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IEEE Transactions on Dielectrics and Electrical Insulation

Vol. 23, No. 3; June 2016

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Impact of Capacitive Coupling Circuit on Online Impulse Frequency Response of a Power Transformer Zhongyong Zhao, Chenguo Yao, Xiaozhen Zhao State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing 400030, China

Naser Hashemnia and Syed Islam Curtin University Perth, Western Australia

ABSTRACT Detecting the early signs of mechanical failures of power transformer winding is necessary and is possible with online monitoring techniques. Online impulse frequency response analysis (IFRA) is a promising diagnostic method when a transformer is in service. This paper examines the unrevealed problem existing in the method, namely, the impact of bushing capacitive coupling circuit on online impulse frequency response. An equivalent electrical model of capacitive coupling circuit and transformer winding is established. The frequency response of the capacitive coupling circuit is obtained to study its influence on online impulse frequency response. The parameter variations of capacitive coupling circuit caused by coupling capacitance variation and bushing dielectric breakdown are simulated to investigate their influence on online impulse frequency response signatures. A few experiments are eventually performed to verify the theoretical analysis and simulation results. This paper contributes to the application of online IFRA. Index Terms - Power transformer, winding deformation, online impulse frequency response analysis, capacitive coupling circuit, electrical model, dielectric breakdown.

1 INTRODUCTION A power transformer is considered as the most valuable property in a power substation. However, as the capacity and load of power networks increased over the past few years, the electromagnetic environment of substation have become more complex and transformer failure has frequently increased. Statistics show that winding deformation is one of the major reasons for power transformer failure. Unbalanced electromagnetic forces caused by external short circuit current more often have a function in generating and developing winding deformation; besides, careless transportation of power transformers, earthquakes, aging of insulation material and explosion of combustible gas in the transformer oil could also be reasons for giving rise to winding mechanical deformation [1–2]. The operation of a power transformer is insignificantly affected by mechanical faults at the incipient stage of winding deformation. Considering the ongoing operation of power transformers, winding deformation is scarcely explored at the initial stage. Winding deformation has a cumulative effect; the Manuscript received on 4 July 2015, in final form 29 September 2015, accepted 18 October 2015.

magnetic field changes dramatically after mechanical deformation; the electromagnetic force of a highly intensive field induced by external short circuit current could exceed the yield strength of winding material, which causes a further mechanical fault [3–4]. In addition, the electrical-thermal aging could be produced in the damaged insulation material, which results in a further short circuit failure. Thus, promptly detecting the winding deformation and preventing a sudden failure of a power transformer are important. Various methods have been proposed and developed by researchers globally [5–9] to detect winding mechanical deformation. Among all the methods, frequency response analysis (FRA) is known to be an accurate, economical, reliable, fast, and non-destructive method [10]. According to the nature of input signal [11], two methods exist: sweep FRA (SFRA) and impulse FRA (IFRA). The SFRA method has been developing for years, its industrial standards and criteria have been successively proposed, and these works are great contributions to the development of winding mechanical fault diagnosis. However, SFRA is currently adopted in offline application, usually after the failure of the transformer, which is hardly sufficient to prevent the sudden failure of a transformer in real

DOI: 10.1109/TDEI.2015.005518

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time. Studies on the online IFRA method have been conducted for more than 20 years and are continuing [12–15]. In [16] it was proposed an online monitoring system in which a high-frequency signal is injected to a 650 kV transformer winding through the bushing tap. Reference [17–18] studied the possibility of obtaining frequency response of a transformer from transient signals by applying continuous wavelet transform, in which theoretical analysis was derived and practical validation was performed. Reference [19–20] conducted an experimental study for online diagnosis of power transformer by utilizing power system transient overvoltage. Compared with SFRA, IFRA has reached the potential for online application. The pulse duration of IFRA is short and the pulse energy is small, which would have an insignificant effect on the normal operation of the transformer. The device, which is used to produce short pulses, is compact and inexpensive. Detection signals with high signal-to-noise ratio could be quickly obtained when short pulses with sufficiently high amplitude are used in the field. Furthermore, IFRA ensures that the device is detected when needed as well as avoids randomness of network events when the controlled signals are introduced [11]. A prototype system for online detection of power transformer winding deformation based on IFRA by using the method of capacitive coupling was previously proposed [21]. Although the IFRA signatures of a 110 kV healthy power transformer were obtained through a validation experiment, an important factor that may affect the online IFRA signature was ignored. A controllable pulse signal is injected to the inner transformer winding through bushing capacitive coupling. An online IFRA signature contains the features of winding and the influence of the capacitive coupling circuit. Moreover, any parameter variation of the capacitive coupling circuit might have an effect on the online IFRA signature, which may obstruct the online diagnosis of transformer winding mechanical failure. To examine these problems, electrical model simulation and verification experiments were carried out in the present study.

