978-1-4799-5141-3/14/$31.00 ©2016 IEEE

Effect of Temperature on Condition Assessment of Oil-Paper Insulation using Polarization-

Depolarization Current

Saurabh Department of

Electrical Engineering Indian Institute of

Technology (Indian School of Mines) Dhanbad, India

M. Mukherjee Department of

Electrical Engineering Jadavpur University

Kolkata, India

A. K. Pradhan Department of

Electrical Engineering Jalpaiguri Govt. Engg.

College Jalpaiguri, India

A. Baral Department of

Electrical Engineering Indian Institute of

Technology (Indian School of Mines) Dhanbad, India

S. Chakravorti Department of

Electrical Engineering

Jadavpur University Kolkata, India

Abstract—Polarization Depolarization Current method of dielectric testing is popularly used by the utilities for condition assessment of the insulation of power transformers. Test temperature is an important factor that affects the polarization depolarization current data measured. In this work the effect of test temperature in condition assessment of cellulosic part of oil-paper insulation using polarization depolarization current method has been investigated. Polarization and depolarization current of experimental samples, emulating oil-paper insulation of power transformers, at different test temperatures were measured. The cellulosic moisture content was estimated for the samples at different temperatures using the farthest zero of the transfer function of the Maxwell’s model derived from the polarization depolarization current data. The error in the calculated paper moisture content is determined from comparison with the moisture content calculated from the minimum tan delta of the frequency domain spectroscopy data of the test samples maintained at different test temperature. Results obtained clearly show that the error in the moisture content calculated from the polarization depolarization current data increases with the increase in temperature.

Keywords—Polarization depolarization current; oil-paper insulation system; cellulosic moisture content; frequency domain spectroscopy; minimum tanδ.

I. INTRODUCTION

Condition assessment and monitoring of transformer insulation has been an area of growing interest in recent years. The main reason for this is that the transformers are one of the most costliest and critical equipments of the power system responsible for maintaining reliable and quality power supply.

Faults in transformers are caused mainly due to the failure of its insulation. The insulation system of power transformers mainly comprises of processed transformer oil and cellulose in the form of kraft paper and pressboard. During the lifetime of operation of a transformer its insulation degrades under the influence of electrical, chemical, mechanical and thermal stresses [1-3]. The degradation of the insulation results in aging along with the increase in the overall moisture content. The

moisture content of cellulosic insulation increases continuously throughout the lifetime of a transformer. Such increase in moisture content is mainly due to diffusive ingress of moisture from the environment and due to gradual degradation of cellulosic materials. The increase in the overall cellulosic moisture content over 4% may decreases the breakdown strength of the insulation sufficiently to cause catastrophic failures.

The main focus of modern day researchers is on the development of non-invasive method for condition assessment of power transformers. Dielectric spectroscopy is one of such non invasive method which is widely used [4-5]. Dielectric Spectroscopy includes return voltage measurement (RVM) [6], polarization and depolarization current (PDC) [7-8] and frequency domain spectroscopy (FDS) [9]. RVM is not used for practical applications as it cannot differentiate the effect of the oil and cellulose from the spectroscopy of the characteristic composite insulation [10]. FDS is one the most popularly used methods for condition monitoring of transformer insulation and is more suitable than PDC because it is independent of insulation geometry, more accurate and low noise sensitivity. The only problem of the conventional frequency domain spectroscopy for field testing is that the time of completion of a complete measurement is too long [10]. Polarization and depolarization current measurement on the other hand has a relatively shorter duration of measurement and more age sensitive information can be extracted from the PDC data.

PDC method is popularly used for condition assessment of oil-paper insulation for its non-invasiveness, short duration of measurement and for ability to extract more age sensitive information of the oil-paper insulation. The temperature of the measurement is one of the most important factors that affect the dielectric response [11-12]. Hence different PDC measurements will be the obtained for the same transformer unit at different temperatures which may result in inaccurate estimation of the condition of the cellulosic part of transformer insulation. It is reported in [13] that the polarization-depolarization current and dc conductivity increases with the increase in temperature. The study has not reported the direct

effect of temperature in the condition assessment of cellulosic part of oil-paper insulation using PDC method.

