Analisis Pontencia Transformador.pdf

Engineering Failure Analysis 55 (2015) 182–192

Contents lists available at ScienceDirect

Engineering Failure Analysis journal homepage: www.elsevier.com/locate/engfailanal

Failure analysis of power transformer for effective maintenance planning in electric utilities Raji Murugan a,⇑, Raju Ramasamy b,1 a b

Department of Electrical & Electronics Engineering, College of Engineering Guindy, Anna University, Chennai 600 025, Tamil Nadu, India Department of Industrial Engineering, College of Engineering Guindy, Anna University, Chennai 600 025, Tamil Nadu, India

a r t i c l e

i n f o

Article history: Received 14 March 2015 Received in revised form 29 May 2015 Accepted 1 June 2015 Available online 6 June 2015 Keywords: Power transformers Failure analysis Statistical analysis Root cause analysis Maintenance

a b s t r a c t In this paper, power transformer failures are analyzed and their root causes are systematically investigated in Tamil Nadu Transmission Corporation Limited (TANTRANSCO)/Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) electric utilities, based on 196 failure cases from the year 2009–2013. Failure analysis is conducted in two phases. Initially, voltage level, geographical zone and power transformer components based failure analysis are performed through statistical analysis. Secondly, the most significant factors that cause power transformer failures are identified by using root cause analysis (RCA). Finally, current maintenance practice is reviewed and an effective maintenance planning has been proposed for implementation in order to prevent these failures and to maintain the power transformers in good operating condition during their life cycle. This study provides a practical guidance to help maintenance personnel for the best utilization of the power transformer in electric utilities. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction Power transformers are the most expensive and strategic components of electric power system [1]. It plays an important role by interconnecting in every stage of power transmission and distribution system [2]. Practically, the power transformer is one of the high risk equipment in electric power system due to its harsh operating condition at various circumstances such as high temperature, emergency overloading and continuous operation in outdoor environment. These conditions lead to unexpected failure of power transformer. The failure of power transformer directly affects the reliability of the whole network [3]. Failures in power transformers may cause disturbances to operating systems, resulting in unprepared outages and power delivery problems. The power transformer failures in electric utilities can be very expensive and may take long time for renewal or replacement of damaged components [4]. The failure not only impacts the cost-effective factors but also causes image of the electric utilities lowered due to customer’s dissatisfaction [2]. It has been reported in several literature that there are large number of power transformer failures in various electric utilities across the world. CIGRÉ working group [5] has conducted a survey on failures in large power transformers and found that about 41% of failures were due to on-load tap changers (OLTC) and about 19% were due to the windings, 13% were due to leakage, bushing with 12%, 12% were others and 3 percent were core failures. Minhas et al. [6] conducted power transformers failure analysis in Eskom network at South Africa during the period 1985–1995. Six failure modes were identified which ⇑ Corresponding author. Mobile: +91 9176763230. 1

E-mail addresses: [email protected] (R. Murugan), [email protected] (R. Ramasamy). Mobile: +91 9444904300.

http://dx.doi.org/10.1016/j.engfailanal.2015.06.002 1350-6307/Ó 2015 Elsevier Ltd. All rights reserved.

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includes lightning, core, tap-changer failures, ageing, and short circuit. In similar outage analysis study, Jagers et al. [7] found that Bushings, tap changers and windings represent about 79% of outage causes and the contribution of core related failures was only 2%. Jongen et al. [8] found that tap changer and bushing failure were the dominant causes of outage for transformers having a rated voltage ranging from 110 to 150 kV. Abdelfatah et al. [9] conducted an outage data analysis for 220 kV power transformers in Egypt Electricity Company, over the period 2002–2009 and found that outage causes were related to Transformer related outage category – buchholz and pressure relief, protection system fails, breakdown and damage, fire fighting systems, hot spots, oil leakage, flash over; Power System related outage category – outage of incomers, bus bar protection failures; Human factors related – operational and maintenance mistakes, etc. Thanapong suwanasri et al. [10] studied the failure statistics of transformers in Thailand at a rated voltage of 230/115/22 kV and the failure analysis showed that unknown failures was the highest with 41.3% followed by 31.7% of bushing, 17.5% of tap changer, 7.9% of leakage, and 1.6% of winding. McElroy [11] reported four single-phase EHV autotransformer failures due to transformer winding resonance in an American utility. Previous studies reported only transformer component related failures through statistical analysis but associated root causes were not explored. This paper not only identifies the failure mode, the root causes of the failures are also investigated. This study is carried out based on 196 failure cases collected from the year 2009 to 2013 in Tamil Nadu Transmission Corporation Limited (TANTRANSCO)/Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) electric utility context in Tamil Nadu. The major problem in TANTRANSCO/TANGEDCO is the frequent failure of power transformers, resulting in fire, oil spillage, electric system outage and complete damage of equipment thereby increasing the unforeseen repair or replacement costs. This also leads to loss of revenue to electric utilities. The main objective of this study is to analyze the failures of power transformer and, to minimize those failures by appropriate maintenance planning. Two methods are employed in this study for failures analysis. First, statistical analysis is used in determining the various indices of power transformer failures. Second, root cause analysis (RCA) is used in identifying the root causes of failures in power transformers. Finally, condition based maintenance (CBM) is proposed in order to predict the current condition of the power transformer for preventing failures. The structure of the paper is organized as follows. Section 2 discusses the methodology used in this study, Section 3 describes the data collection, Section 4 discusses on the statistical analysis performed to identify power transformer failures, Section 5 discusses on the root cause analysis performed, Section 6 reviews the current maintenance practice in electric utilities, Section 7 describes the effective maintenance planning for preventing power transformer failures, Section 8 provides the results and discussion and Section 9 concludes the paper.

