENT
Fahad: [email protected]
Abstract Detecting partial discharges (PD) inside high voltage equipment is apowerful means of insulation diagnosis that can be used for condition
monitoring. One way of doing this is to use ultra high frequency (UHF) sensors
to detect the electromagnetic waves that radiate from the discharge. The case
study will involve the student becoming familiar with; (i) partial discharge
phenomena and (ii) finite difference time domain (FDTD) method of modelling
transient electromagnetic fields. During the subsequent project, the student will
use the software package XF7 to study a range of cases of practical interest and
provide new insight into the challenges of PD detection and location in power
transformers and gas insulated substation (GIS) equipment.
TABLE OF CONTENTS
1. INTRODUCTION ........................................................................................... 2
2. PARTIAL DISCHARGE (PD). ...................................................................... 2
2.1 Methods of measuring PD .............................................................................................................4
2.1.1 Chemical testing of PD ........................................................................................................ ........5
2.1.2 Acoustic testing of PD ...................................................................................................... ......... ..5
2.1.2.1 Ultrasonic testing of PD ............................................................................................................62.1.3 Electrical testing of PD ........................................................................................................ ........8
2.1.4 UHF testing of PD ........................................................................................................................8
3. FINITE DIFFERENCE TIME DOMAIN (FDTD) ............................................. 9
3.1 Theory ...................................................................................................................................... ........ .10
4. MODELLING OF PD USING FDTD ............................................................ 12
Discussion ................................................................................................................................................14
4.1 Simulation Results ................................................................................................................ ......... ..16
5. CONCLUSIONS AND FUTURE WORK ..................................................... 20
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1. IntroductionUHF sensing method of partial discharge (PD) detection in high voltages is fast
attracting vigorous research activities. A theoretical and experimental study of excited
UHF signals in a 132 kV gas insulated substations (GIS) was described by [1]. And a
very sensitive PD detection for GIS equipment in the range of 400 kV has also been
reported in [2, 3]. The major challenge, however, is to try and match the system
frequency response to the high voltage GIS design criteria which might require the
use of an UHF active coupler because most of the PD signal energy is found at higher
frequencies, in order to have the detection cover a wider range of high voltages (132
kV and above). Towards this objective, this project will seek the use XF7 software
package to study various challenging scenarios facing PD detection as well as location
in power transformers and GIS equipment using well known measuring methods such
as the UHF mentioned above and others like the chemical, acoustic and electrical
methods.
2. Partial Discharge (PD).Partial discharges may be defined as small electrical sparks that take place in the
insulation of electrical equipment such as generators, cables, motor windings,
transformers and other switchgear. PD study is particularly of interest to us when
considering sustainable and reliable electric power network operations. Since a
potential PD emerges as a result of an electrical breakdown of a segment within the
insulation, then its analysis method should be measured in a proactive approach by
diagnosing the respective equipment smitten with PD for ensured sustainable
functionality. This is more so the reason PD measurements could be carried out either
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on-line or off-line and periodically or continuously to further predict any need for
future maintenance.
PD measurements are based on breakdown currents caused by erosion of an insulating
materials dielectric strength explained below. Most insulating materials namely
polyethylene, epoxy and polyester do exhibit some kind of dielectric strength
otherwise known as electrical break down strength which is a representation of the
electrical intensity required for current to flow through as well as for discharging the
current. Air when used as an insulating material on the other hand, exhibits a very low
dielectric strength which gives way to a rather extremely brief (fractions of
nanoseconds) passage of current during dielectric breakdown.
Different electrical equipments portray different characteristics when subjected to
different operating conditions. For example, electrical insulations of generators and
motors tend to erode through weakened properties of the epoxy or resins bonding that
coat and insulate the windings when subjected to thermal stresses, chemical attack
and or abrasion to excessive coil movement, resulting in the development of an air
pocket in the windings.