Figure 1. Simple diagram of the proposed online IFRA method.

a 2D cross-section drawing of the busing and CCS.

2 ELECTRICAL MODEL OF CAPACITIVE COUPLING CIRCUIT AND TRANSFORMER WINDING 2.1 CAPACITIVE COUPLING CIRCUIT A simple diagram of the proposed online IFRA method is depicted in Figure 1. The controllable nanosecond pulses with good repeatability and sufficiently high amplitude are injected to the terminal of transformer winding by using the method of capacitive coupling principle. In particular, a capacitive coupling sensor (CCS) is used, which is a metal strip that is wrapped around the bushing external insulation layer. Both the original excitation nanosecond pulse signals and the response pulse signals of winding are simultaneously recorded to construct the IFRA signature of a transformer to estimate the status of windings. However, the method of pulse signal injection is performed by skillfully using the configuration of transformer bushing [21–23]. The online IFRA signature of transformer winding

b Disturbed parameter electrical model of the capacitive coupling circuit. Figure 2. Electrical model of capacitive coupling circuit.

is actually not the signature of winding itself, and contains the effect of the capacitive coupling circuit, which may distort the winding signature. In addition, any parameter variation of the

IEEE Transactions on Dielectrics and Electrical Insulation

Vol. 23, No. 3; June 2016

capacitive coupling circuit might result in variation of the online IFRA signature, which could eventually affect the diagnosis of winding deformation. To investigate these problems, an equivalent electrical model of capacitive coupling circuit should be established. Given that the nanosecond high-frequency pulses are injected, the distributed parameter electrical model of capacitive coupling circuit should be built according to its structure and principle, as shown in Figure 2a. The distributed electrical model of the capacitive coupling circuit is shown in Figure 2b. 2.2 ELECTRICAL MODEL OF TRANSFORMER BUSHING In Figure 2b, the equivalent electrical model of bushing is divided into several sequential parts that are represented by bushing capacitance Cbn, volume resistance Rsn and surface resistance Rpn [24]. Stray inductance is ignored because of the thin bushing layers [25]. The capacitive bushing layers are designed as the configuration that each layer capacitance and voltage difference are identical. The calculation formula of bushing layer capacitance Cbn is described in equation (1), where r is the relative dielectric constant of dielectric material, ln is the length of nth bushing layer and rn is the radius of nth bushing layer. Volume resistance Rsn can be obtained through calculation formula for radial resistance of coaxial cylindrical conductor, as shown in equation (2), where  is the resistivity. Rpn represents surface resistance of bushing layers and bushing external insulation dielectric, which can usually reach the range 106–107 . A 110 kV bushing is composed of 33 capacitive layers. However, according to [25], the selection of the number of bushing layers for electrical simulation is a compromise between precision and complexity. Thus, the bushing equivalent electrical model of five layers is utilized as half measure in this study. In addition, the bushing tap of the capacitive coupling circuit model should be grounded because the busing tap is kept grounded when a power transformer is in service.

Cbn

2SH r H 0l1 r ln 1 r0 rn

Rsn

dr 2S rln rn1



2SH r H 0l2 r ln 2 r1



r U ln n 2S ln rn1

2SH r H 0ln r ln n rn 1

(1)

(2)

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potential distribution, and  is the solving domain. The coupling capacitance Cc is calculated to be approximately 30 pF in a 110 kV power transformer bushing.

C

We

2We V2

H

(3)

’I 2³

2

d:

Figure 3. FEM model of power transformer bushing.