2. Methodology The study is conducted based on the failure data gathered from the TANTRANSCO & TANGEDCO electric utilities. The methodology for the power transformers failure analysis is shown in Fig. 1. The power transformer failure analysis is conducted in two phases. In the first phase, statistical failure analysis of power transformers is conducted. The failure data collected has been split up into three different groups as voltage, geographical zone and power transformer component based failures. The purpose of this grouping is to identify the highest failure impacts that occurred in each of the population. In the second phase, power transformer component based failures are further analyzed in order to identify the root causes for failures. Root cause analysis (RCA) is an essential step to identify the causes for failures of power transformer. RCA is facilitated by the use of various standard techniques such as check sheets, pareto analysis, brainstorming, reliability and maintainability circles, benchmarking, fail safe methods and cause and effect diagrams. These techniques are often used in continuous and they are effective tools in identifying and solving maintenance and reliability problems [12]. A distinctive advantage of cause and effect diagrams is a graphical tool that is used to identify all potential failure causes for each failure and effects in a systematic way [13]. The cause and effect diagram, also known as the fishbone diagram because of its fish like shape and Ishikawa diagram in honor of its developer [14]. In this study, cause and effect diagram is constructed to identify the factors influencing failures in power transformer components. Finally, Time Based Maintenance (TBM), the current practice in TANTRANSCO & TANGEDCO is reviewed and Condition Based Maintenance (CBM) is developed for effective maintenance implementation in electric utilities. The motive, advantages, CBM basis condition assessment techniques, interpretation criteria and CBM decision model for effective maintenance planning are described. This would enhance the power transformer operation for the best utilization in electric utilities.

3. Data collection The state owned TANGEDCO is responsible for generation, purchase of bulk power and distribution of electric power for low voltage consumers whereas the state owned TANTRANSCO is responsible for transmission and selling bulk power to the distribution companies, high voltage (HV) and extra high voltage (EHV) consumers. The TANTRANSCO/TANGEDCO consists of 842 numbers of substations in various voltage levels. Among these substations, large numbers of electrical equipments are failing every year due to various factors including poor maintenance, overloading of electric network and aging reasons. The power transformer is one among the major frequent failure component.

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Transformer failure data from the year 2009 to 2013

Voltage based failures (400KV,230KV,110KV,66KV and 33KV)

Geographical zone based failures (Chennai north, Chennai south,Trichy,Covai, Madurai,Vellore, Tirunelveli,Erode,Vilupuram)

Power transformer component based failures

Failure data analysis (Statistical analysis)

Identification of causes for failures (Root cause analysis)

Review current maintenance practice

Effective maintenance planning

Fig. 1. Methodology for the power transformers failure analysis.

