A Comprehensive Comparative Study of Practical Experience-based Transformer: Utilizing Cross-Combined Frequency Response Analysis for Specific Deformity Identification

1

Bagas Maulana Sutardi1.2*, Ario Wulung1.2, M. Helmi Prakoso3 , Ricky Faizal2 , Umar Khayam1 and Suwarno1

School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia 2 PLN Corporate University, PT PLN (Persero), Jakarta, Indonesia 3 PLN Head Office, PT PLN (Persero), Jakarta, Indonesia *Corresponding author: bagasmaulanasutardi@gmail.com

Abstract: Transformers are among the majority worthwhile and significant parts associated with machinery with high voltages. Transformers that provide electricity ought to undergo routine inspections for visible degradation as well as prevent the formation of flaws that could eventually result in a major breakdown. By using this expertise to identify these modifications, testing instruments have previously shown that response-frequency assessment remains a viable approach. Despite our lack of knowledge of the factors that generated the alterations in the first place, FRA continues to be utilized up to that point to identify distortion throughout these devices by detecting modifications to the response time profile. A while ago, several FRA techniques were put into practice globally, mostly toward identifying and diagnosing the cause of conversion displacement. However, an expanding investigation is being carried out to precisely identify the kind and magnitude of distortion within the transformer's structure through examination of its FRA sensitivity profile. To guarantee the correctness of the examination of frequencies responsive data, therefore one must review the advice provided throughout the who have been freed IEC, IEEE, SPLN, and CIGRE specifications. The remainder of this piece discusses an electrical transformer diagnosis technique through crossreferencing specifications and practical FRA data as well as performing a comparison evaluation involving different experimental examples of different natural events.

Keywords: SFRA, IEC, IEEE, CIGRE, Frequency Response, Diagnosis Tools

1. Introduction

Network operators must ensure that the high-voltage transformers remain in excellent working order to maintain the electricity mechanism's reliability. high-voltage conversion devices are required to be inspected following an occurrence to determine when significant wear and tear took place. Transformer problems may develop from several events, including storms, panel changes, seismic events, and short-circuiting contacts [1]. Because coil dislocation with displacement contributes to a large percentage of breakdowns associated with electrical Transformers, having an accurate strategy for harm diagnosis is necessary. The frequency-dependent reaction Investigation approach is widely used because of its superior accuracy in identifying this type of degradation. The foundation of FRA involves the theory because variations with the corresponding circuit configuration that constitutes the changer, namely within the values of L, C, as well as R, influence the electrical frequency sensitivity concerning the converter through mirroring variations within the shifting in addition to distortion of the wounds. A common technique for obtaining the range of sensitivity includes SFRA.

Received: May 14th, 2023. Accepted: December 30th, 2023

DOI: 10.15676/ijeei.2023.15.4.7

A. Basic SFRA

Arguably, particularly expensive, and consequential parts of the electricity grid continue to be transformers that regulate electricity. The previous SFRA was particularly vulnerable regarding testing methods because it could inhibit comparison and therefore cause outcomes of tests to be interpreted incorrectly. The necessity for a precise assessment of the facilities' integrity increases as converter squadrons mature. Perhaps the most effective and reliable method for locating strain and wiring issues associated with electrical converters is the Sensitivity Investigation.

Several research projects conducted worldwide utilize various techniques to investigate the ideal layouts for the proposed FRA. A while ago, some FRA techniques were successfully put into practice globally, mostly enabling the recognition and identification of converter distortion. A range of approaches have been proposed subsequently regarding SFRA evaluation, such as using statistics as well as specialist views. By combining real value with an established estimation, electrical or physical shifts in the core of the magnetic field coil together, et fastening framework may be found. Although this initial method usually relies upon judgment as well as knowledge, it is not unbiased or transparent. On deciding to consent to the data, the seasoned researcher looks over the whole wavelength. His primary focus is on vibration position along with amount.

B. Literature Review

A previous work [2] analyzed the efficacy of different operating procedures in converter diagnosis to determine which one would be more successful. Any technique is applied by the info that needs to be extracted out of the converter. A technique used to evaluate the physical condition of the winding of the converter as well as the inner is called responsive evaluation. In essence, this technique measures the amplitude behavior of the converter core. This is the background of FRA testing shown in Figure 1. The graphic illustrates the measuring spectrum, which ranges from 20 Hz to 2 MHz the following constitutes the recommended conventional wavelength spectrum, per [2] and [3]. The estimated response is a plot of the peak and valley phases of what happens.

