CHAPTER 1 INTRODUCTION

Transcription

1 1 CHAPTER 1 INTRODUCTION 1.1 GENERAL The efficacy of a power system depends mainly on the reliability of the power equipment connected to the system. The power transformer is one of the most essential components of power generation and transmission system. Any failure in the power transformer will have a crucial impact on the system operation. The detailed survey of transformer failure reports shows that more than fifty percent of the failures in power transformers are due to insulation failures in windings (CIGRE JWG 12/13/23.21, 2002). For a successful operation, the transformer winding insulation has to withstand the electric stress during operation without any major damage for the expected life time. Most of the insulation failures are due to the gradual deterioration of insulation, which are mainly due to partial discharge (PD). PD may occur anywhere within the transformer winding where the insulation becomes weak. When the transformer insulations are highly stressed, the voids present within the solid or liquid or gaseous insulation generates PD. PDs are small electrical sparks (discharge) resulting from the localized dielectric breakdown of small voids in insulation system. PDs within an insulation system may or may not exhibit visible discharges and these discharge events tend to be more sporadic in nature than corona discharges. PDs can be prevented through careful design and proper selection

2 2 of insulation material. Once PD is initiated, PD causes progressive deterioration of insulating materials, ultimately leading to electrical breakdown. PDs are very short pulses of duration from tens of ns to 5µs. If the locations of PD are detected and rectified at an early stage, the incipient insulation faults can be minimized. Otherwise, the strength and frequency of PDs increases leading to catastrophic failure of transformer insulation. PD measurement is performed to assess the design adequacies and overall integration of the insulation systems and this has been accepted world wide as non-destructive quality-control to test the power equipment after manufacturing. For a quantitative judgment on the PDs, the apparent charges are used, which can be determined with the help of calibration pulses (Wenzel et al 1998). PD measurements are mainly affected by presence of noise. In order to enable diagnostic and maintenance procedures, location of the PD source is of major importance which is not straightforward due to the complex structure of the transformer. For the location of PD, a number of electrical methods (digital filtering, polarity location, capacitive location and traveling wave etc.,) and non-electrical methods (optical, chemical, acoustical method etc.,) have been used. Each method has its own merits and demerits. Generally, electrical methods are more sensitive and preferable for online PD (Wang et al 2005) and electrical methods are standardized by International Electrotechnical Commission (IEC) and Institute of Electrical and Electronics Engineers (IEEE). In this research, an attempt has been made to locate PD in transformer windings with the PD pulse durations of 0.1µs to 5µs using correlation methods.

3 3 1.2 A BRIEF REVIEW OF LITERATURE Surveying the literature helps to gain knowledge about the work done previously and steps to be taken to move forward in a particular field of interest. The literature survey is done under the following broad categories: Transformer failures PD in transformer windings PD measurements PD detection and location Transformer failures Many transformer industries and committees are conducting surveys on transformer failure statistics to improve the design of transformer. As per the international survey on transformer failures conducted in 1983 by CIGRE WG 12.05, typical failure rates for large power transformers with winding voltages upto kV are in the range of 1-2% per year. Though this is lesser in percentage, proper care should be taken because even a small winding failure in a transformer usually results in large expenses for the utility. An extensive survey by MSA Minhas et al (1990) in South Africa revealed that the most common cause of failure in the early service life of large power transformers is due to insulation failure. The Mexican Utility (CFE) (1999) reported that 53% of the failures in power transformers occur in the insulation system and mainly due to electromagnetic transient overvoltages. The transient overvoltages produce high dielectric stresses that can damage the turn insulation which can lead to failures like short circuit between turns, layers or discs of the transformer. The

4 4 short rate of rise of the surges (in the order of ns) and high amplitude (1.5pu-2.5pu) of the surges are dangerous for the insulation (Cornick et al 1992). The nonlinear voltage distribution in the windings is mainly due to short rate of rise and it may lead to failures on winding insulation. A five-year survey (from ) by William Bartley (2003) on the causes of the failures is shown in Table 1.1. It is seen from the table that the number of failures in power systems equipments is mainly due to insulation failure. Insulation failures due to defective installation, insulation deterioration and short circuits are only included in this report. But, the exterior surges such as lightning and line faults are not included in the insulation failures. Table 1.1 Number of failures in power system equipments (Cause of failures in five-year survey) Cause of failure Number of failures Insulation failures 24 Design/ material/ workmanship 22 Unknown 15 Oil contamination 4 Overloading 5 Fire/Explosion 3 Line surge 4 Improper operation 5 Flood 2 Loose connection 6 Lightning 3 Moisture 1