An equivalent transformer lumped parameter electrical model for single-phase shell-type transformer winding is adopted in this study [26–27]. The HV and LV windings consist of 10 disks. In the model, each disk is represented by series resistance Rs and inductance Ls, shunted by capacitance Cs and conductance Gs. The capacitance CHL between HV winding and LV winding shunted by dielectric conductance G simulates the insulation condition between two windings, and mutual inductances Mij between two coils are included. The dielectric insulation (oil) between the LV winding and the core, and that between the HV winding and the tank, are simulated by capacitance Cg, shunted by dielectric conductance G. The specific lumped parameter values can be obtained by using the FEM analytical tool, as presented in Figure 4. The entire electrical model of transformer winding and capacitive coupling circuit is shown in Figure 5. The capacitive coupling circuit is connected to the terminal of HV winding because nanosecond pulses are invariably injected into HV winding when transformer is in service. Bus characteristic impedances of HV and LV sides are also introduced [16].

2.3 FINITE ELEMENT ANALYSIS FOR COUPLING CAPACITANCE AND TRANSFORMER WINDING The coupling capacitance Cc formed by CCS can be calculated by finite element method (FEM). A FEM model of power transformer bushing mounted with CCS is constructed based on its actual size and material, as shown in Figure 3. The bushing 3D model is analyzed using an electrostatic solver of ANSYS Maxwell to obtain the coupling capacitance. The basic for calculation of capacitance is described in equations (3) and (4), where V and We are voltage source and electric field energy storage, respectively.  is electric

(4)

:

Figure 4. 3D transformer FEM model

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G

Cg-L /2 Cg-L G s-L M ij-L

R s-L Cs-L Cbn

R pn

R sn

Ls-L G

CHL

M HL

Ls-H

R s-H C s-H

Cc

M ij-H

G s-H G

Cg-H /2 Cg-H

Figure 5. Electrical model of transformer winding and capacitive coupling circuit.

3 IMPACT OF CAPACITIVE COUPLING CIRCUIT ON ONLINE FREQUENCY RESPONSE OF TRANSFORMER WINDING

Vin f TFIFRA

f FFT I 0 t f FFT Vin t 20 log

I0 f

Vin f

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a Linear mode -20 -40 -60

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I0 f

online IFRA signature winding's IFRA signature

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Gain/dB

A square wave pulse [28] with pulse width of 300 ns, pulse rise and fall time of 30 ns, and pulse amplitude of 600 V functioning as the excitation signal Vin of transformer winding, is injected at the terminal of HV winding through capacitive coupling circuit, as shown in Figure 5. The response current Io is recorded by current transformer (CT) at the other terminal of HV winding. The excitation signal Vin and response signal Io are used to construct online IFRA signature (admittance transfer function of winding incorporated with capacitive coupling circuit) according to equation (5)–(7). In these equations, fFFT is Fast Fourier Transform, which is used to transform time domain pulse signal to frequency domain signal [29]. In addition, voltage signal Vc of inner conductor of bushing is also measured, and both Vc and Io are used to construct winding’s IFRA signature (admittance transfer function of winding only).

-20

-100 -120 -140

(7)

The simulation result is depicted in Figure 6. Apparently, online IFRA signature is not identical with winding’s IFRA signature. The capacitive coupling circuit has a significant influence on the online IFRA signature. In the frequency band of 0–0.1 MHz, the winding’s IFRA signature has a decreasing trend, whereas the online IFRA signature has an increasing trend. These two curves also have a significant difference in

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b Logarithmic mode Figure 6. Online IFRA signature and winding’s IFRA signature.

amplitude. The simulation result with this trend could be demonstrated in [30]. In the frequency band of 0.1–1 MHz, a

IEEE Transactions on Dielectrics and Electrical Insulation

Vol. 23, No. 3; June 2016

significant difference in the amplitude between the two signatures is still observed, which increases the difficulty in diagnosing the winding deformation based on signature graphical comparison. Fortunately, the amplitude difference remains unchanged in this frequency band, and the positions of each resonance and anti-resonance are identical. Frequency variation of resonance and anti-resonance could best reflect winding mechanical fault because resonance and antiresonance are determined by distributed inductance and capacitance [31], as shown in equation (8). The online IFRA signature of frequency band between 0.1–1 MHz could still be used for winding deformation diagnosis.

