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The 3rd National Graduate Conference (NatGrad2015), Universiti Tenaga Nasional, Putrajaya Campus, 8-9 April 2015.
Analysis and Characterization of Partial Discharge
Signals From Instrument Transformer in Noisy
Environment
Chong Yu Ping. Email: [email protected]
Chua Chun Piau. Email: [email protected]
Yasmin Hanum Md Thayoob. Email: [email protected]
Syed Khaleel Ahmed. Email: [email protected]
College of Engineering, Universiti Tenaga Nasional, Malaysia.
Yogendra A/L Balasubramaniam
Department of Transformer Diagnosis, TNB Research SDN. BHD, Malaysia. Email: [email protected]
Abstract—Partial Discharge (PD) detection is one of the
important methods used to evaluate the insulation condition of
in-services high voltage electrical equipment. On-site PD
detection methods are preferable compared to others method
because non-intrusive sensors are easy to install and have no
interruptions on operation. An electrical PD testing utilizing
High Frequency Current Transformer (HFCT) installed at the
ground terminal of the instrument transformer was used to
detect partial discharge activities. However, the limitation of this
method is the measurement often lacks of accuracy due to
interference in PD. The PD signals are hard to distinguish from
the stochastic noise pulses. Therefore, the characteristics of PD
signals and interferences signals are studied in Phase Resolved
Partial Discharge (PRPD) pattern in order to identify the extent
of PD signals.
Keywords—partial
discharge;
instrument
transformer;
inteferences; phase resolved partial discharge pattern
I.
INTRODUCTION
Instrument transformers (IT) are high accuracy electrical
devices that designed to transform voltage or current from the
high values to low values in the transmission and distribution
systems that can be utilized by low voltage metering devices
[1]. It also can be used to isolate the utilization current or
voltage from the supply voltage for safety to both the operator
and the end device in use [2]. IT primary functions are used to
metering for energy billing and transaction purposes and
protection control for system protection and protective relaying
purposes in transmission and distribution system. IT plays an
important role in electrical system. Therefore, condition
assessment of in-service high voltage instrument transformer
should be carried out to determine failures in IT. Partial
detection (PD) detection is one of the important methods used
to monitor and evaluate the condition of in-service high voltage
electrical equipment. Online partial discharge testing is
performed during real operating condition with normal
operating voltage. This is a non-destructive test; therefore nonintrusive sensors which are easy to install and have no
interruptions on operation are preferred for on-site PD
detection. An electrical PD test utilizing High Frequency
Current Transformer (HFCT) installed at the ground terminal
of the instrument transformer was used to detect partial
discharge activities [3].
As defined by IEC60270, ‘Partial discharge is a localized
electrical discharge that only partially bridges the insulation
between conductors and which can or cannot occur adjacent to
a conductor [4]. PD usually started within voids and cracks.
Since PDs are limited to only a portion of the insulation, the
discharges only partially bridge the distance between
electrodes. PD can also occur along the boundary between
different insulating materials. The electric field across the void
is significantly higher than that across an equivalent distance of
dielectric due to the dielectric constant of the void is
considerably less than the surrounding dielectric. If the voltage
stress across the void is increased above the corona inception
voltage (CIV) for the gas within the void, PD activity will start
within the void [5].
PD detection is using to monitor the status of IT; however,
PD measurement performed on-site and under noisy condition
is a challenging task. The measurement often lacks of accuracy
due to interference in PD signals [6]. The PD signal is
superposed with stochastic noise pulses or even multiple PD
sources, which leads to a complex phase resolved PD patterns
that is not easy to analyse and distinguish. Therefore,
characteristics of PD and noise are studied in order to
differentiate by using phase resolved partial discharge (PRPD)
pattern.
According to IEEE standard (IEEE Std C57.113-2010) that
the possible noise could be encountered from on-site
measurement such as harmonics, radio frequency (RF) noise,
corona and sparking that can be generated by several kinds of
sources [7]. Analysis of possible interferences pattern is
essential to distinguish PD pattern from interferences pattern
by using PRPD pattern.
II.
PHASE RESOLVED PARTIAL DISCHARGE (PRPD)
In PRPD, the phase of occurrence, apparent charge and
number of PDs which has the same phase and magnitude can
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The 3rd National Graduate Conference (NatGrad2015), Universiti Tenaga Nasional, Putrajaya Campus, 8-9 April 2015.
be recorded. For data recording purpose, usually an m × n
matrix is used where m is the number of phase channels and n
is the number of charge levels [8]. Each element of this matrix
shows the number of PDs with a particular magnitude and
phase. This method can provide different patterns such as the
phase of occurrence (φ) versus the number of PD (n), the
phase of occurrence (φ) versus the maximum apparent
charge(qm), the phase of occurrence (φ) versus the average
apparent charge (qa) and the apparent charge (q) versus the
number of discharge (n).