The failure data of transformers are collected from TANTRANSCO & TANGEDCO for five years from 2009 to 2013, for 196 transformers in voltage populations ranging from 33 kV to 400 kV and MVA rating from 5 MVA to 315 MVA. The collected data include the transformer location, date and time, transformer failure duration, the disruptions in terms of power supply interruptions, protection accomplishment and transformer repair time etc. From the total failures of 196 units, the age of the population is in range of 2–30 years and the average age is 15 years. The number of failures of power transformers per voltage subpopulation during 2009–2013 and their total numbers are tabulated in Table 1. Table 2 shows the number of power transformer failures in various geographical zones during 2009–2013. The power transformer components based failures during 2009–2013 are shown in Table 3. Based on the failure data, various indices of power transformer failures are analyzed. The failures of power transformers fall under different failure categories. These failure categories are related to transformer component, protection, electric network, working environment conditions, human error, design/manufacturing/installation failures and unclassified failures (others) [9]. But, the data availed from TANTRANSCO/TANGEDCO electric utilities, deals with the voltage, geographical zone and power transformer component related failures. 4. Statistical analysis for power transformer failures Over 196 power transformer failure cases are collected for analysis. The voltage subpopulation, geographical zone and power transformer component based analysis of failures are presented below. 4.1. Voltages based failure analysis The distribution of failures for various voltage categories for five years from 2009 to 2013 is shown in Table 1. The voltage population of power transformers consists of 11 kV, 33 kV, 66 kV, 110 kV, 230 kV and 400 kV transformers. The rated power is within the range of 5 MVA up to 315 MVA. There were 196 failures in five years. In Fig. 2 the percentage of failures versus various voltage based failures are given in this study period. It can be found that there were 36% of failures in 33/11 kV, 22%

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R. Murugan, R. Ramasamy / Engineering Failure Analysis 55 (2015) 182–192 Table 1 Number of power transformer failure per voltage population during 2009–2013. Years/subpopulation (kV)

400– 230 kV

230– 110 kV

110– 66 kV

110– 33 kV

2009 2010 2011 2012 2013

0 0 0 0 0

0 1 1 0 2

0 1 0 0 1

0 9 10 10 13

Total

0

4

2

42

110– 22 kV

110– 11 kV

66– 11 kV

33– 11 kV

Total no. of failures

3 9 8 7 8

7 6 11 8 9

0 0 0 0 1

11 15 14 16 15

21 41 44 41 49

35

41

1

71

196

Table 2 Number of power transformer failure in various geographical zones during 2009–2013. Zone Chennai north Chennai south Villupuram Vellore Trichy Madurai Tirunelveli Covai Erode Total

2009

2010

3 1 3 2 6 1 2

2011

2012

2013

Total no. of failures

3

1 2 3 10 8 3 3 6 5

6 3 5 5 8 4 6 3 4

3 3 1 5 12 5 5 4 3

8 9 3 9 5 3 7 3 2

21 18 15 31 39 16 23 16 17

21

41

44

41

49

196

Table 3 Power transformer component based failures during 2009–2013. Category wise failures Winding Core Bushing OLTC Tank Coolant Insulation Others Total

2009

2010

2011

11 7

7 4 9 5 2 3 10 1

2 20 1

21

41

44

2 1

5 1 9 6

2012

2013

13 4

19 1

3 6 6 5 3 4 20 2

28 15 26 20 6 9 80 12

41

49

196

3 1

Total no. of failures

Percentage of failures

40% 35% 30% 25% 20% 15% 10% 5% 0% 230/110 KV 110/66 KV 110/33 KV 110/22 KV 110/11 KV 66/11 KV

33/11 KV

Failures of power transformer in various voltage populaons Fig. 2. Failure statistics of power transformers voltage based failures.

in 110/33 kV and 21% in 110/11 kV voltage ratios. The voltage ratios 33/11 kV, 110/33 kV and 110/11 kV were the major failures encountered across nine zones in TANTRASCO/TANGEDCO electric utilities. The results of the analysis for the voltage based population are most useful, when deciding about spare parts or spare transformers and repair or replacement decision making for the electric network.