1

f

(8)

2S LC

The frequency response characteristic of the capacitive coupling circuit is described in Figure 7. This characteristic is equivalent to the capacitive reactance of the purely capacitive/resistive circuit, but is presented in the form of frequency response to better investigate and interpret the IFRA signatures. The frequency response signature shows a rising trend in the broadband frequency region. In low frequency band of 0–0.1 MHz, the frequency response shows a tremendously rising trend, whereas the frequency response appears to be more stable in the frequency band of 0.1–1 MHz. The tendency of frequency response of capacitive coupling circuit obviously has an effect on the winding’s IFRA signature, with a significant influence on the low frequency region of 0–0.1 MHz. -80 -90 -100 -110

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Figure 7. Frequency response characteristic of capacitive coupling circuit.

According to the simulation results, the following conclusions can be derived. (1) The capacitance characteristic formed by bushing and CCS results in the frequency response of the capacitive coupling circuit varies with frequency, which makes online IFRA signature different from winding’s IFRA signature. (2) In the low frequency region of 0–0.1 MHz, the frequency response of the capacitive coupling circuit shows a tremendously rising trend, which results in the increasing trend of the online IFRA signature, regardless of the

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decreasing trend of the winding’s signature in the corresponding frequency region. In the medium and high frequency region of 0.1–1 MHz, the frequency response of the capacitive coupling circuit shows a relatively stable trend. Thus, the tendencies of the online IFRA signature and winding’s signature are highly similar. (3) The reason for this phenomenon can be explained as follows. In the very low frequency region, the reactance of the capacitive coupling circuit is much larger than the inductive component of winding equivalent electrical model, and the online IFRA signature shows the capacitive characteristic of the coupling circuit. As the frequency increases, the reactance of the capacitive coupling circuit decreases, the reactance of the winding equivalent electrical model is much larger than that of the coupling circuit, and the online IFRA signature shows the inductive and capacitive characteristic of the winding. The constant difference on the amplitude of the two signatures is due to the capacitive reactance of capacitive coupling circuit. (4) The frequency response characteristic of the capacitive coupling circuit shows a tremendous change with a large gradient variation in the low frequency band. The capacitive coupling circuit dominates the online IFRA signature at this frequency band because of its larger reactance. In the medium and high frequency band, the frequency response characteristic of the capacitive coupling circuit shows a stable trend with a small gradient variation. The winding equivalent electrical model dominates the online IFRA signature at this frequency band because of its larger reactance, and the online IFRA signature could reflect the inductive and capacitive components of winding effectively. (5) Cross-connect point of two frequency bands, namely, a knee point of frequency response, in which the reactance of the capacitive coupling circuit is equal to that of the winding equivalent electrical model, is important in shaping the online IFRA signature. Therefore, this point should be selected as a critical point. The position of this frequency point varies according to different transformers, but more general conclusion could be derived as followed. Contrary to direct comparison of frequency response signatures in different frequency band for offline diagnosis, the low-frequency region of the online IFRA signature might be unsuitable for analysis because this frequency region is forcedly dominated by the characteristic of the capacitive coupling circuit.

4 IMPACT OF CAPACITIVE COUPLING CIRCUIT PARAMETER VARIATION ON ONLINE FREQUENCY RESPONSE OF A POWER TRANSFORMER 4.1 IMPACT OF COUPLING CAPACITANCE VARIATION ON ONLINE FREQUENCY RESPONSE SIGNATURE Coupling capacitance Cc is formed by CCS and is actually a stray capacitance; its value may be influenced by certain factors. To investigate the impact of coupling capacitance variation on the online IFRA signature, a parameter sweep

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simulation study with different coupling capacitance Cc values is conducted. The values of capacitance Cc are set to be 10–40 pF, with the step of 10 pF. The maximum rate of change reaches 67% with respect to the normal value 30 pF. Online IFRA signatures under different conditions are drawn in Figure 8. Frequency response characteristic of capacitive coupling circuit under different coupling capacitance values are described in Figure 9. According to the results in Figures 8 and 9, the coupling capacitance variation would not change the shape of the online IFRA signature. However, the amplitude of signature has changed because of the different frequency response characteristic (equivalent capacitive reactance) of the capacitive coupling circuit. The amplitude difference is identical in each frequency point, and the positions of resonance and antiresonance remain unchanged under different coupling capacitance values, which is significant for the online diagnosis of transformer winding deformation. The signature difference appears to be unremarkable in reality because the coupling capacitance variation is insignificant compared with the simulation. However, using the shift of resonance and antiresonance of the IFRA signature as the diagnostic indicators for online detection is better than using the amplitude variation of the IFRA signature.