The detected production provides information about the structural makeup of the coil and center. The primary reaction might be affected by changes that are made to the components. Consequently, the technique of FRA assessment is obtaining two measures (one before the other after), correlating them as well, and discovering any variations. A frequent application using FRA in the industry involves determining the initial (the beginning) as well as secondary reactions to frequencies before as well as following delivering the converter onto the location. A few scenarios when FRA are utilized were noted in Referring [2]: (i) transformers relocation or moving; (ii) after an enormous through-fault event; (iii) as a reaction to a malfunctioning transformers alarm; and (iv) examination of manufacturing shorts.

2. State of Practice

A newly developed and practical method has been offered and applied to distinguish and distinguish the range with low frequencies of the device output analyses from the middle and upper frequencies in the circuit feedback characterization. Transformer coils that have been operating unusually are intended to be found via frequency response analysis [3]. It is important to recollect that the insulator quality of the transformer is a dynamic factor that varies with its capacity to operate and can affect its FRA [4] while conducting a functional reserve assessment (FRA) examination to assess a device's technical integrity. Currently, a few specialists are looking at the effects of insulator levels. The main problems of the transformer failure stem from the failure of the transformer insulation. Therefore, insulation testing and monitoring are very important to ensure the operation of the transformers [18]. The degradation of paper is one of the main lifetimes deciding factors for transformers and has been studied for several decades [17]. Most of the faults inside the transformer occur in its insulation system, which may be damaged due to exposure to thermal, mechanical, or electrical stresses [19].

A. Wideband FRA

Evaluation instrument approaches are utilized to identify alterations or distortions that affect the transformer's physical parts, with the value of the core or windings. As demonstrated in Figure 1 [4], residuals may modify the SFRA output curve's shape, decreasing the transformer's signal signature's credibility. SFRA represents a cross-combined technique consisting of the following commonly utilized tackles for assessing the depicts gained from a transformer. A seismic event represents a few triggers because there is displacement [1], [9]. Before performing any more assessments, the SFRA examination is performed to prevent polarity from being retained in the inner core of the transformer due to magnetic absorption following an assortment of magnetic testing. [10, 11]

Figure 1. The region in Frequency Response Analysis

B. Methodology

Sensitivity assessment is regarded as an effective, rapid, inexpensive, and not harmful way of discovering winding issues. The notion of a cross-valid simply implies developing an argument based on one set of data and testing it with a second. This concept is used to model selection as follows. The best optimal procedure for each case is determined via a multidimensional examination. This study will look at four different experimental scenarios.

• Exercise 1: Degradation of fluids
• Exercise 2: Displacement evaluation scenario
• Exercise 3: Reestablishing the electrical transformer's basis.
• Exercise 4: Seismic Investigation

B. Instrument Setup

Using the FRA technique to monitor the condition of critical transformers that convert electricity in networks for transmission as well as distribution is nothing new. The realization notion of the AC resistivity or admittance in each RLC circuit related to frequency seems arguably as old as the discipline of electricity design itself. As demonstrated in Figure 2, frequency shift modeling is being lauded as an important enhancement in coil condition tracking since it allows for simulated viewing of each core inner workings requiring the expenditure of core de-tanking.

Figure 2. Instrument for Frequency Response Analysis

3. FRA Specification and Guidelines

A signal examination is a standard approach for diagnosing breakdown that rapidly and correctly detects transformer electricity coil displacement while preserving results distortion and strong reliability. A variety of factors including nature or stimulating strength, frequency response analysis is separated into harmonic period response methods and sweep frequency response analysis. The sinus response in frequency technique has been used more frequently in China's power sector standards and IEC standards. To guarantee the correctness of the frequency responsiveness analysis results, it is critical that one stick to the detailed instructions provided in the recently issued IEC, IEEE, SPLN, as well as CIGRE specifications [5] - [8]. The current research discusses a method for circuit examinations through carrying out comparisons on 4 investigation scenarios connected to different physical events while assessing the cross-comparison of criteria of actual real FRA conclusions.