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4.2. Geographical zone based failure analysis The distribution of power transformer failures based on geographical zone is shown in Table 2. Fig. 3 represents the percentage failures versus the geographical zone based failures. It can be noted that 20% of failures occurred in Trichy zone, 16% of failures occurred in Vellore zone, 12% in Tirunelveli zone and 11% in Chennai north zone. The causes of failure for transformers vary from one geographical zone to others. It is mainly due to various factors for failures across these zones which includes working environment conditions, network loading conditions during summer, aging factor, poor maintenance of power transformer and lack of training of maintenance personnel, etc. Therefore, the results of analysis for the geographical zone wise are most useful to find the critical zones according to their percentages of failures. This will help to support spare part management and effective maintenance activity planning in electric utilities. 4.3. Power transformer component based failure analysis The power transformer component related failure is shown in Table 3. From Fig. 4 it can be found that insulation failures are the predominant causes of failures, which contributes to about 41% from the total failures. The subsequent major contributors are winding failures with 14% and bushings with 13%. OLTC contributes to 10% and core contributes to 8% of failures. The components with high percentage of failures are considered as critical and should be carefully focused. Therefore, these failures are further analyzed in order to identify its root cause in the following section. 5. Root causes of failure for power transformer The result of failure analysis reveals that predominant failure occurs on various components of power transformer. Therefore, the transformer components related failures are further explored in order to identify its root causes. The insulation is the most leading failure followed by winding and bushing failures. The remaining failures are OLTC, coolant and tank, etc. To illustrate cause and effects, a cause and effect diagram is developed and is shown in Fig. 5. The Cause and effect diagram is used to describe the complete set of power transformer potential causes for failures. The diagram is structured with the topic of interest of ‘‘power transformer failure’’ attached at the right-hand end. It has 8 main causes including insulation, winding, bushing, OLTC, core, coolant, tank, others and 27 primary causes. The representation of failures on the diagram is made in the order of importance. The most key causes are placed at the beginning (Insulation and winding). Placements of the main causes are shown in the upper zone and left part of the axis whereas the less important causes are shown in lower zone and right part of the axis. The identified potential failure modes and their causes are (i-a) Solid insulation – mechanical damage, Over load causing over heating insulation and fault in insulation material (i-b) Liquid insulation-oxidization of oil, thermal decomposition of oil and contamination from moisture (ii) Winding – electrical (lightning surge, switching surge, connection fault and over voltage), mechanical (shipping damage, vibration, electromechanical forces which includes the hoop buckling of the innermost winding, conductor tipping, conductor telescoping, spiral tightening, failure of clamping system and displacement of connection leads), thermal (overloading of the transformer, failure of the cooling system, low oil quality, operation of the transformer under excessive ambient temperature conditions and operation of the transformer in an overexcited condition) and Insulation failure (local over heating of the winding insulating material, Cooling system fail and insulation containment fail). (iii) Bushing-fault in material, damage of the porcelain and insulation failure. (iv) Tap changer – diverter switch or tap selector failure, control device and drive mechanism fails. (v) Core – electrical (over voltage), mechanical (displacement of the core steel during the construction or DC-magnetism) and insulation failure (poor insulation of the tightening screws of the core, an obstructed oil-cooling duct and ungrounded core system that cause excessive heating of the core).(vi) Others – operational errors, lack of maintenance, lack of skills for operators, aging of transformers. (vii) Cooling System – Pump, fan, radiator failure and temperature gauge and control circuit and (viii) tank – leakage and rupture due to internal overpressure. From this, the causes of power transformer component based failures are identified. Therefore, it is very important for electric utilities to prevent a transformer from these failures by developing effective maintenance, which is discussed in the following section. 6. Review of the current maintenance practice in electric utilities The maintenance of power transformer plays a vital role in order to achieve maximum availability during their life cycles in electric utilities. There are various maintenance schemes such as corrective, preventive, time based maintenance, but TANTRANSCO/TANGEDCO is currently practicing time based maintenance (TBM). The authors reviewed the current maintenance practice to understand the practicality and their issues. Fig. 6 shows the flowchart of TBM practice in TANTRANSCO/TANGEDCO power sector. These maintenance works are performed at fixed time intervals regardless of equipment condition. The time intervals are chosen based on maintenance schedule for annual, monthly and weekly basis using equipment manufacturers’ specification or based on the regulations and instructions framed by the electric utilities. Once the need for maintenance is decided, it is carried out based on a weekly work schedule. Prior to performing weekly

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Percentage of failures

25% 20% 15% 10% 5% 0% CHN N

CHN S

VPM

VLR

TRY

MDU

TIN

CBE

ERD

Failure of power transformer in zone wise Fig. 3. Failure statistics of power transformer geographical zone based failures.

Winding 14%

Others 6%

Core 8% Insulaon 41% Bushing 13% OLTC Tank 10% 3%

Coolant 5%

Fig. 4. Failure statistics of power transformer component based failures.

maintenance schedule, maintenance activities, availability of labor and spare parts are prepared. Then, power transformer to be serviced must be switched off (outage) to perform maintenance works. If outage is unfeasible, works are rescheduled for some other time. Time based maintenance activities in power transformer include visual inspection, cleaning bushings, oil level checking, repair or replacement of failed components, oil replacement, tightening of tank gasket bolts and testing. Upon completion of maintenance works, the equipment will be put into operation and their test reports will be gathered and filed. Then, the