PD are an unwanted phenomena in an electrical power network signalling a wide
range of system malfunction from imminent equipment failure to accelerating the
breakdown process explained above. At instances, ground faults or phase-to-phase
faults could be generated through excessive arcing between ground and live conductor
in the insulation causing its dielectric strength and mechanical texture of the winding
to disintegrate. This may be the starting point of the PD process and could get worse
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considering the global system in which PD tends to spread, inflicting a more serious
damage to a scale of total failure to the entire system or a greater part of it. Although
some PD is harmless, it should be the responsibility of the tester to identify which PD
is harmful and which one is not and to specifically locate the position where the PD
occurs. It has been reported that insulation failure in high voltage levels can cause up
to 90% electrical system failure. This is definitely abominable due to the excessive
costs associated with high voltage equipment and must be avoided through either
conducting on-line or off-line testing. On-line testing may be conducted when in
operation in a normal mode which gives sufficient information as to how the system
has been fairing, whether PD has build up, in which case engineers could take
preventive action and save the system from catastrophic failure by going off-line. This
can save money, time and even lives. With the on-line testing accurate measurements
of the systems performance, accurate assessment of the PD build up as well as the
spread of the PD can easily be ascertained. Off-line testing is often carried out when
the entire system is either down or switched off.
To sum it all, PD could be said to occur when the electric field strength is greater than
the electrical resistive breakdown strength of the insulating material. And should be
tested and identified as early as possible to curb out systems catastrophic failure.
2.1 Methods of measuring PD
On going research has so far identified four ways of measuring partial discharge
named below and are explained in turn:
Chemical
Acoustic
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Electrical
Ultra High Frequency (UHF)
2.1.1 Chemical testing of PD
Activities in PD are evidenced by changes in chemical composition in some particular
phases of the system. Conversely, these changes have been exploited in the detection
of PD activities. For example, liquid insulations often results in developed gaseous
compound usually determined through gas-in-oil analysis. In this process, the
developed fission gases solely depend on the insulation material and its power
density. Precipitation of NOX and ozone concentration is witnessed confirming the
presence of PD activity in an air insulated material due to exposition to chemical
reaction. The main disadvantage of the chemical method lies in its integrative
characteristic which makes it rather difficult to identify the current state of a single
PD in terms of its location, intensity or extent and nature.
2.1.2 Acoustic testing of PD
It is well known fact that most operating equipments produce a broad sound range.
These sounds exhibit high frequency ultrasonic components characterized by short
wave signals which are fairly directional in nature. Therefore, isolating these signals
from background noise and determining their location at a particular instance is a
straightforward matter.
Ultrasonic translators are some kind of airborne ultrasonic instruments capable of
providing a two-way type of information as qualitative or quantitative. Qualitative
type is the ability to hear ultrasounds through noise filtering headphones. Quantitative
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type of information dissemination is carried out through meter readings. This is
accomplished using heterodyning electronic process often adopted by ultrasonic
translators which accurately converts sensed ultrasounds into audible range
recognizable by users through headphones.
It is equally important to be able to hear ultrasounds as it is important to view and
gauge the sonic patterns produced by various equipment. This is the main advantage
of this method as it allows analysts to confirm a diagnosis on the spot by being able to
discriminate among various equipment sounds. The high frequency/short wavelength
nature of ultrasonic signals makes them easy to users to accurately pinpoint their
locations. Humans can sense sounds in the range of 20 Hz ~ 20 kHz with low
frequency sounds in the audible range of about 1.9 cm ~ 17 m long. These tend to be
gross when compared to the sensing pattern of ultrasonic translators operating only
within 0.3 ~ 0.6 cm of length. It can thus be seen that ultrasound wavelengths are far
smaller in magnitude suggesting ultrasonic environment as more conducive for
isolating and locating a source of problems in noisy plat environments.
2.1.2.1 Ultrasonic testing of PD
Ultrasonic testing is especially important in evaluating high voltages exceeding 1000
volts in identifying tracking problems, say, in enclosed switchgear where the tracking
frequency exceeds the fault frequency using infrared thermograph techniques.
Transient current discharges through high voltage lines or across electrical connection
gaps often disturbs the surrounding air molecules and generates ultrasound, normally
perceived as a cracking or frying sound and at times as a buzzing sound. Three basic
electrical problems detectable by ultrasound are:
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Corona effect is the ionization of the surrounding air forming a blue or
purple glow in an electrical conductor, such as an antenna or high voltage
transmission line, when its voltage exceeds some threshold value.
Tracking occurswhen anarc traces the path of damaged insulation, often
referred to as baby arcing.