This work mainly focuses on the determining the direct effect on temperature in estimating the moisture content of cellulosic insulation using PDC method. The PDC data are recorded for laboratory samples at different test temperatures and moisture content of cellulosic insulation is estimated from suitable curve fitting technique and zero method reported in [14]. The moisture content estimated from PDC data is then compared with the moisture content determined from the FDS data and the corresponding error obtained is calculated.

II. ESTIMATION OF MOISTURE CONTENT OF CELLULOSIC

INSULATION USING DIELECTRIC SPECTROSCOPY

A. Estimation of moisture content of cellulosic insulation from Polarization - Depolarization Current

The branch parameters of the Maxwell’s model obtained from suitable curve fitting of the PDC data contains age sensitive information that can be used for condition assessment of cellulosic insulation. Each branch represents a particular group of dipoles having a particular relaxation time [15]. Hence the branch parameters i.e. the resistance (Ri) and the capacitance (Ci) of each branch represent the condition of a particular group of dipoles of the composite oil-paper insulation system of a transformer. However the PDC data is sensitive to the insulation geometry. Hence research has been conducted to determine age sensitive parameter which is less dependent on the insulation geometry. It is reported in [14] that such an age-sensitive parameter can be determined from the transfer function of the Maxwell’s Model. The parameter is the farthest zero of the transfer function located in the left half of the s-plane (z1). It is shown mathematically and experimentally that the parameter z1 can be used to estimate the cellulosic moisture content with satisfactory accuracy. The empirical relationship between the paper moisture content (% pm) and z1 is given in equation (1) [14].

( )1ln*418.0718.1% Zpm += (1)

The moisture content of cellulosic insulation of the experimental samples at different test temperatures are determined from the PDC data using equation (1). The results obtained are compared with the moisture content obtained from the FDS data in order to determine the direct effect of test temperature in the condition assessment of transformer insulation using PDC data.

B. Estimation of moisture content of cellulosic insulation from Frequency Domain Spectroscopy

The Frequency domain spectroscopy (FDS) is the most widely used non invasive techniques for condition assessment of oil-paper insulation. The moisture present in the cellulosic insulation significantly affects tanδ value because of its awkwardly shaped molecules [1]. The minimum tanδ in FDS represents the minimum frictional loss due to rotating dipoles. Hence the minimum tanδ is used for more accurate estimation of moisture content of cellulosic insulation as it represent the intrinsic condition of the insulation. The relationship widely

used to determine the paper moisture content (% pm) from minimum tanδ (tanδmin) established by W. S. Zaengl is represented by equation (2) [15].

)ln(tan*53267.2297.15% minδ+=pm (2)

Paper moisture content of the test samples at different temperatures are also determined from the minimum tanδ obtained from the FDS data. This paper moisture content is used to determine the error in the paper moisture content calculated from the PDC data.

III. PREPARATION OF TEST SAMPLES AND EXPERIMENTAL

PROCEDURE

Laboratory samples are constructed for experimental purpose that emulates the composite oil-paper insulation of power transformer as reported in [1, 17]. The procedures used in preparing the test samples are similar to the steps those were reported in [17]. The cross sectional views of the test samples along with the dimensions have been shown in Figure 1(a). The preparation of test samples begin with the construction of core, A. Over A, a pressboard cylinder, B is placed and a blanket of un-impregnated kraft paper, C, is wrapped over B. The insulation between LV (D) and HV (H) winding is modeled by arranging the layers of copper strips (D)- un-impregnated kraft paper (E) - pressboard strips (F) – un-impregnated kraft paper (G) - copper foil (H) in parallel. The photograph of the test samples have been shown in Figure 1(b).

(a)

(b)

Fig. 1. Test sample fabricated in the laboratory. (a) Sectional drawing and (b) actual photograph [1, 17].