A. IEC Guideline

To produce SFRA evaluations, IEC Standard: IEC60076-18 Ed. 1 – 201, an inadequate voltage for the output around 0.1 V and 10 V usually gets used—sometimes even under difficult situations. The broadband range is defined as having an initial design range of -90 dB and a maximum configuration range of about +10 dB [5]. Furthermore, it has the advantage of being estimated as the minus test range + 20 dB according to experience accumulated throughout the years. Outside problems can be reduced by using proper connecting procedures, as demonstrated in Figure 3. The IEC 60076-18 guideline [5] details the proposed method for an appropriate and reproducible measurement setup.

Figure 3. Instrument Standard IEC

To get the highest ratio of signals to noise probable, conventional wisdom recommends utilizing coaxial tubing has been selected for SFRA tests, but requires being connected by thick, smooth metallic braids. As indicated in Figure 3, a grounded system's influence on the SFRA results ought to be continually tightly looped onto the bushing's structure. [14] The connecting technique used must maintain a substantial degree of precision, particularly within extreme-frequency zones like those above 500 kHz [5].

B. IEEE Guideline

To better comprehend and evaluate any changes to the FRA response, IEEE C57.149 Guide, it is useful to know which elements supervise the different parts and shapes of the response curve. Examining the distinct responses of all the components and their mixes will help achieve this. When a converter winding acts as an inductor constituent at low frequencies, the end-to-end FRA response shows a lowering intensity trend throughout the bandwidth domain and a progressively diminishing inclination of near -20 dB each century [6]. At elevated frequencies, where a converter coil acts as a sensitive component, the end-to-end FRA signal exhibits a developing strength trend throughout the bandwidth spectrum and has a linear decreasing slope of about 20 dB each period, as seen in Figure 4. [13] As capacitors increase, the magnitude also increases. Smaller adverse response values at high levels are frequently observed in power transformers with higher voltages and greater output [6].

Figure 4. IEEE bandwidth FRA

C. DL/T 911-2004

Utilizing the spectral sensitivity measurement technique, transformer coil distortion is assessed in compliance with the national standard DL/T911-2004 for the electrical power industry. The rate response curve of characteristics will exhibit a noticeable shift at low ranges when the winding induction fluctuates. For many transformers, the low-frequency band should be very comparable. [13] In the event of a disparity, the underlying cause must be found. Evidence of local winding deformation, including twisting and hunching, is frequently seen in the measurement of frequency noticeable changes in signal locations in the medium-frequency band (100 kHz to 600 kHz). There are several distinct variations in the response characteristics curve within this frequency band. The noticeable shift in response characteristics measured in high-frequency bands (>600 kHz) indicates a change in the capacitance-to-ground of the winding, which may be caused by the movement of the leading wire or the entire coil. At higher frequencies, the winding has a larger inductance and a smaller capacitance [7], [14].

D. Technical Standard CIGRE 342

According to the one indicated in Table 1, the bandwidth variation in Cigré demonstrates the usual variations behavior for modulating the wires with a substantial mixed intermediate Power class [8], high electricity (HV), along with low voltages (LV). [12, 16]

Table 1. Standard of CIGRE for Transformer [8]

4. Validation of the Findings and Exercise

A. Exercise 1: Degradation of fluids

Water-pollution research circumstances involving an electrical substation. As can be seen in the following illustration, the brightly colored experiment represented the updated experiment related to the R-N major 150 kV cycle SFRA examination, while the gray assessment represented the test that had previously been conducted since the previous year's antecedent to the displacement. The data visualization demonstrates how Ring 1's relapse differs significantly among the remainder of the bandages. Ring 1's relationship proved to be beneath its 0.95 reliability criterion, suggesting that the newly reported outcome was achieved after a loud shift in water pollution. The findings of the S-N, as well as T-N open-circulation techniques, were identical and the intensity of the current is increasing, as Figures 5 illustrate.

Figure 5. Open-circulation r-n frequency response analysis

The following result pertained to the open-circulation method supplementary frequency response analysis evaluation. The magnitude that corresponds to the latest findings had been claimed after liquid contamination differs from the Previous frequency response analysis accomplishments, as seen in Table 2. This means that Table subsequently shows the reason for the greater intensity was likewise caused by the fluid ingress pollution within the identical range as in the initial period experiment.

Table 2. Exercise I dependency factors.