Arcing is the production of an arc when electricity flows through space such
as occur in lightening process.
Ultrasound testing method is particularly used in detecting for discharges at both
winding ends (phase - phase) and in slot sections (phase - earth). It is also ideal for
high voltage applications such as switchgear, relays, insulators, bus bars, cables,
junction boxes, contactors and substation equipments like transformers and bushings
may as well be tested.
Arcing and corona leakage detection uses similar procedure to that used in detecting
acoustic emissions from mechanical sources. The user listens for cracking or buzzing
sounds rather than listening for rushing or rubbing sound. Generally, an area of
disturbance may be identified and located with a transistor radio or a wide-band
interference locator known as gross detector. A scanning module can then be used to
scan the area globally once a disturbance has been located. The sensitivity of the
module is reduced in the presence of a strong signal to be shown on the meter until
the location of the loudest point.
This method offers a simple means of determining whether a problem exists or not by
comparing sound quality and sound levels among similar equipment which produces
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different tones for envisaged problems. Another advantage is prediction of faults may
be accomplished by an extended period amplitude signals trending.
2.1.3 Electrical testing of PD
In the conventional electrical method, the detection circuit focuses on the capturing of
electrical pulses created by the streamer in the void. It calculates the apparent charge
by measuring and integrating the PD current in the measuring /detecting impedance.
2.1.4 UHF testing of PD
Although it is uncommon to use UHF waves for the detection of PD, however, UHF
detection offers the advantage of localizing the source of discharge as PD occurs
because of sharp geometries created in high voltage insulated equipment. The main
drawback of this method is the extreme sensitivity it offers to external noise.
UHF detection method is particularly applied to large distribution transformers in the
field. In order to avoid sudden failure to neighbouring equipment or cause
unnecessary customer dissatisfaction and economic disruption, it is always important
to determine whether power transformers are suffering from dangerous levels of PD
or from internal arcing.
The use of UHF method was in recent years established as the usual PD measuring
procedure in gas insulated substations (GIS) and increasingly in transformers. The
method is based on the detection of high frequency signals generated in the event of
discharges. PD impulses of momentary duration (< ns) can produce electromagnetic
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waves whose spectrum lies in the GHz range. To this effect, capacitive sensors
resembling antennas have now been developed to detect transient waves.
3. Finite Difference Time Domain (FDTD)Finite difference time domain (FDTD) is a popular computational modelling
technique. It is time domain based and hence can cover a wide range of frequency in a
single simulation run. FDTD methods are of generic class of grid based differential
time domain numerical methods. The time dependent Maxwells equations (in partial
differential form), are descritised using central difference approximations to the space
and time partial derivatives. The resulting finite difference equations are solved in
either software or hardware in a leapfrog manner. The electric field vector
components in a volume of space are solved at a given instant in time, then the
magnetic field vector components in the same spatial volume are solved at the next
instant in time and the process is repeated over and over again until the desired
transient or steady state electromagnetic field behaviour is fully evolved.
Basic FDTD space grid and time stepping algorithm trace back to a seminal paper in
1996 by Kane Yee in IEEE Transaction on Antennas and Propagation [1]. The
descriptor Finite Difference Time Domain and its corresponding FDTD acronym
were originated by Allen Taflove in a 1980 paper in IEEE Transactions on
Electromagnetic Compatibility [2].
Since about 1990, FDTD techniques have emerged as primary means to
computationally model many scientific and engineering problems dealing with
electromagnetic wave interactions with material structures. Current FDTD modelling
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applications range from near DC (ultralow frequency technology involving the entire
earth ionosphere waveguide) through microwaves (radar signature technology,
antennas, wireless communication devices, digital interconnects, biomedical
imaging/treatment) to visible light (photonic crystals, nanoplasmonics, solitons, and
bio photonics) [3]. In 2006, an estimated 2000 FDTD related publications appeared in
the science and engineering literature. In 2008, there were at least 27
commercial/proprietary FDTD software vendors, 8 free software/open source
software FDTD projects and 2 freeware/closed source FDTD projects.