The simulation result also provides guidance on optimal design of CCS. To obtain response signal with much larger signal-to-noise ratio, a CCS with larger coupling capacitance should be applied. Larger coupling capacitance means smaller equivalent reactance of the capacitive coupling circuit, which, in turn, results in larger response current signal and larger gain of the IFRA signature. 4.2 IMPACT OF BUS CHARACTERISTIC IMPEDANCE ON ONLINE FREQUENCY RESPONSE SIGNATURE Nanosecond pulses transmitted through the capacitive coupling circuit also enter the bus; the length of the bus appears to be infinite considering short duration pulses. According to Peterson’s principle [32], the wave propagation process of the bus can be replaced by a lumped parameter equivalent circuit, represented by its characteristic impedance.

P 0 P r 2 hc ln 2S r

L0

(9)

2SH 0H r 2h ln c r

C0

(10)

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L0 C0

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Z

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60 ln

2hc r

(11)

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10pF 20pF 30pF 40pF

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Figure 8. Impact of coupling capacitance variation on online IFRA signature.

Characteristic impedance of overhead bus line is determined by its inductance L0 per unit length and capacitance C0 per unit length, as shown in equation (9)-(11). r and r are relative magnetic permeability and relative dielectric constant of air, respectively. Their values remain unchanged regardless of external condition. hc and r are height and radius of the bus, respectively. Generally, the bus characteristic impedance is 300 ohm, and this impedance is fixed according to the bus dimension. Consequently, misjudgments of transformer winding deformation could not be induced by bus characteristic impedance. -90

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normal fault degree 1 fault degree 2

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Figure 9. Frequency response characteristic of capacitive coupling circuit under different coupling capacitance values.

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Figure 10. Impact of bushing dielectric breakdown on online IFRA signature (0–1 MHz).

IEEE Transactions on Dielectrics and Electrical Insulation

Vol. 23, No. 3; June 2016

4.3 IMPACT OF BUSHING FAILURE ON ONLINE FREQUENCY RESPONSE SIGNATURE Dielectric breakdown between bushing layers is considered as the most common failure of transformer bushing [33]. If bushing dielectric breakdown occurs and develops, then the equivalent electrical model of transformer bushing changes and the online IFRA signature may be distorted. To study the impact of bushing dielectric breakdown failure on the online IFRA signature, bushing layers are artificially shorted in the electrical model shown in Figure 5. In the capacitive coupling circuit shown in Figure 5, the bushing layer closest to the inner conductor of the bushing is labeled as number 1, the following bushing layer is labeled as number 2, and so on. Two different conditions are set up by shorting number 1 and number 2 layers, and number 1 and number 3 layer, to simulate the dielectric breakdown under different fault degrees. Given that the bushing equivalent electrical model is composed of five layers, a short circuit of number 1 and number 2 layers appears to be a catastrophic failure, which rarely occurs in reality. However, conducting the simulation to explore the effect of bushing dielectric breakdown on the online IFRA signature is still necessary. The simulated online IFRA signatures under normal and faulty conditions are depicted in Figure 10 and 11. The simulation result of Figure 10 and 11 shows the same trend as that of Figure 8. Bushing equivalent capacitance Cb can be obtained through equation (12).

Cbn m

Cb

(12)

Where Cbn is the bushing layer capacitance and m is the number of bushing layers. -90 -100 -110

Gain/dB

-120 -130 -140 -150 -160 normal fault degree 1 fault degree 2

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0.2 0.25 0.3 Frequency/MHz

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capacitance variation on online IFRA signature, the bushing dielectric breakdown does not change the shape and trend of the signature. The positions of resonance and anti-resonance remain unchanged. Given that the bushing dielectric breakdown will not occur remarkably in reality as the simulation does, the amplitude difference between signatures shows a smaller tendency. The feature of online IFRA signatures under different conditions of simulated bushing dielectric breakdown is also important for the online diagnosis of transformer winding deformation. The upper shift of signature in the broadband frequency region might be used to distinguish the bushing failure and winding deformation, because the signature of winding deformation generally shows a shift of resonance and anti-resonance at a particular frequency band compared with the reference signature.