The test samples are heated continuously at 90°C inside a sealed chamber maintained at low pressure for sufficient time to remove residual moisture that might have been absorbed by the test sample from the atmosphere during preparation. The moisture content of the test samples are set using the dry weight test method using the procedure described in [1, 17]. In this technique, the weights of the cellulosic part of the insulation (Wb) of the test samples are determined using a balance after heating the sample in a sealed chamber for a sufficient amount of time. The specimen are then kept in open air and kept some times for moisture to ingress. After achieving sufficient moisture, the cellulosic part of the test samples are weighed (Wa). From Wb and Wa, the moisture content of each sample is calculated using equation (3).

Moisture content of the samples at a definite temperature

= %100×−

b

ba

W

WW (3)

In the present work, specific samples re developed for experimental purpose. Value of paper moistures present in each of the test samples at 30°C is given in 3.2%.

After absorbing requisite amount of moisture, the test samples are placed inside a specially designed oil-filled glass chamber (as shown in Figure 2) and kept for some days for oil-impregnation. It is worthwhile to mention that the volume of oil within the glass chamber is kept equal for each test sample. The temperature within the glass chamber is kept fixed using the heating bath (marked 2 in Figure 2). Besides temperature, the pressure within the chamber is kept fixed with a vacuum pump (marked as 3 in Figure 2). The arrangement makes sure that the oil used here for impregnation purpose does not moisture from atmosphere and remains fresh.

Fig. 2. Setup for oil impregnation. (1) Glass chamber, (2) Heating bath, (3) Vacuum pump, (4) Pressure gauge

Now the test samples are heated for several days continuously at different temperatures namely; 30°C to 80°C in steps of 10°C using the environmental chamber as shown in Figure 3. After heating each sample at the predefined temperature the dielectric response (frequency domain) is measured from 1 mHz to 1 kHz. Also the polarization depolarization currents are measured for the test samples at different temperatures using an instrument designed and fabricated at Jadavpur University as shown in figure 4. An in built real-time non linear de-noising routine ensures noise free measurement of polarization depolarization current of the test sample [18].

Fig. 3. Environmental chamber for heating the test samples.

Fig. 4. Equipment used to measure the polarization current

IV. EXPERIMENTAL RESULTS

Polarization depolarization current and tanδ data are measured for the test samples at different temperatures (30°C – 80°C). Figure 5 and Figure 6 show depolarization current data and the measured tanδ data of the test samples at different temperatures respectively. It is worth mentioning here that the relaxation (polarization and depolarization) current from the laboratory sample are recorded until it settles down to a constant value. For the laboratory sample constructed it is observed that this time is in the range of 1000s.

Time (s)

0.1 1 10 100 1000 10000

Pol

ariza

tion

Curr

ent (

A)

1e-9

1e-8

1e-7

1e-6

1e-5

1e-4

30 deg C40 deg C50 deg C60 deg C70 deg C80 deg C

Fig. 5. Measured polarization currents of the test samples at different temperatures

Frequency (Hz)

0.0001 0.001 0.01 0.1 1 10 100 1000 10000

tan-d

elta

(%

)

0.001

0.01

0.1

1

10

100

1000

30 deg C40 deg C50 deg C60 deg C70 deg C80 deg C

Fig. 6. Measured tanδ data of the test samples at different temperatures

It is clear from the figure 5 that the depolarization current increases with the increase in temperature.

The branch parameters of the Modified Maxwell model are determined using suitable curve fitting technique. The transfer function is then formed using the branch parameters equation (4).

−

= +

×++=

brno

i

ii

i

CRs

Rs

R

CsRTF

100

00

1

1

)1( (4)

Where Ri and Ci are the respective branch resistance and capacitances, R0 and C0 are the insulation resistance and capacitance respectively and no-br represents the number of branches (group of dipoles).

The transfer function can also be written as equation (5) in order to express its dependency on z1 [14].

)(

)()( 1

sD

sNzsTF

×+= (5)

Where, N(s) and D(s) are the modified numerator and modified denominator polynomial of the transfer function of the Maxwell’s model respectively.

The paper moisture content of the test samples heated at different temperatures are determine from z1 using equation (1) and are shown in Table I.

TABLE I. PAPER MOISTURE CONTENT AT DIFFERENT TEMPERATURES CALCULATED FROM Z1

Temperature of the Test Sample

Paper Moisture calculated from z1 (%)

30°C 3.1838 40°C 3.4815 50°C 3.7702 60°C 4.1456 70°C 4.8152 80°C 5.1053

It is clear from Table I that with the increase in temperature the paper moisture content increases which is in good correlation with the results reported in [19].