Power transformers are one of the most important and expensive elements of power
system. Severe conditions, such as lightning strikes, switching transients and short
circuits can lead to an immediate failure, especially for aged transformers. Their
insulation strength can degrade to the point that they cannot withstand system events
such as short circuit faults or transient over voltages [1]. Insulation degradation is
frequently linked to PD. The methods of detection of PD are outlined in section 3 with
a report in [2, 3] that one or combination of more than one can be applied.
3.1 Theory
This section presents a brief overview of the FDTD technique for further reading
reference is made to Yee's classic paper [1] and the text by Taflove [2]. In a three-
dimensional FDTD model, magnitudes of the E- and H-fields are stored at points on a
discrete lattice.
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x
zEy
discharge current
Iy(t)
effectivecurrent density
Jy
= Iy
/(x z)
Fig. 1 Discharges can be defined in terms of a current density passing through the
face of a cell in the lattice [9].
TheE- andH- field components are offset in space so that central differencing can be
used to implement Maxwell's equations. An iterative algorithm alternately updates the
EandHarrays with a small time increment t. In rectangular coordinates, distances
between points in the lattice are denoted x, y and z, which are usually made
equal.
Signal propagation through the lattice occurs when a source of electromagnetic
energy is introduced by the appropriate numerical representation. An electrical
discharge current, whose cross-sectional area is smaller than the face of a cell in the
FDTD lattice, can be represented by a current density J, aligned with one of the
electric field components in the lattice. For the example shown in Fig. 1, introducing a
y-directed currentIy(t) requires the following additional operation at each iteration of
the FDTD code:
( )
zx
tItEE
yyy
+
(1)
Where Ey is the y-directed electric field in the cell containing the discharge current
and is the material permittivity at that point. The defined current, flows over one
cell of length y. This approach has been validated for a cylindrical coordinate
system [3].
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A current source in an FDTD model deposits two equal and opposite fixed charges in
the lattice at its end points [4]. If the current source spans a number of adjacent cells,
charge is only deposited at the start and end of the current path, provided that the
currents flowing in each cell are made equal. If one or both ends of the current path
meet the surface of a conducting object, the charge (as represented by electric flux)
that has been created spreads out over the surface of the object in order to satisfy the
boundary conditions. By this means, static fields can be set up within the FDTD
lattice, which might provide the initial conditions for a subsequent fast discharge
event.
4. Modelling of PD using FDTD
The experiment shown in Fig. 2 represents a simple PD detection system. A cell
containing a PD source is mounted inside a hollow cylindrical chamber. The cell
consists of a clear plastic envelope filled with SF6 at a pressure of 100 kPa, within
which a needle (30 mm long) is mounted on the centre pin of a hermetically sealed
50 coaxial connector. An electrode connected to a variable HV supply provides the
potential necessary to electrically stress the needle tip. Current pulses flowing on the
needle are used to trigger the digitizer sweep. Chamber resonances are monitored by
means of an electric field probe, whose output signal is recorded on the same trace by
summing the input channels, A and B. Further details of the PD cell and electric field
probe can be found in [6].
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variable HVAC supply
digitizer UHF amplifier
hollowcylinder
E-field probe
PD source
10 dB
x
z
y
A
B
Fig. 2 Detecting UHF resonances in a cylindrical cavity containing a PD source [9].
For an FDTD simulation of this experiment, the cylindrical cavity was represented on
rectangular lattice with a spacing of 5 mm. Fig.3 shows a cross-section through the
array holding the material permittivity data pertaining to they-component of electric
field. The needle is not represented in this array, but rather is included as a current
source in free space on the axis of the cell. This is achieved by using equation (1) to
incorporate the measured PD current into six cells coincident with the needle position.
Fig. 3 Section through the FDTD lattice atx = 0.3 m in the model of the
experiment shown in Fig. 5. A lattice spacing of 5 mm was used [9].
A typical result for this configuration is shown in Fig. 7, where the amplified output
voltage of the electric field probe is compared with the simulated signal. This requires
a post-processing stage for the FDTD E-field data, using a Fast Fourier Transform
together with a frequency-domain model for the probe transfer function. The resulting
13
z
y
PD current is
y-directedover six celllengths in thisregion
HV cable
plastic cell,
r = 2.6
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voltage must also be scaled to allow for the gain of the UHF amplifier. Although the
signals begin to differ after a few ns (probably due to stair casing effects when the
cylinder is approximated on a rectangular grid), the amplitude of the signal was
modelled quite accurately.