5 5 CIGRE, Doble clients, CEA, ZTZ-service clients and South Africa have done the survey on transformer failure statistics and different components are involved in these reports. Bjerkan (2005) has tabulated these failure reports in objective manner and is reproduced in Table 1.2. Table 1.2 Failure statistics of transformer components Defective component CIGRE survey CEA Survey Doble clients ZTZservice clients South Africa Bushings / accessories Tap-changer Major insulation Aging of winding Winding distortion Core Leads All the values are in percentage The detailed survey of these transformer failure reports shows that the reliability of transformer is mostly affected by insulation failure. The insulation failure is the predominant part of faults and highest risk for all types of transformer failures. Insulation failures result in two kinds of winding faults in a transformer namely series and shunt faults. Series fault implies insulation failure between the discs or between the turns, while shunt fault implies insulation failure between the winding and earthed components like tank, core etc. The winding fault occurs over the entire length of the winding and results in system outage and a very high maintenance cost of transformer. Thus, identification and characterization of insulation failures is a fundamental requirement for the purpose of condition based maintenance.

6 PD in transformer windings Most of the insulation failures in transformer are due to gradual deterioration of winding insulation, which are mainly due to PD (Wang Xiaorong et al 1991, Wang et al 1999 and Mazhab Jafari et al 2008 etc.). PD includes a wide group of discharge phenomena such as internal discharges, surface discharges, corona discharges, continuous impact of discharges (Kuffel et al 2000). PDs within an insulation system may or may not exhibit visible discharges and these discharge events tend to be more sporadic in nature than corona discharges (Kreuger 1989). When a discharge is initiated, high frequency transient pulses of pulse durations from ns to µs are generated. The PD pulses are considered to be harmful in HV insulation systems such as transformers because they cause energy loss and gradually degrade the winding insulation. Generally, discharge pulses can be characterized by amplitude and pulse shape. The PD pulse at the place of origin is strongly dependent on the insulation medium. Typically, the durations of discharge phenomena in liquid dielectric media are much longer than in other media. Yamashita et al (1993) conducted experimental studies to analyze PD pulse duration in idealized dielectric medium and reported that PD pulses are in the range of very short duration of 200ns. Tanaka (1995) analyzed on PD pulse distribution and reported that single PD pulse can be discriminated within 100µs for a 50Hz voltage supply. Ma et al (2002) analyzed the rise time and the pulse shape of the discharge current. The discharge pulses are recognized as having a very steep wave front in few ns and short duration in the order of 10ns. The pulse shape of the discharge current is determined by void dimension such as its radius, height and the external measuring circuit.

7 7 Hettiwatte et al (2002) investigated on the propagation of PD pulses in transformer windings. Generally, the PD pulse propagation is decided by the instantaneous field distribution and it is determined by applied voltage and charge distribution on the void surfaces. In most of the practical cases, the PD pulse duration can vary from 100ns-10µs. Jitka Fuhr (2006) reported that the rise time of the PD current impulse at the origin, depends on the insulating material in which the PD source is active and may vary in the range between picoseconds (gas discharge) to several hundreds of ns (discharge in oil). Palani et al (2007a) analyzed on PD events in the literature and reported that PD events can occur from tens of ns to few µs. Si Wenrong et al (2008) investigated about the time-frequency characteristics of PD pulse using Wigner-Ville distributions. The PD pulse shapes are defined as a mono-exponential pulse, mono-exponential attenuation oscillation pulse, double-exponential pulse, and doubleexponential attenuation oscillation pulse PD measurements Extensive research has been conducted on the sophistication of the PD measurement and data processing methods. The acceptance criteria for identification of PD sources in transformers are the measured value of apparent charge in picocoulomb (in pc as per IEC 60270, 2000) or in µv (as per IEEE revised standard 62, 1994) during PD tests (Jitka Fuhr 2005). When the insulation is partially damaged, turn-to-turn short circuits occur resulting in rise in temperature and finally in the worst case, to fire accidents. Due to known PD sensitivity, manufacturers have to prove that dry type transformers do not have any PD with apparent charge above 20pC