5 EXPERIMENT VERIFICATION Verification experiments were conducted on a 50 Hz, 10/0.4 kV, three-phase distribution transformer. The winding vector group was YYN connection, and the test was performed on one-phase of the YN side. The diagram of experimental connection is shown in Figure 12. This manuscript focused on studying the effect of the capacitive coupling circuit, hence the tested transformer was not connected to Grid and energized, and instead a resistor was connected with bushing to emulate the characteristic impedance of the bus. Several experiments were conducted under the same condition. The measured voltage and current were averaged to reduce the external interference and disturbance. The excitation pulses of 300 ns pulse width, 600 V pulse amplitude were injected to the transformer winding through CCS. The excitation voltage Vin and the response current of the grounded neutral terminal Io were used to construct the online IFRA signature. The coupled voltage of bushing conductor Vc and the neutral current Io were used to construct winding’s IFRA signature. The configuration of CCS metal strip, which was used to form the bushing coupling capacitance, was alternated to emulate the coupling capacitance variation. First, an intact metal strip was mounted on the bottom of a 0.4 kV bushing external insulation layer to form a large coupling capacitance. The intact metal strip was then replaced by three quarters and half of metal strip to emulate the different coupling capacitors with middle and small capacitance, respectively. The experiment was performed following the same procedure.

0.5

Figure 11. Impact of bushing dielectric breakdown on online IFRA signature (0–0.5 MHz).

Dielectric breakdown between bushing layers results in a decrease of bushing layers and an increase of bushing capacitance. As the capacitive reactance of bushing decreases, a larger response current is obtained, and the amplitude of the online IFRA signature increases according to equation (7), as shown in Figures 10 and 11. The increase of bushing capacitance has a similar effect with increasing coupling capacitance Cc. In addition, similar to the impact of coupling

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Figure 12. Simple diagram of experimental connection.

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The experiment result is shown in Figure 13. Notably, the tested transformer shown in Figure 12 is relatively different from that shown in Figure 5. As a result, different signatures are obtained. The test is performed only for fundamental verification and it makes sense. Similar to the features of the online IFRA signatures shown in Figure 8, larger coupling capacitance Cc results in larger amplitude of online signature. The trends of three online signatures are identical and the difference between any two signatures remains unchanged as the frequency changes. The coupling capacitance formed by 0.4 kV bushing is small, hence the difference between online signatures are small. In addition, IFRA signature of winding is incorporated, the difference between winding’s signature and online signature is constant and resonance and anti-resonance of two signatures are identical in medium and high frequency range. The trends of two signatures are similar to those shown in Figure 6, which validates the theoretical analysis and simulation results.

The impact of capacitive coupling circuit parameter variation on the online IFRA signature was also investigated. The variations of coupling capacitance and bus characteristic impedance were considered. The dielectric breakdown failure of bushing layers was emulated to explore its influence on the online IFRA signature. Finally, verification experiments were performed to further validate the theoretical analysis and simulation studies. This paper provides guidance on the actual online application of IFRA. More experiments, including those on bushing fault and winding fault, have to be carried out in the future.

ACKNOWLEDGMENT This work was supported by the National Natural Science Foundation of China (No. 51377175, 51321063) and China Scholarship Council.

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Figure 13. Impact of coupling capacitance variation on online IFRA signatures (IFRA signature of winding is also incorporated).

6 CONCLUSION AND FUTURE WORK The impact of capacitive coupling circuit on the online IFRA signature was studied in this paper. An equivalent electrical model of the coupling circuit and the winding was initially established, and then the online IFRA signature and winding’s IFRA signature were compared to explore the effect of the capacitive coupling circuit. The frequency response characteristic of the coupling circuit was obtained to explain the difference between the two curves. The trend of the online IFRA signature was contrary to that of the winding’s signature in the low frequency band of 0–0.1 MHz, however, a constant difference in the signature amplitude was observed in medium and high frequency range because of the reactance of the capacitive coupling circuit. The positions of resonance and anti-resonance of the two signatures were identical. This finding was significant for online diagnosis of transformer winding mechanical deformation. A key frequency point, in which the reactance of capacitive coupling circuit is equal to that of the winding equivalent electrical model, has to be located to distinguish the major effect of the capacitive coupling circuit and winding.

