Progress In Electromagnetics Research Symposium Proceedings, Cambridge, USA, July 5–8, 2010
1013
Detection of Partial Discharge inside of HV Transformer, Modeling,
Sensors and Measurement
P. Fiala, T. Jirku, P. Drexler, and P. Dohnal
Brno, FEEC BUT, UTEE, Kolejnı́ 2906/4, Brno 612 00, Czech Republic
Abstract— The aim of this paper is to present the particulars of result research in the HF
measurement method and modeling of starting process partial discharge inside of high voltage
transformer. The numerical analysis of the electromagnetic wave attenuation helped to set up
conditions to decrease it and get of information for sensors conception preparing and detection
apparatuses construction and measurement methods.
1. INTRODUCTION
One of the problematic conditions in the field of high-voltage technology, apparatuses and devices
(machines) consists in the emergence of partial discharges [1]. At this point, let us also note that
several other effects have combined with this notion over time [2–4]. In consequence of these
effects there emerge short electromagnetic pulses with a defined and measurable spectrum in the
characteristic frequency band [5]. The group of end products attributable to the emergence of
interfering signals involves, for example, displacement current in a dielectric, pulse current on the
interface between dielectrics, or the dielectric/metal interface owing to high electric field intensity
and structure of the dielectric. In HV and VHV transformers the dielectric is mineral or synthetic
oil.
Large distribution transformers are constructed in such a manner as to have structural measures
facilitating oil purification. Also, these transformers are equipped with sensors indicating the initial
stage of increase in pulse activity. In the course of this activity, as is well-known, there occurs an
increase in the boundary value of the of the applied dielectric breakdown value. As referred to in
the above text, oil is the dielectric. Under certain conditions, however, the separation of chemical
compounds incurred by decomposition of the dielectric does not have to occur. Thus, free atoms
of carbon, hydrogen and oxygen develop from hydrocarbons, and there also generates a certain
percentage of water, other organic compounds, and semiconductive carbon. All of these elements
decrease the quality of the dielectric; in addition to that, rapid increase in pulse activity may cause
the formation of a hazardous explosive compound of oxygen and hydrogen. Then, this situation
may result in a local explosion, damage to the device and reduction of its ability to perform the
respective functions.
This work deals next steps after the analysis of electromagnetic field distribution in a transformer
dielectric region. The structural parts enable the placement and choice of sensors, whose structure
and concept must be adapted to the characteristics of the configuration in such a manner that,
from all components of the device, there is a measurable (indicable) electromagnetic impulse signal.
The analysis will be realized for the minimum required level of an electromagnetic pulse for the
discrete values of frequencies from the desired spectral interval. An example will be evaluated of
electromagnetic field distribution in the region of critical parts of the device.
2. MATHEMATICAL MODEL
It is possible to carry out an analysis of an MG model as a numerical solution by means of the
Finite element method (FEM). The electromagnetic part of the model is based on the solution of
full Maxwell’s equations
∂B
∂D
, ∇ × H = σE +
+ Js , ∇ · D = ρ, ∇ · B = 0 in Ω.
(1)
∂t
∂t
where E and H are the electrical field intensity vector and the magnetic field intensity vector, D
and B are the electrical field density vector and the magnetic flux density vector, Js is the current
density vector of the sources, ρ is the density of free electrical charge, γ is the conductivity of the
material and Ω is the definition area of the model. The relationships between the electric and the
magnetic field intensities and densities are given by material relationships
∇×E=−
D = εE,
B = µH.
The numerical model analysis was described in paper [8].
(2)
PIERS Proceedings, Cambridge, USA, July 5–8, 2010
1014
3. TYPES OF SENSORS
The sensors of electromagnetic field were described in report [9]. Tests of antennas are prepared
according Fig. 1, described in paper [1] and [5]. Results of numerical model analysis are presented
in Fig. 3. The real position of antennas is shown in Fig. 2. There were tested three types of
antennas. The first one was spiral types, Fig. 4. The frequency range for spiral antennas was from
500 MHz to 3.5 GHz. The SWR diagram was tested in anechoic chamber and it is shown in Fig. 5.
The second type of antenna was based on cone design, Fig. 6, the SWR diagram is shown in Fig. 7.
The last type of antenna was design like a Vivaldi. The used material of them was PCB of FR-4,
Fig. 8.
Figure 1: The sensor tests.
teflon boxes
Figure 2: Detector position.
Modul Electric Intensity
Attenuation [dB]
Frequency Characteristics
Low
0,0
-10,0
-20,0
-30,0
-40,0
-50,0
-60,0
-70,0
-80,0
-90,0
Upper
average
Minimal electronic
sensitivity
Frequency [MHz]
Figure 3: Numerical model analysis result of Electric intensity attenuation inside of HV transformer.
Progress In Electromagnetics Research Symposium Proceedings, Cambridge, USA, July 5–8, 2010
1015
Figure 4: Spiral antenna for f ∈ h500; 3500i MHz.
Figure 5: The SWR diagram of spiral antenna.
Figure 6: Cone type antenna design for f ∈
h500; 3500i MHz.
Figure 7: The SWR diagram of cone type antenna.
Figure 8: The Vivaldi antenna design for f ∈
h500; 3500i MHz.
Figure 9: The SWR diagram of Vivaldi type antenna.
4. CONCLUSION
The basic research of the numerical model HF wide band signals inside of a VHV transformer has
brought a considerable sum of experience in the field of signals and possibilities of their measurement
and detection. It was used for sensor design conception and construction. There were tested three
types of antenas and it was prepared next step of partial discharge detection.
ACKNOWLEDGMENT
The research described in the paper was financially supported by FRVŠ (a fund of university
development) by research plan No. MSM 0021630513 ELCOM, No. MSM 0021630516 and grant
Czech ministry of industry and trade MPO No. FR-TI1/001, GACR 102/09/0314.
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