8 8 according to the standards of IEC (2000). For this purpose, narrow band electrical PD measurements according to IEC (2000) are performed. PD measurement is normally conducted with narrow band detection instruments (Bartnikas 1987). During test on transformers, it is a common practice to use narrow band electrical PD pulse detectors (RLC detector type) that conform to ASTM (ASTM D1868, 2007), IEEE-62 (1994) and IEC (60270, 2000) standards and specifications. Conventional narrow band and wideband detectors can also be used to reduce the interference caused by signals. Narrow band detectors have a band pass filter/integrator with a bandwidth of about 10kHz or so, while wideband detectors have a band pass filter/integrator with a bandwidth of 100 to 400kHz. Ma et al (2002) reported that the narrow band detection technique can give an erroneous quantification and information loss due to the adoption of quasi-integration or existence of multiple overlapped pulses. The characteristic parameters which describe the shape of single discharge pulse cannot be described explicitly in narrow band detection. Vaillancourt et al (1985) reported that the transformer specimens function satisfactorily in a flat bandwidth of 200kHz, since spectral components of the discharge pulses undergo more attenuation between 200kHz to 1MHz. The frequency region of electrical PD detection methods mainly lies in the high-frequency (3MHz-30MHz), very high frequency (30MHz-300MHz) and ultra high-frequency (300MHz-3GHz) bands. Generally, the high frequency signals are measured by Hall Effect sensor or current measuring resistor or antenna. Different types of PD measuring techniques such as electrical detection method (according to IEC 60270, 2000), Ultra High Frequency (UHF) PD measurement (electromagnetic), acoustic PD measurement, optical

9 9 and chemical method are used for analyzing the PD phenomenon. Each method has its own merits and demerits. Masayuki Hikita et al (2008) analyzed the features of various PD measurement methods PD detection and location methods The PD signal detection and location is one of the main challenges for power utilities and equipment manufacturers. In practice, the accurate location of a PD source is difficult because of the complex insulation structure of a transformer. For the location of PD, a number of electrical methods (using UHF, digital filtering, polarity location, capacitive location and traveling wave) and non electrical methods (optical, chemical, acoustical method) have been used Electrical PD location method A reliable method to locate PD source in transformer would generally contribute to a better diagnostic tool for insulation failure. Jitka Fuhr et al (1993) reported that the PD signals at the measuring terminal represents the response of the transformer winding, core and insulating medium (RLC circuit) to the PD current pulse excitation. The measured PD signals can be categorized into capacitive components, traveling wave component (propagation of pulses along the conductor) and oscillating component. These components are strongly dependent on the design of the transformer and PD defect location. The capacitive component (visible in the signal at the neutral terminal) is caused by the transmission of PD pulse through the capacitive network of the transformer (high frequency range MHz) (James et al 1977) and it is immediately transmitted by winding parasitic capacitance. The

10 10 transfer of capacitive component of the current signal is used for location of PD and their limitations are as follows: Need for the capacitive component of the response is a restriction and adequate resolution cannot be obtained for all transformer windings (Bartnikas 1987 and Wang et al 1999). Very difficult to separate capacitive component (Bartnikas 1987 and Wang 1999). Valid over a limited frequency range and inadequate for studying PD propagation (James et al 1989). Cannot be used to locate the PD accurately if the neutral terminal of the winding is directly grounded. Traveling wave component is caused by the transmission of electro magnetic wave (120 to 180m/s) (Thoeng 1973) and it is dependent on the type of the winding (lower frequency range MHz). Jitka Fuhr (1993) suggested a method of comparison of voltage response by using traveling wave techniques. For PD location, the time delay between measured PD signals is used and the limitations of this method are as follows: Difficult to identify the time at which the start of the PD signal arrived at the two ends of the winding. This is particularly difficult when the neutral and bushing ends are terminated with different impedances (Wang 1999). It is better suited to high distribution constant (α) value of the winding. It is applicable in the low frequency range (James et al 1989).