[5]

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[8]

[9]

[10]

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[12]

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IEEE Transactions on Dielectrics and Electrical Insulation

Vol. 23, No. 3; June 2016

[14] E. Rahimpour, M. Jabbari, and S. Tenbohlen, “Mathematical Comparison Methods to Assess Transfer Functions of Transformers to Detect Different Types of Mechanical Faults”, IEEE Trans. Power Del., Vol. 25, No. 4, pp. 2544-2555, 2010. [15] E. Rahimpour, J. Christian ˈ K. Feser, and H. Mohseni, “Transfer Function Method to Diagnose Axial Displacement and Radial Deformation of Transformer Windings”, IEEE Trans. Power Del., Vol. 18, No. 2, pp. 493-505, 2003. [16] T. De Rybel, A. Singh, A. J. Vandermaar, M. Wang, J. R. Marti, and K. D. Srivastava, “Apparatus for Online Power Transformer Winding Monitoring Using Bushing Tap Injection”, IEEE Trans. Power Del., Vol. 24, No. 3, pp. 996-1003, 2009. [17] E. G. Luna, G. A. Mayor, J. P. Guerra, D. F. S. Salcedo, and H. Gutiérrez, “Application of Wavelet Transform to Obtain the Frequency Response of a Transformer From Transient Signals—Part 1: Theoretical Analysis”, IEEE Trans. Power Del., Vol. 28, No. 3, pp. 1709-1714, 2013. [18] E. G. Luna, G. A. Mayor, and J. P. Guerra, “Application of Wavelet Transform to Obtain the Frequency Response of a Transformer From Transient Signals—Part II: Practical Assessment and Validation”, IEEE Trans. Power Del., Vol. 29, No. 5, pp. 2231-2238, 2014. [19] M. Wang, “Winding Movement and Condition Monitoring of Power Transformers in Service,” Ph.D. dissertation, Dept. Elect. Comput. Eng., Univ. British Columbia, Vancouver, BC, Canada, 2003. [20] M. Wang, A. J. Vandermaar, and K. D. Srivastava, “Condition Monitoring of Transformers in Service by the Low Voltage Impulse Test Method”, Int’l. Sympos. High Voltage Eng. (ISH), London, UK, pp. 4548, 1999. [21] C. G. Yao, Z. Y. Zhao, Y. Chen, X. Z. Zhao, Z. J. Li, Y. Wang, Z. H. Zhou, and G. Wei, “Transformer Winding Deformation Diagnostic System Using Online High Frequency Signal Injection by Capacitive Coupling”, IEEE Trans. Dielectr. Electr. Insul., Vol. 21, No. 4, pp. 14861492, 2014. [22] V. Behjat, A. Vahedi, A. Setayeshmehr, H. Borsi, and E. Gockenbach, “Diagnosing Shorted Turns on the Windings of Power Transformers Based Upon Online FRA Using Capacitive and Inductive Couplings”, IEEE Trans. Power Del., Vol. 26, No. 4, pp. 2123-2133, 2011. [23] A. Setayeshmehr, A. Akbari, H. Borsi, and E. Gockenbach, “On-line Monitoring and Diagnoses of Power Transformer Bushings”, IEEE Trans. Dielectr. Electr. Insul., Vol. 13, No. 3, pp. 608-615, 2006. [24] M. H. Zink, V. Klipfel, F. Berger, and A. Kuchler, “Ageing-Condition Assessment of Generator Transformer Bushings by Means of Dielectric Simulation Models”, IEEE Int’l. Conf. Condition Monitoring and Diagnosis (CMD), Bali, Indonesia, pp. 137-140, 2012. [25] H. Y. Mai, D. X. Lie, C. Y. Zang, G. Chen, Z. Y. Du, and Y. Q. Chen, “Simulation Analysis of High Voltage Bushing Insulation Status Detection Using Frequency Response Analysis Method”, High Voltage Eng., Vol. 37, No. 12, pp. 3045-3052, 2011 (in Chinese). [26] N. Hashemnia, A. Abu-Siada, and S. Islam, “Improved Power Transformer Winding Fault Detection using FRA Diagnostics – Part 1: Axial Displacement Simulation”, IEEE Trans. Dielectr. Electr. Insul., Vol. 22, No. 1, pp. 556-563, 2015. [27] N. Hashemnia, A. Abu-Siada, and S. Islam, “Improved Power Transformer Winding Fault Detection using FRA Diagnostics – Part 2: Radial Deformation Simulation”, IEEE Trans. Dielectr. Electr. Insul., Vol. 22, No. 1, pp. 564-570, 2015. [28] C. G. Yao, X. M. Zhang, F. Guo, S. L. Dong, Y. Mi, and C. X. Sun, “FPGA-Controlled All-Solid-State Nanosecond Pulse Generator for Biological Applications”, IEEE Trans. Plasma Sci., Vol. 40, No. 10, pp. 2366-2372, 2012. [29] K. Ludwikowski, K. Siodla, and W. Ziomek, “Investigation of Transformer Model Winding Deformation Using Sweep Frequency Response Analysis”, IEEE Trans. Dielectr. Electr. Insul., Vol. 19, No. 6, pp. 1957-1961, 2012. [30] M. Bagheri, M. S. Naderi, T. Blackburn, and B. T. Phung, “Bushing Characteristic Impacts on On-line Frequency Response Analysis of Transformer Winding”, IEEE Int’l. Conf. Power and Energy (PECon), Kota Kinabalu Sabah, Malaysia, pp. 956-961, 2012. [31] M. Wang, A. J. Vandermaar, and K. D. Srivastava, “Improved Detection of Power Transformer Winding Movement by Extending the FRA High Frequency Range”, IEEE Trans. Power Del., Vol. 20, No. 3, pp. 19301938, 2005.