Moreover, the relationship between variables in Stage 1 is smaller, below 0.96, suggesting that interference is likely to be blamed for the poor performance. The identical result happened through the s-n as well as t-n cycles. During the overall R-N SFRA Investigation utilizing that closed-circuit technique, the peak magnitude varied about at Stage 4, despite it staying throughout the relationship's restriction. The previous Initial outcome appeared in navy, whilst the amended outcome after pollution was shown with yellow. Amplification of Stage 4 is now lower, suggesting the fact the structure's coil and gripping region were impacted by some liquid incursion pollution.

B. Exercise 2: Displacement evaluation scenario

The second scenario in conjunction with the displacement evaluation scenario depicted in Figure 6.

Figure 6. Open-circulation R-N frequency response analysis Table 3. Exercise II Dependency factors

Furthermore, the regression coefficient during Stage 1 is smaller, above 0.969, suggesting that displacement is probably the cause of the poor performance. The identical result was achieved on the s-n as well as t-n cycles. During the R-N SFRA Investigation utilizing the overall closed-circuit technique, the peak magnitude varied at about Stage 5, but it stayed over the relationship's threshold. As seen in Table 3, the reduction within the intensity of Stage 5 suggests that the structure's circulation is being impacted by certain displacement.

C. Exercise 3: Reestablishing the electrical transformer's basis.

The scenario with the basis of the investigation scenario replaced as well rebuilt is depicted in Figure 7.

Figure 7. Open-circulation R-N frequency response analysis

Table 4. Exercise III Dependency factors

Reestablishing upon a basis is the reason underlying the poor performance, as Table 4 indicates that the relationship in Stages 1 and 2 equals 1. The identical result was achieved through the s-n along with t-n periods.

D. Exercise 4: Seismic Investigation

This exercise is the scenario alongside the case relating to the seismic investigation, as displayed in Figure 8.

Figure 8. Seismic R-N frequency response analysis

For pair of stages graphs, within example 4 exhibit a minor change across the middle-frequency Stage, with an increase within the R cycle's strength along with a decrease in the transient stage's size.

Table 5. Exercise IV dependency factors

Remodeling from the base remains the reason for the poor performance, as Table 5's relationship during Stage 1 equals 1. The identical result was achieved throughout the s-n as well as t-n cycles. By the overall R-N SFRA Investigation utilizing the overall closed-circuit technique, the peak value varied about at Stage 4, despite nevertheless staying throughout the relationship's restriction. Any among plate defect may be recognized through a rise in the reactivity curve's height. Shorting is a breakdown and extra friction may result in adjustments to the orientation of the plate spaces. Nevertheless, a decrease throughout the resultant curve's strength indicates the existence of electrical leak flows, such may have been brought through the deterioration of the substance with fluid, earth protection deterioration, or a significant amount of humidity inside the wire.

5. Conclusion

In this study, a strategy for determining the best criterion along with the procedure for assessing a power transformer's operational consistency was presented, along with feedback characterization from the various standards. Although it's several SFRA measurement methods offered, researchers need to proceed with beware when performing the measurement considering several issues, the most significant of which relates to the inner magnetization influence. When measuring through an open loop, the ripple effect of the coil inductor is less pronounced during the lower frequencies range compared to the value of the inner inductor. Up to 2 KHz is the frequency range of the effect. Thus, demonstrated by the previously mentioned instance, the inner magnetization phenomenon might cause us to receive replies regarding damaged transformers even when the device itself is in fine condition. This article discusses a transformer test technique by cross-referencing guidelines and practical Assessment information as well as carrying out a comparison examination involving 4 experimental examples of different natural events. According to the findings of the review, the

diagnostic methods developed by IEEE along with IEC contain a highly precise measurement of the real state.

6. Acknowledgment

The authors express their great appreciation to the PLN, Indonesia's state-owned electricity company, and STEI (School of Electrical Engineering and Informatics), ITB, Indonesia, for the support given to enable the authors to complete this research.