Furthermore, the second typical characteristic to review is
that PD activity is increasing at beginning of each half cycle
followed by decreasing like bell-shaped curve as shown in
Fig. 2. There is no article or journal draw conclusion about the
pattern of PD shall increase at beginning followed by
decreasing in PRPD pattern. However, it is easily to see this
trend in many published papers about PD in [6, 12-13].
Therefore, these characteristics can be used to further analysis
the PRPD pattern obtained from HFCTs.
A. PD Pattern Characteristics
There are some common phenomena or characteristics of
partial discharge in PRPD diagram, such as PD pulses shall
occur only in both first and third quadrants in PRPD diagram,
PD pulses shall abrupt increase at beginning of first and third
quadrants followed by rapid decrease and number of PD pulses
in first and third quadrants shall not have big difference.
Up till now, there is no article or journal that can draw any
conclusion on the partial discharge on instrument transformer.
However, it has been accepted that the partial discharge could
appear on both first and third quadrants. It is not possible for
PD to take place in either first or third quadrants only as PD
shall take place in both first and third quadrants simultaneously
[1-2, 5]. Furthermore, “characteristic traits of partial discharges
occur only during the first and third quarter of each cycle”, as
stated in [9]. Therefore this characteristic can be applied on
partial discharge recognition analysis.
In Fig. 1, PD occurs when voltage across the void, V1
reaches the breakdown voltage, Vi. Voltage V1 reduces until
the discharge extinguishes. Then, rises again as applied
voltage, V is rising until new breakdown occurs again. This
situation repeats again and again, eventually the breakdown of
insulation system [10]. Therefore, PD occurs only in positive
and negative half cycles in PRPD pattern, where initial rising
of positive signal and initial rising of negative signal. This
behavior can use to further justify the occurrence of PD.
Fig. 2. Typical PD pattern in Phase Resolved PD pattern
B. PD Parameters and Determine the Extent of PD activity
In PRPD analysis, PD parameters such as PD magnitude
and PD count are very important to determine the extent of
partial discharge activity. Apparent charge (q), repetition rate
and number of pulses (n) with respect to the phase angle (θ)
were recorded when measuring the PD activity. PD magnitude
usually measured in picoCouloumb (pC) while PD count is the
number of occurrence of PD in one second duration. There are
no standard for PD magnitude and PD count to determine the
extent of PD. However, there are concerns for the safety of the
insulation system if the PD magnitude and PD count are high.
Disturbance might have contributed to high value of the PD
parameters.
According to a journal conducted by V. R. Garcia-Colon
and his partners that the apparent charge that over a reading,
which 300 pC were considered as abnormal and over 1000 pC
was considered as extremely high and immediate actions
recommended [14]. Therefore 300 pC would be the trigger
value used for apparent charge in this experiment. There might
be some concerns when the PD magnitude is exceeds 300 pC
but the transformer still can function properly. When the PD is
exceeds 1000 pC, the IT needed to be test offline by using
DGA that is a published method to be used to determine the
extends of the partial discharge.
III.
Fig. 1. Sequence of cavity breakdown under alternating voltages: (a) voltage
waveforms and (b) PD Pulses [11]
NOISE IN E LECTRICAL PD DETECTION
Noise can be classified into two groups, which are nonimpulsive noise and impulsive noise. Non-impulsive noise
consists of white noise, which generated from any electrical
equipment, such as amplifier and oscilloscope; Harmonic
signal, which are generated from communication, wireless and
electronics systems. However, impulsive noise can be divided
into two groups, which are repetitive pulses and random pulse.
Repetitive pulses are generated from Corona and switching
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devices, such as AC/DC converter and rectifier. Random pulse
is generated from lightning impulses, switching operations,
welding, and sparking.
According to IEEE standard (IEEE Std C57.113-2010) that
the possible noise could be encountered such as harmonics,
radio frequency (RF) noise, corona and sparking [7]. The
characteristic noise signature was shown in Fig. 3. Fig. 3(a)
refers to corona discharge; it can be easily being identified
because corona discharge appears only in one half cycle of
applied voltage after exceeding the inception voltage. Fig. 3(b)
refers sparks between metallic parts; faulty metallic contact
may happen inside or outside the CTs due to corrosion and this
discharge pulse repetition rate is significantly higher.