11 11 Oscillating component is determined by the resonance frequency of LC circuit of insulating system (intermediate frequency range MHz). Frequency of oscillations used for PD location (Jitka Fuhr et al 1993). Wang et al (1998) developed simulation model for studying the propagation of PD pulse in transformer winding. The simulation model is constructed with frequency dependent circuit parameters of transformer windings. Wang et al (1999) developed a novel approach for PD location based on the PD pulse propagation characteristics. The differences in the responses of the measured current signals that result from a PD occurring at different locations are used for PD location. It is applicable to power transformers (continuous disc winding construction) operating upto 132kV. Wang et al (2000a and 2000b) developed feature template matching method based on zeros for PD location in main insulation and inter-disc insulation. Experimental studies are carried out on 110kV rating of continuous disc winding to validate the algorithm. Results indicate that location accuracy better than 5% of the winding length is normally achieved. Transfer function method is commonly used for different applications such as transient analysis, insulation coordination and design procedure at the high frequency range in power transformers. In recent years, application of transfer function method has been extended for diagnostic purpose. Stace et al (1997) used transfer function method for condition monitoring of power transformer to identifying faults such as winding displacement, inter-turn and inter-disc faults. Islam (1997) extended the transfer function method to identify the transformer faults through high frequency modeling of the transformer.

12 12 A few research studies have located PD based on zeros and poles of the transfer functions. Malewski et al (1988) reported that a reduction of pole height of the transfer function indicates the PD location during LI excitation. Hettiwatte et al (2002) reported that zeros are used to locate the PD source. But zeros of the measured line-end signals are difficult to detect when the source of the discharge is near the line-end. Hettiwatte et al (2003) devised the transformer model for location of PD along the winding which is valid upto 10MHz. Each turn of the continuous disc winding (distribution transformer) is modeled by a transmission line with distributed parameters. The transfer function is obtained by using frequency spectra of the measured terminal signals for locating the position of PD along the winding. The transmission line model is validated experimentally by using PD calibrator as a PD source. Stone (2005) summarized the features of modern PD measurement systems to improve PD diagnostic methods and also addresses the salient features of PD detection methods. Mitchell et al (2007) utilized a narrowband high frequency distributed transformer model to estimate the PD location. The cost function is applied to the PD response to locate the PD. Naderi et al (2008) reported that the poles in the transfer functions always occur at fixed frequencies and it is not affected by the location of the PD, while various simulations show that zeros of the transfer functions might be considered as an indicator of the position of PD. Masayuki et al (2008) extensively analyzed the similarities, differences and features of various PD measurement methods and also described the noise removal, PD location and foreign particle identification to study the PD in transformer winding.

13 Acoustical PD location method The first published discussion on the acoustical method appeared in 1964 (Ogihara 1964). Recently, several studies have been done on location of PD using acoustical method. The principle of acoustic method is based on the detection of pressure waves (rapid flow of electrons and ions create a gas pressure waves acoustically) generated in the event of discharges within the insulation systems. An overview of the application and limitation of the acoustic method for detection of the PD signals in transformers is reported by Beyer et al (1987). Van Haeren (1985) reported that the acoustic pulse created by each discharge is concentrated in the range of 40kHz (ultrasonic range). The sensitivity of the method is related to distance between the sensor location and discharge location, angle of incidence of acoustic signals to sensor, PD magnitude, acoustic impedance between sensor and discharge source (Raja Kuppuswamy 2002). Van Haeren et al (1985) reported that if discharges are occurring on the surface of an insulation system, then the rapid flow of electrons and ions create a gas pressure wave which can be detected acoustically. The acoustic pulse created by each discharge is concentrated in the 40kHz (ultrasonic) range. The transmission losses in different media with their interface (Kemp 1993) and level of the discharge with interference (Lundgaard 1992) should be considered when using acoustic PD location. The primary advantage of using acoustic detection over chemical and electrical methods is that, position information is readily available from acoustic systems using sensors at multiple locations. This position information can help to identify the type of PD as well as the location and severity of an insulation fault.

14 14 Another advantage of acoustic detection over electrical detection is its immunity to electromagnetic interference. Jitka Fuhr (1993) reported that the acoustical methods for detection and location of PD defects in power transformers are found to be successful only for defects positioned closed to the walls of tank. Wang et al (2005) reported that the location results could be sometimes misleading especially when there is solid insulation between the discharge source and the sensor. Li-Jung Chen et al (2007) proposed a digital non-contact type acoustic PD measurement system and adopted Phase Resolved Partial Discharge (PRPD) pattern to examine the features of discharge signals. The wavelet transform is used to suppress the noise in the discharge signals. The proposed acoustic measurement system is validated for epoxy-resin transformers. Markalous (2008) reported that the precise measurements of acoustic signal arrival time and robust positioning algorithms are essential for estimation of the PD location. The following two approaches are discussed for PD location: (i) Alterations of the signal amplitude or deformations of the signals shape along the propagation path can give hints for a source location (ii) Measured arrival times are used to calculate the origin of signals PD detection during impulse test The Lightning Impulse (LI) test is a routine test for power transformers rated above 132kV in order to assess the dielectric integrity of the windings at the Basic Insulation Level (BIL). Failure identification during