-0.10
-0.05
0
0.05
0.10
0.15
(a) Measured
PD current pulse shape shownhere and below for reference.Peak current is 10.3 mA.
0 5 10 15 20time ( ns )
-0.10
-0.05
0
0.05
0.10
0.15
(b) FDTD
Fig. 4 Comparing the measured (a) and simulated (b) UHF signals excited by PD in
the cylindrical chamber of Fig. 2 [9].
Discussion
Condition monitoring remains a research topic of considerable importance to
electrical utilities. In the field of PD detection, the principal interpretation strategies
are based on analyzing phase or time resolved pulse amplitude patterns. Even when
using sensors that detect discharges by means of emissions at VHF or UHF (such as
in GIS), signals are usually converted to simple pulses, devoid of all high-frequency
content. This approach has been adopted for practical reasons, because multiple signal
paths for the original PD pulse can lead to a very complicated time-domain signal, as
shown in Fig. 5. However, the proliferation of mass-market products such as
computers and mobile communications equipment operating in the UHF band will
reduce the cost of electronic hardware for signal processing at these frequencies. We
may therefore benefit by improving our understanding of the high frequency signals
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radiated by electrical discharges, identifying any high-frequency information that
could be used to characterize and locate insulation defects, or to improve
discrimination between PD signals and external sources of interference. FDTD
models could assist with this process by allowing transient fields to be visualized and
by generating signal data that can be used to test new diagnostic techniques.
HVplant
sensor
PDpulse
multiple
signalpaths
Fig. 5 Signals radiated by PD are influenced by surrounding structures, as well as by
the signal source. This can lead to the generation of complicated time-domain signals
[9].
Another field that could benefit from employing FDTD techniques is experimental
research involving high-speed discharges [7]. In certain experiments, quantities of
interest cannot be measured directly. For example, FDTD models could be used to
study interactions between discharge channels and electrode geometry, as may be
illustrated with reference to Fig. 6. Suppose that we wish to determine the shape of a
fast current pulse during the breakdown of a small gap by measuring the electric field
at the surface of the ground plane a short distance from the test object. The radiated
signal will depend on both the forcing function (the current pulse) and the pattern of
current flow over the experimental apparatus. If the experiment was reproduced in an
FDTD model, it should be possible to determine the time-domain transfer function
relating the voltage output from the remote sensor to the current pulse flowing in the
gap. The impulse response predicted using the model could be used to enable de-
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convolution of the experimentally measured sensor output signal so that the temporal
variation of the source current can be recovered.
4.1 Simulation Results
Figure 7 shows two dimensional simulation results in free space as reconstructed from
[10]. The problem space was divided into 60 x 60 cells and the spread for the
Gaussian pulse in equation (9) is taken as 0.5 ns.
Fig. 7 Ez field after 30 times step with Gaussian pulse at centre
Two dimensional simulation results in free space without PMLis depicted in Figure 8
results have been obtained using the sameGaussian pulse simulated at the centre of
the grid after 100time steps in free space without the absorbing boundaryconditions.
Here the pulse is seen to have reached theboundary and reflected. The contour in Fig.
9 is neitherconcentric nor symmetric about the centre.
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Fig. 8 Ez field after 100 times steps without PML
Fig. 9 Contour of Ez field after 100 time steps without PML
Two dimensional simulation results in free space with PML is shown In Fig. 7 and 8
point PML has been used. Comparison of Fig. 8 and Fig. 10 shows how the
reflections get eliminatedwith PML. The outgoing contour of Fig. 11 is circular and
onlywhen the wave gets within eight points (PML) of the problem space, does the
phase front depart from its circular nature.
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Fig. 10 Ez field after 100 time steps with 8 point PML
Two dimensional simulation results in oil with obstructions is presented below. A real
transformer will contain oil as the insulating mediumand also obstructions like the
winding and core. Here such obstructions are simulated by two representative and
scaleddown circular objects of 6 cm radius centred at (15, 30) and (45, 30).