Signatures of external interference such as noise caused by
power electronics and radio noises were shown in Fig. 3(c).
The pulses caused by power electronics can easily being
identified because the pulses have equally spaced and roughly
same amplitude.
site PD data has been tested with DGA test and it shows
satisfactory condition, which are KL405, KL136 and Perak205.
Fig. 4 shows the PD pattern of experimental data in PRPD
pattern. It can be seen that the PD patterns of experimental data
occur in first and third quadrant in Fig. 4. PD activity is
increasing at beginning of first and third quadrant, and
followed by decreasing trend. It is not clear to see this tendency
in Fig. 4 (d), because PD signal has been covered up by noise
signal, but it is easy to see this tendency in (a), (b) and (c).
Therefore, the results from Fig. 4 have been proven that the
occurrence of PD can be recognized by using PD pattern
recognition, which recognize based on typical characteristics of
PD in PRPD pattern.
Fig. 3. PD pattern of experimental data in PRPD pattern: (a) exp132332 (b)
exp150246 (c) exp154523 (d) exp153818
Fig.5 illustrates the possible noise identified from the
PRPD measurement data from KL North Bay 405 which are in
accordance with the possible noise that can exist in an on-site
PD measurement that was stipulated by the IEEE Standard.
The possible noises have been identified based on Fig. 3 that
referred to IEEE Standard [7]. Hence, it is necessary to filter
the noise in the on-site PD measurement data before any
further diagnosis can be made on the severity of the PD
occurrence and determination of the PD level.
Fig. 3 Signatures of electromagnetic interferences encountered during PD
tests [7]
IV. RESULT AND DISCUSSION
Data to be analyzed consist of four known experimental
data (named as exp132332, exp150246, exp154523 and
exp153818), three known and four unknown site data from onsite PD measurement (named as KL405, KL505, KL136,
PenangL25, PenangL55, Seremban405 and Perak205). Four
known experimental data are recorded under different
situations, which are high PD activity without noise, low PD
activity without noise, high PD activity with noise and low PD
activity with noise accordingly. However, the three known on-
Fig. 5 Noise identification on KL North Bay 405
Results from unknown defect site data are justified by PD
pattern recognition. Hence, the results obtained have indicated
that there are insufficient evidences to determine there are PD
activities. As summary, three known and four unknown site
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The 3rd National Graduate Conference (NatGrad2015), Universiti Tenaga Nasional, Putrajaya Campus, 8-9 April 2015.
data from on-site PD measurement (named as KL405, KL505,
KL136, PenangL25, PenangL55, Seremban405 and Perak205)
are failed to fulfill the criteria to prove that there are PD
activities.
V.
[3]
[4]
[5]
CONCLUSION
In conclusion, partial discharge (PD) detection is an
important method to evaluate the insulation condition of an
instrument transformer (IT). Electrical partial discharge
measurement using high frequency current transformer (HFCT)
is an alternative technique for PD detection as PD
measurement can be done on in-service IT and non-intrusive,
without the IT to be offline. However, the limitation of
electrical PD measurement is that it is highly susceptible to
electromagnetic interference and noise found in any substations
which may superposed with PD signals. Hence, this could also
be the reason for high PD activities detected during on-site
measurement conducted by TNBR before on eight units of the
instrument transformers. DGA test carried out on three of the
instrument transformers showed that the instrument
transformers were in good or acceptable condition.
[6]
[7]
[8]
[9]
[10]
As such in this research, a study has been carried out to
study the characteristics of PD to identify noise from on-site
electrical PD measurement data obtained from MPD 600 PD
measurement system. Initially, the electrical PD measurement
data which was in the form of PRPD pattern were visualized
and evaluated. Then, the types of noise that could interfere with
the measured PD signals were identified.
[11]
ACKNOWLEDGEMENT
This project is funded by TNB Research SDN. BHD. The
research work is carried out in collaboration with UNITEN
R&D SDN. BHD.
[14]
[12]
[13]
Guomin Luo, Daming Zhang, “Study on Performance of HFCT and
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A. Mehta, R. N. Sharma, S. Chauhan, “Partial discharge study by
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analysis of PD pulses and pulse-shaped disturbances,” Electrical
Insulation (ISEI), Conference Record of the 2010 IEEE International
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IEEE Standard C57.113, “IEEE Recommended Pratice for Partial
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Mohamad Ghaffarian Niasar, “Partial Discharge Signatures of Defects in
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REFERENCES
[1]
[2]
GE Digital Energy ITI, Instrument Transformer Basic Technical
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