15 15 the test is a non-trivial task and IEC (2000) standard provides some guidelines about the magnitude, shape and sequence of application of the voltages for help assessment. The test procedure involves the application of the voltages from a Marx generator in a standard sequences (Kamaraju and Naidu 2000, Kuffel et al 2000). The test procedure implicitly treats the transformer as a linear system. Reliable online PD location is a critical need for power industry to improve personnel safety and decrease the potential loss during service. The various techniques have been developed for fault identification; the transfer function method (Malewski 1988, Leibfried et al 1999, Vaessen et al 1992, Hanique 1994) has gained some acceptance during LI test. The transfer function method which has quite a few adherents is based on computing transfer function of the winding. The method has also been extended to incorporate features such as fault identification and magnitude of the fault using wavelet transform (Vanaja 2001). The transfer function method is not a successful method always for fault identification during Chopped lightning impulse (CLI) compared to lightning impulse (LI) test (Leibfried 1999). The transfer functions obtained using CLI and LI wave shape cannot be compared. The standard IEC (2000) portrays the drawbacks of the transfer function. Palani (2007a) reported that the transfer function becomes undefined at locations where the frequency content of the voltage signal approaches the noise level as in chopped LI. The transfer function method implicitly treats the device under test as linear, but faults are always not linear. Thus, the transfer function method is not adequate for the case of faults that occur at different instant. Satish (1998) proposed a time frequency analysis tool (short-time Fourier transform) for analyzing the neutral currents directly for fault diagnosis during impulse testing of power transformers. Advantages of the

16 16 method over the conventional transfer function method are demonstrated and it appears that the wavelet transform is better suited for the location of PD. Wavelet analysis is best suitable for non-stationary signal (LI Jun-hao et al 2008). This method ignores the finite energy deterministic nature of the input signal. The main limitation of this method is that it does not provide good resolution in both time and frequency domain because of its fixed window width (Naderi et al 2008). The wavelet transform is a tool that splits the data of functions or operators into different frequency components and then studies each component with a resolution matched to its scale. In comparison with shorttime Fourier transform, wavelets have a window that automatically adjusts to give the most appropriate resolution (Kim and Aggarwal 2000). The wavelet transform can give information in both time and frequency domains. The advantage of wavelet transform is that, the band of analysis can be adjusted so that the high frequency and low frequency components can be precisely detected. Butler and Bagriyanik (2003) used wavelet transform for analyzing the transient phenomena associated with the transformer fault. Unlike the basis function used in FT techniques, wavelets not only localize in frequency but also in time. This localization allows the detection of the time of a sudden fault occurrence. Wavelets can also provide higher precision time resolution for short duration higher frequency signals as well higher precision frequency resolution for long duration low frequency signals (Naderi et al 2008). The existing method of impulse testing involves the analysis of the response from current measuring resistor through High frequency current transformer (HFCT). Jayalalitha et al 2004a and 2004b suggested that the acquisition of the winding response through three analog filters (triple filter approach) namely low pass, band pass and high pass filter is used for detection of PD.

17 17 Gopalakrishnan et al (2003) and Jayalalitha et al (2006) proposed time domain correlation method (matched filter approach) for location of PD in transformer windings. The simulation and experimental studies are performed on lumped layer winding to validate the efficacy of method. The correlation method locates the PD in the presence of noise. A phase-sensitive detector is known to provide extremely high accuracy in identifying sinusoids in the presence of noise (Blair et al 1975). One can utilize the fact that the current response of the winding is measured and compared with fault current response. A PD phenomenon affects the current signal at a region close to noise floor. Palani et al (2007a) developed a Virtual Instrument (VI) based on phase-sensitive detection principle. A Virtual Instrument is developed for analysis of impulse test records in transformers. The front-end hardware has three analog filters that precede three digitizers with varying resolution. The breakdown and PD events can be identified clearly and the drawback of the transfer function method is highlighted. Palani et al (2007b) suggested a lock-in amplifier technique for detection of PD within the winding during impulse test on a transformer. The lock-in amplifier technique is implemented with a Virtual Instrument and it is validated with hardware implementation using lock-in amplifier (SR-830 DSP, 102 khz lock-in amplifier). Digital acquisition of waveforms has led to increasing research study in the area of failure analysis. Some of the techniques for achieving the foregoing task are analyzed for identification and location of PD. It can be noted that only limited success has been achieved for PD location. The limitation with several studies on PD location is that the most of the electrical methods are not optimal in the presence of noise. In this study, the efficacy of the correlation method is used for PD location in transformer windings.