The cellulosic moisture content of the test samples at different temperature are calculated from the minimum tanδ obtained from the FDS data as shown in equation (2) in order to determine the accuracy of the cellulosic moisture content determined from the PDC data,. Table II shows a comparison of the moisture content estimated from PDC and FDS method and the error obtained by using PDC data at different temperature.

It is clear from Table II that with the increase in temperature the error in the moisture content determined from the PDC data corresponding to the moisture content determined from the FDS data increases with the increase in the temperature.

TABLE II. COMPARISON OF THE PAPER MOISTURE CONTENT AT DIFFERENT TEMPERATURES CALCULATED FROM PDC AND TAN-DELTA

Temperature of the Test

Sample

Paper Moisture calculated

from z1 (%)

Paper Moisture from

measured tanδmin (%)

Deviation of the calculated

Paper Moisture

30°C 3.1838 3.212 0.8832 40°C 3.4815 3.675 5.2656 50°C 3.7702 4.2089 10.4242 60°C 4.1456 4.6435 10.7242 70°C 4.8152 5.8018 17.0059 80°C 5.1053 6.8064 24.9933

The main reason for this is that the parameter z1, from

which moisture content is estimated, changes with the change in R0, Ri and Ci. It is reported that with the change in temperature the branch resistances changes according to the activation energy of the test samples. The branch resistances (Ri) of insulation at two definite temperatures T1 and T2 should follow the activation energy relationship as given by equation (6) [20].

−

×= 12

11

12TTk

W

eRR (6)

Where, W is the activation energy, k is the ideal gas constant (8.3145 J/mol·K), R2 and R1 are the resistances at temperatures T2 and T1 respectively.

The branch parameters obtained from the PDC data at different temperatures using curve fitting technique does not follow the relationship given by equation (6). Hence it cannot be ensured that the moisture content obtained from z1, which in turn is dependent on the branch parameters, is accurate at every temperature. With the increase in temperature the error will not remain constant. The error will rather increase with the increase in temperature as shown in Table II as the difference

1 2

1 1

T T

−

increases. At present, the authors of the paper are

engaged in studying the influence of important factors (like variation in aging time and initial paper moisture content of sample ) on paper moisture (column 2 of Table II) evaluated at different temperatures.

V. CONCLUSIONS

In this work PDC data of transformer samples were measured at different temperatures and the paper moisture content was determined using the farthest zero method. The cellulosic moisture content determined from the PDC data is validated using the cellulosic moisture content determined from the minimum tanδ of the FDS data of the same transformer samples. Experimental results clearly show that the test temperature greatly affects the PDC data. The error in the moisture content determined from z1 of the PDC data increases with the increase in temperature. Hence the deviation in the paper moisture content determined using PDC and FDS is fixed at a particular temperature and increases with the increase in temperature.

REFERENCES [1] A. K. Pradhan, B. Chatterjee and S. Chakravorti, “Estimation of Paper

Moisture Content based on Dielectric Dissipation Factor of Oil-paper Insulation under Non-sinusoidal Excitations”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 2, pp. 822-830, 2015.

[2] S. Q. Wang, G. J. Zhang, J. L. Wei, “Experimental Study of the Aged States Effects on Pressboard PDC Characteristics”, Proceedings of the CSEE, Vol. 31, No. 34, pp. 177-183, 2011.

[3] R. J. Liao, L. J. Yang, H. B. Zheng, “Reviews on Oil-paper Insulation Thermal Aging in Power Transformers”, Transactions of China Electrotechnical Society, Vol. 27, No. 5, pp. 1-12, 2012.

[4] T. K. Saha, "Review of Modern Diagnostic Techniques for Assessing Insulation Condition in Aged Transformers", IEEE Transactions on Dielectric and Electrical Insulation, Vol. 10, No. 5, pp. 903-917, 2003.