Fig. 11 Ez field after 100 time steps with 8 point PML
This simple geometry is assumed for verification of the algorithm. An oil medium
with relative permeabilityr= 1, relative permittivity r= 2.2 and conductivity = 0
and the 2 circular obstructions with relative permeability r= 1, relative permittivity
r = 1 and conductivity = 5.8x107 (S/m) representing simplified copper winding
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structure are considered. In Fig. 12 Ez field propagation, with pulse originated at
(30, 30), after 100 time steps is shown. Here the PML is also used. Figure 113 is the
contour of the pulse propagation.
Fig. 12 Contour of Ez field propagation after 100 time steps with pulse at (30, 30) in
oil and circular obstructions centred at (15, 30) and (45, 30)
Fig. 13 Ez field propagation with pulse after 100 time steps at (30, 30) in oil and
obstructions centred at (15, 30) and (45,30).
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5. Conclusions and future work
Results presented in this paper have demonstrated that electrostatic fields can be
generated within an FDTD model and shown how such models might be applied to
the study of electrical discharges through the measurement of radiated signals. Using
FDTD models in parallel with experiments may help to improve the accuracy of
breakdown measurements, as well as assisting with the interpretation of the signals
radiated by partial discharges inside electrical plant. One aim of future work will be to
incorporate models of sensor structures into the lattice so that their interaction with
the electromagnetic fields is taken into account.
HV electrode
dischargeE-fieldsensor
insulatingmedium
Fig. 14 Using an FDTD model in parallel with this experiment could allow the
discharge pulse shape to be measured [9].
Interfacing electromagnetic FDTD models with numerical models of the fundamental
processes in the gap, such as those developed by Morrow [8], may yield new insights
into the overall electromagnetic interactions that occur during electrical breakdown.
Thus, an object could be charged to an initial potential by an artificial pulse in the
FDTD lattice, with the subsequent discharge channel parameters being controlled by
the ionization processes of the insulating medium. These in turn would feed back to
the external field, initiating its collapse and radiation of an electromagnetic transient.
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Subsequently, this project would use the software package XF7 to study a range of
cases of practical interest and provide new insight into the challenges of PD detection
and location in power transformers and gas insulated substation (GIS) equipment.
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References
[1] K S Yee, "Numerical solution of initial boundary value problems involving Maxwell's equations in isotropic
media", IEEE Trans. Antennas and Propagation, Vol. AP-14, No. 3, pp. 302-307, May 1966
[2] A Taflove, Computational electrodynamics The finite-difference time-domain method, Artech House, 1995
[3] M D Judd and O Farish, "FDTD simulation of UHF signals in GIS", Proc. 10th Int. Symp. on High Voltage
Engineering (Montreal), Vol. 6, August 1997
[4] C L Wagner and J B Schneider, "Divergent fields, charge, and capacitance in FDTD simulations", IEEETrans. Microwave Theory and Techniques, Vol. 46, No. 12, pp. 2131-2136, December 1998
[5] M D Judd, O Farish and B F Hampton, "Excitation of UHF signals by partial discharges in GIS", IEEE Trans.Dielectrics and Electrical Insulation, Vol. 3, No. 2, pp. 213-228, April 1996
[6] M D Judd, O Farish and B F Hampton, "Modeling partial discharge excitation of UHF signals in waveguidestructures using Green's functions", IEE Proc. Science, Measurement and Technology, Vol. 143, No. 1, pp. 63-70,
1996
[7] A R Dick, S J MacGregor, M T Buttram, R C Pate, L F Rinehart and K R Prestwich, "Breakdown phenomena
in ultra-fast plasma closing switches", Proc. 12th IEEE Int. Pulsed Power Conf., pp. 1149-1152, 1999
[8] R Morrow, "Properties of streamers and streamer channels in SF6", Physical Review A, Vol. 35, No. 4,
pp. 1778 - 1785, February 1987
[9] M.D. Judd, Using Finite Difference Time Domain Techniques to Model Electrical Discharge Phenomena,
Annual report conference on electrical insulations and Dielectric Phenomena, Vol. 2 pp 518 521, October 2000.[10] C. Abraham and S.V. Kulkarni, FDTD Simulated Propagation of Electromagnetic Pulses due to PD forTransformer Diagnostics