18 SCOPE OF THE PRESENT WORK Scope of this study lies in PD location within the transformer windings for different PD pulse durations. In this study, correlation based methods are proposed for PD location with the PD pulse durations of 0.1µs to 5µs. Amongst the various methods that have been developed for PD detection, transfer function method have gained some acceptance. The fundamental issues in transfer function method have always been frequency resolution and Signal-to-noise ratio (SNR) at higher frequencies. It would be useful to develop methods that can work under circumstances of improving the SNR too. Hence, in communication theory, the correlation method is known to be the optimum method for detecting a pulse of known shape contaminated by additive noise with known spectral density of the signal. In other words, the correlation method is optimal for detection of PD signal in the presence of noise provided that only the reference responses are known (Whalen 1971, Veen et al 2003, Jayalalitha et al 2006). Hence, the principle of correlation method is used for PD location in transformer windings. The correlation method is only valid if one can physically inject known / reference pulses at various sections and then to establish correlation. In practice, this might not be possible. Hence, the correlation method can be adopted to a general case as follows. The responses of the transformer winding for PD are estimated theoretically using an accurate equivalent winding circuit model by injecting reference / known pulse across the different section of the transformer winding and the measured winding responses is used as reference signals (reference responses) for correlation. In practice, if a PD response of the winding is measured at the current measuring resistor across HFCT, one can identify the PD location by correlating reference responses and real PD response using correlation method.

19 19 To study the responses of the transformer windings with different PD durations from 0.1µs to 5µs at different sections, it becomes necessary to use a simple model which can be realized in practice with ease. To fulfill this requirement, a PD model in terms of a voltage pulse source is suggested to simulate the PD in transformer winding with different pulse duration. The correlation methods are validated on 22kV transformer windings namely layer, continuous disc and interleaved windings. All the windings are provided with tappings at every 10% of the winding for injection of PD with different pulse durations. The present work starts with voltage pulse represented as a PD across the sections of the windings for studying the efficacy of the correlation method. The PD location using correlation method is performed by injecting a PD pulse durations and the winding responses are analyzed both in time domain as well as in frequency domain to characterize the behaviour of the transformer windings. Generally, the frequency domain measurements will always contain noise at higher frequencies. This has led to the use of Butterworth bandpass filter. The proposed methodologies are applied for all types of transformer windings, demonstrated by measurements and validated with PD calibrator and live discharges to locate the PD within the transformer windings. The proposed methodologies are validated with 25MVA, 220/6.7kV power transformer to locate the PD using circuit simulation package (PSPICE).

20 ORGANIZATION OF THE THESIS This thesis is organized into seven chapters as detailed below: Chapter 2 presents a simple PD model which can be easily realizable to understand the transformer winding behaviour both simulation and in practice for PD of different pulse durations. The experimental winding responses of commonly used transformer windings viz. layer, continuous disc and interleaved windings are presented, when different duration of PD pulses are injected across each section. Chapter 3 presents the normalized and orthonormalized correlation methods for PD location with different pulse durations from 0.1µs to 5µs. The experimental test PD response due to injection of different pulse duration is effectively used for correlation methods. The Butter worth bandpass filter is also used to improve the performance of the correlation methods. Chapter 4 presents the least difference methods for PD location to locate the PD in transformer windings. Chapter 5 presents regression analysis with statistical correlation method for PD location. Chapter 6 deals with validation of the correlation based methods with PD calibrator and live discharges. An attempt has also been made to validate the correlation methods on 25MVA, 220kV/6.7kV power transformer for PD location by using circuit simulation (PSPICE). Chapter 7 presents the summary and conclusions. The scope of the future work is also highlighted.