[5] M. C. Lessard, L. Van Nifterik, M. Masse, J.F.Penneau and R. Grob, “Thermal Aging Study of Insulating Paper used in Power Transformer”, IEEE Conference on Electrical Insulation and Dielectric Phenomena, San Francisco, USA, Vol. 2, pp. 854–859, 1996.

[6] Y. C. Kuang, G. Chen, P. Jarmm, “Recovery Voltage Measurement on Oil-paper Insulation with Simple Geometry and Controlled Environment”, IEEE International Conference on Solid Dielectrics, Toulouse, France, pp. 739-742, 2004.

[7] T. K. Saha, P. Purkait, “Investigation of Polarization and Depolarization Current Measurements for the Assessment of Oil-paper Insulation of Aged Transformers”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 11, No. 1, pp. 144-154, 2004.

[8] T. K. Saha, P. Purkait, “Effects of Temperature on Time-domain Dielectric Diagnostics of Transformers”, Australian Journal of Electrical and Electronics Engineering, Vol. 1, No. 3, pp. 157-162, 2004.

[9] S. M. Gubanski, P. Boss, G. Csepes, “Dielectric Response Methods for Diagnostics of Power Transformers”, IEEE Electrical Insulation Magazine, Vol. 19, No. 3, pp. 12-18, 2003.

[10] X. Liu, R. Liao, Y. Lv, J. Liu, J. Gao and J. Hao, "Study on Influences and Elimination of Test Temperature on PDC Characteristic Spectroscopy of Oil-Paper Insulation System", Journal of Electrical Technology, 10(1), pp. 30-40, 2015.

[11] V. D. Houhanessian, W. S. Zaengl, “Application of Relaxation Current Measurements to On-site Diagnosis of Power Transformers”, IEEE Conference on Electrical Insulation and Dielectric Phenomena, Minneapolis, America, pp. 45-51, 1997.

[12] A. Setayeshmehr, I. Fofana, A. Akbari, “Effect of Temperature, Water Content and Aging on the Dielectric Response of Oil-impregnated Paper”, IEEE International Conference on Dielectric Liquids, Futuroscope-Chasseneuil, France, pp. 1-4, 2008.

[13] T. K. Saha, P. Purkait, “Investigations of Temperature Effects on the Dielectric Response Measurements of Transformer Oil-paper Insulation System”, IEEE Transactions on Power Delivery, Vol. 23, No. 1, pp. 252-260, 2008.

[14] A. Baral and S. Chakravorti, “Condition Assessment of Cellulosic Part in Power Transformer Insulation using Transfer Function Zero of Modified Debye Model”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 21, No. 5, pp. 2028-2036, 2014.

[15] A. Baral and S. Chakravorti, “A Modified Maxwell Model for Characterization of Relaxation Processes within Insulation System having Non-uniform Aging due to Temperature Gradient”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 20, No. 2, pp. 524 to 534, 2013.

[16] W. S. Zaengl, “Applications of dielectric spectroscopy in time and frequency domain for HV power equipment”, IEEE Electrical Insulation Magazine, Vol. 19, No. 6, pp. 9-22, 2003.

[17] A. K. Pradhan, B. Chatterjee and S. Chakravorti, “Effect of Temperature on Frequency Dependent Dielectric Parameters of Oil-paper Insulation under Non-sinusoidal Excitation”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 21, No. 2, pp. 653-661, 2014.

[18] D. Dey, B. Chatterjee, S. Chakravorti and S. Munshi, “A Hybrid Filtering Scheme for Proper Denoising of Real-Time Data in Dielectric Spectroscopy”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol.14, No.5, pp.1323-1331, 2007.

[19] J. Gao, Y. Wang, R. Liao, C. Qi, J. Liu, "Effect of Temperature Change Mode on Condition Assessment of Oil-paper Insulation Using Frequency Domain Spectroscopy", proceeedings of International Conference on High Voltage Engineering and Application (ICHVE), Poznan, 2014.

[20] E. I. Koufakis, C. D. Halevidis, A. D. Polykrati, and P. T. Tsarabaris, "Calculation of the Activation Energy of Oil-Paper Insulation in a Distribution Transformer", IEEE Electrical Insulation Magazine, Vol. 28, No. 2, pp. 52-58, 2003.