7. References

• [1]. M. Bagheri, M. S. Naderi, T. Blackburn, and T. Phung, "FRA vs. short circuit impedance measurement in detection of mechanical defects within large power transformer," IEEE International Symposium on Electrical Insulation (ISEI), 2012.
• [2]. S. A. Ryder, "Methods for comparing frequency response analysis measurements,", 2002 IEEE International Symposium on Electrical Insulation, USA, 2002.
• [3]. D. K. Xu, C. Z. Fu and Y. M. Li, "Application of artificial neural network to the detection of the transformer winding deformation," 1999 Eleventh International Symposium on High Voltage Engineering, UK, 1999.
• [4]. A. Kraetge, et. al., "Aspects of The Practical Application of Sweep Frequency Response Analysis (SFRA) on Power Transformers" CIGRE 6th Southern Africa Regional Conference, 2009.
• [5]. IEC 60076 18, "Measurement of frequency response", TC 14 Power transformers, 2012.
• [6]. "IEEE Guide for the Application and Interpretation of Frequency Response Analysis for Oil-Immersed Transformers," in IEEE Std C57.149-2012.
• [7]. Professional Standard of the People's Republic of China: "DL/T 911 2004 Frequency Response Analysis on Winding Deformation of Power Transformer", 2006
• [8]. CIGRE Technical Brochure No. 342, "Mechanical condition assessment of Transformer windings using Frequency Response Analysis (FRA)",
• [9]. PT PLN Persero, SK DIR Book of Power Transformer Maintenance. Indonesia, 2014.
• [10]. Muhammad Helmi Prakoso, Rizky Fajar Maulana, "Excessive Water Content Identifying Approach Using Sweep Frequency Response Analysist and Electrical Individual Test for Power Transformer," 2019 International Conference on Technologies and Policies in Electric Power & Energy, Indonesia.
• [11]. K. G. N. B. Abeywickrama, Y. V. Serdyuk, and S. M. Gubanski, "Exploring possibilities for characterization of power transformer insulation by frequency response analysis (FRA)," IEEE Trans. Power Del., 2006.
• [12]. CIGRE 445 Guide for Transformer Maintenance, Paris, France: CIGRE Publication, 2011.
• [13]. E. P. Dick and C. C. Erven, "Transformer diagnostic testing by frequency response analysis," IEEE Trans. Power App. Syst., 1978.
• [14]. Abu-Siada, A.; Hashemnia, N.; Islam, S.; Masoum, M.S.A. Impact of Transformer Model Parameters Variation on FRA Signature. In Proceedings of the 22nd Australasian Universities Power Engineering Conference (AUPEC), Indonesia, 2012.
• [15]. PT PLN Persero SK DIR Book of Power Transformer Maintenance, Indonesia, 2014.
• [16]. CIGRE 349 Moisture Equilibrium and moisture migration within transformer Insulation System, France, CIGRE Publication, 2008.
• [17]. Alvin Ritonga and Suwarno. Study of Thermallay accelerated aging of Transformer Insulation Paper in Mineral Oil and Gas-to-Liquid Dielectrics using Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA) and X-ray Diffraction (XRD). International Journal on Electrical Engineering and Informatics (IJEEI), Volume 13, Number 12, September 2021

• [18]. Korraya Jongvilaikasem, Norasage Pattanadech, Wilasinee Wattakapaiboon, Masaaki Kando, Sakda Maneerot and Pittaya Pannil. The Comparison of DGA Interpretation Techniques Application for Actual Failure Transformer Inspections Including Experience from Power Plants in Thailand. International Journal on Electrical Engineering and Informatics (IJEEI), Volume 14, Number 14, March 2022.
• [19]. Sherif S. M. Ghoneim. Identification of Power Transformer Insulating Paper's State Based on Principal Component Analysis. International Journal on Electrical Engineering and Informatics (IJEEI), Volume 14, Number 3, December 2022.

Bagas Maulana Sutardi received a B.Sc. degree from the Electrical Engineering and Information Technology Department, Gadjah Mada University (UGM), Yogyakarta, Indonesia, in 2017. He has a passionate interest in renewable energy, system planning, energy investment, HV-MV systems, stability studies, and dynamics made him participate in some scientific projects and research, especially on tackling Energy problems. He has experience as an HV-MV Power System Dispatcher, Energy Transaction, and System Planning Engineer in PLN. He is currently a PLN scholarship awardee at ITB, Bandung, Indonesia with a joint-

master research program at Alma Mater Studiorum - Università di Bologna, Bologna, BO, Italy to study intelligence for novel materials and reliability: digitalization of power electronic applications within key technology value chains, a project in collaboration with the public-private partnership, Università di Bologna, and European Union.