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[32] J. G. Huang, X. Y. Hu, X. S. Li, and H. M. Hu, “A Novel Single-Phase Earth Fault Feeder Detection by Traveling Wave and Wavelets”, Int’l. Conf. Power System Technology, PowerCon, Chongqing, China, pp. 14, 2006. [33] A. J. Vandermaar, M. Wang, J. B. Neilson, and K. D. Srivastava, “The Electrical Breakdown Characteristics of Oil-paper Insulation Under Steep Front Impulse Voltages”, IEEE Trans. Power Del., Vol. 9, No. 4, pp. 1926-1935, 1994. Zhongyong Zhao was born in Guangyuan, Sichuan, China, on 1 October 1988. He received the B.S. degree in electrical engineering from Chongqing University, Chongqing, China, in 2011, where he is currently working toward the Ph.D. degree with the combined Master–Ph.D. Program in electrical engineering. His areas of research include online monitoring of insulation condition and insulation fault diagnosis for HV apparatus, pulsed power technology.

Chenguo Yao (M’08) was born in Nanchong, Sichuan, China, on 1 February 1975. He received the B.S., M.S., and Ph.D. degrees in electrical engineering from Chongqing University, Chongqing, China, in 1997, 2000, and 2003, respectively. He became a Professor with the School of Electrical Engineering, Chongqing University, in 2007. His current works include pulsed power technology and its application in biomedical engineering, online monitoring of insulation condition and insulation fault diagnosis for HV apparatus. Xiaozhen Zhao was born in Taian, Shandong, China, on 20 April 1989. He received the B.S. degree in electrical engineering and automation from China University of Mining and Technology, Xuzhou, China, in 2012. He is currently working toward the Ph.D. degree with the combined Master–Ph.D. Program in electrical engineering of Chongqing University from September 2012. His current works include the fault diagnosis of transformer and its state evaluation.

N. Hashemnia received the B.Sc. degree in electrical power engineering from Yazd University, Iran, in 2006 and the Master of Electrical Utility Engineering d e g r e e from Curtin University in 2010. He received a scholarship from the Cooperative Research Centre for Infra- structure and Asset Management in 2011 to enable him to pursue his PhD study at Curtin University. His research interests include power transformer condition monitoring and application of artificial intelligence to power systems. S. Islam (M’83-SM’93) received the BSc from Bangladesh University of Engineering and Technology, Bangladesh, and the M.Sc. and Ph.D. degrees from King Fahd University of Petroleum and Minerals, Saudi Arabia, all in electrical power engineering in 1979, 1983, and 1988, respectively. He is currently the John Curtin distinguished professor in electrical power engineering at Curtin University, Australia. He received the IEEE T Burke Haye Faculty Recognition award in 2000. His research interests are in condition monitoring of transformers, wind energy conversion, and power systems. He is a regular reviewer for IEEE Transactions on Energy Conversion, IEEE Transactions on Power Systems, and IEEE Transactions on Power Delivery. Prof. Islam is an editor of IEEE Transactions on Sustainable Energy and IET Renewable Power Generation.