Ario Wulung received a B.Sc. degree from the Electrical Power Engineering from Institut Teknologi Bandung in 2011. He has experience as an Energy Transaction, Medium Voltage Customer Substation and Metering Maintenance, and Electrical Power Losses Control Engineer in PLN since 2014. He has interests in diagnostics on high voltage equipment, renewable energy, and asset management. He is currently a PLN scholarship awardee at ITB, Bandung, Indonesia with a jointmaster research program at Graz University of Technology, Graz, Austria to study Diagnostic on Power Equioment especially on High-Voltage Conductor, Cable,

and Gas Insulated Switchgear (GIS).

Muhammad Helmi Prakoso earned a BSc in Electrical Power Engineering from Institut Teknologi Bandung in 2015. PLN, an Indonesian electricity corporation, has employed him since 2015. He assessed and developed West Kalimantan power grid electricity from 2016 to 2022. High-voltage electrical, asset management, and procurement are his specialties. He likes high-voltage and asset management R&D. He publishes IEEE papers on high-voltage engineering research and development annually. In 2022–2023, he worked with the transformation division to analyze smart meters and digital procurement at PLN

Headquarters. He is currently an MSc Candidate in Sustainable Energy Systems at Edinburgh University, studying Indonesian sustainable energy development.

Ricky Faizal received the B.Sc. and M.Sc. degrees from the Department of Electrical Engineering, Institut Teknologi Bandung, Indonesia, in 2005 and 2014. He earned a PLN scholarship awardee at ITB, Bandung, Indonesia with a jointresearch program at the University of Graz, Graz, Austria. He is an experienced manager with a demonstrated history of working in the power utility industry. Skilled in PSS/E, DIgSILENT Power Factory, Power System Operations and Planning, Load Forecast, and Energy Management. Strong professional with a

master's degree focused in Power System Engineering from Institut Teknologi Bandung (ITB). Currently, he is the Vice President RUPTL Control of PT PLN (Persero), Indonesia since 2023.

Ova Kurniawan received a bachelor's degree in Sociology from University Indonesia, Jakarta, Indonesia, in 1992 and received an M.M. degree in Strategic Management from Prasetya Mulya Business School, Indonesia, in 2007. He earned an M.Eng.Sc. degree in Electrical Engineering from Universiti Tenaga Nasional, Malaysia, in 2008. He is currently an executive vice president of transmission strategic planning at PT PLN (Persero) based in Jakarta, Jakarta, Indonesia.

Suwarno (Senior Member, IEEE) received the B.Sc. and M.Sc. degrees from the Department of Electrical Engineering, Institut Teknologi Bandung, Indonesia, in 1988 and 1991, respectively, and the Ph.D. degree from Nagoya University, Japan, in 1996. He is currently a Professor and the Emeritus Dean of the School of Electrical Engineering and Informatics Institut Teknologi Bandung. He is currently serving as the Head of Electrical Power Engineering Research Group, School of Electrical Engineering and Informatics, ITB. He has published over 260 international journal and conference papers. His research interests include high

voltage insulating materials, technology, and diagnostics of HV equipment. He received the Student Best Awards from IEEJ Japan, in 1994 and 1995; from IEEE Queensland, Australia, in 1994; and from ACED Seoul, South Korea, in 2002. He was elected as The First Winner of Outstanding Indonesian Lecturer by The Ministry of Education and Culture, in 2009. He was the General Chairperson of several IEEE sponsored international conferences such as ICPADM 2006, ICEEI 2007, CMD 2012, ICHVEPS 2017, ICHVEPS 2019, and ICHVEPS 2021. He has been listed in top 2% of the world's most influential scientists according to a study conducted by Stanford University 2021. He is the Editor-in-Chief for the International Journal on Electrical Engineering and Informatics.

Umar Khayam (Member, IEEE) received the B.Sc. and M.Sc. degrees from the Department of Electrical Engineering, Institut Teknologi Bandung, Indonesia, in 1998 and 2000, respectively, and the doctoral degree from Kyushu Institute of Technology, Japan, in 2008.,He is currently an Associate Professor with the Power Engineering Research Group, School of Electrical Engineering and Informatics, ITB He is also the Head of the Laboratory of High-Voltage and High-Current Engineering and the Doctoral Study Program of Electrical Engineering and Informatics, ITB. He has published more than 161 international conference

papers and journal articles. His research interest includes high-voltage engineering, mainly on the development of diagnosis system of power apparatus based on partial discharge measurement techniques. He received the best paper award from international conferences, in 2005, 2014, 2016, 2018, and 2022.