INSULATION INSULATION

WINDING WINDIN G

BUSHING BUSHING

TAP TAPCHANGER CHANGER

Solid Insulation 1.Mechanical damage 2.Fault in material 3.Overheating 4.Aging

1.Electrical 2.Mechanical 3.Thermal 4.Insulation

1.Fault in material 2.Damage of porcelain 3.Insulation failure

1.Diverter switch 2.Control device 3.Drive mechanism

Liquid Insulation 1.Oxidization of oil 2.Thermal decomposition 3.Contamination POWER POWER TRANSFORMER TRAN SFORMER FAILURES FAILURE S

1.Leakage 2.Internal rupture

1.Electrical 2.Mechanical 3.Insulation

1.Pump 2.Fan 3.Raditor failure 1.Operational errors 2.Lack of maintenance

TANK TANK

COOLANT COOLANT

OTHERS OTHERS

CORE CORE

Fig. 5. Cause and effect diagram for power transformer failures.

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TANTRANSCO/TANGEDCO time based maintenance regulation and instructions

Yearly maintenance schedule

Monthly maintenance schedule

No

Is maintenance needed?

Yes List maintenance work activities

Prepare spare parts list

Determine labor availability

Determine spare parts availability

Weekly maintenance schedule (Including outage request)

Test reports/Documentation

Perform maintenance work as per the schedule

Fig. 6. Flowchart of a time based maintenance in TANTRANSCO/TANGEDCO.

performed maintenance works are registered in database as per the maintenance schedule laid down in the utility maintenance regulations. Experience with TBM as scheduled maintenance has many drawbacks. The usage of TBM practice is minimized recently due to high maintenance costs, unnecessary outage of network system, labor intensive and time consuming. Therefore, there is a need for effective maintenance in TANTRANSCO/TANGEDCO electric utility.

7. Effective maintenance planning for preventing power transformer failures The Statistical, root cause analysis of failures and issues in current maintenance practice of power transformers constitute an important basis for establishing the condition based maintenance (CBM) as effective maintenance in TANTRANSCO/TANGEDCO electric utility. The aim of effective maintenance is to keep the power transformers in good working condition in its life cycle thereby extending the lifetime of equipment and reducing the failure probability in electric utility. The essential need of the maintenance activity is to deploy at acceptable costs with no adverse environmental impact [15]. CBM is the most widely employed strategy in various industries [16]. CBM is performed according to the actual condition of the equipment. The most important task of electric utility is to reduce failure occurrence and cost of maintenance of power transformers in order to provide high reliability and availability. The proposed CBM approach for TANTRANSCO/TANGEDCO is shown in Fig. 7. The CBM concept comprises of different elements, in which online condition monitoring and offline diagnostic test constitute the core of the CBM strategy. The first step is monitoring which focuses on identifying symptoms of possible failure modes or abnormal condition in power transformer components. The techniques should be cost efficient and possible to develop models for anomaly detection of any potential problem at an early stage using sensors and data acquisition system. If an anomaly is detected, the own monitoring system

1

2

189

Online monitoring Data acquisition system, Anomaly detection, Graphical user interface

Sensors

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Offline diagnostic test Diagnostic test

Evaluation (International standards)

Maintenance decision

n Fig. 7. CBM approach for power transformer.

will be able to diagnose, but normally, further offline diagnostic tests are required. The second step is the offline condition diagnostic where an anomalous situation is explored to determine the type of faults and the severity of the problem. The condition diagnostic test needs to be performed only on certain units are deemed abnormal condition. Finally, the maintenance activities can be scheduled according to the condition of the assets. To achieve this, condition based maintenance decision model for effective maintenance of power transformer in TANTRANSCO/TANGEDCO power sector has been developed which is shown in Fig. 8. The steps involved in the CBM based decision making are: 7.1. Step 1. Assessment of current condition of power transformer CBM involves continuous or intermittent collection of online critical data from power transformers. But normally, further offline measurement test has to be performed followed by online critical indication. The measurement data has to be interpreted based on the operating condition of the power transformer in order to determine current condition or failure mode if any. The current condition of the power transformer is predicted through the following measurements:  Online direct measurements (continuous condition monitoring the power transformer variables and component condition) Online measurement is performed regularly and preferably continuously during the service condition of the power transformer. On-line monitoring system serves to detect in the form of an early warning system due to chemical/dielectric/thermal or mechanical impact in power transformer. The list of online measurements includes hot spots, top oil and bottom oil monitoring, winding temperature monitoring, localized faults/defects, gases monitoring, on-load tap changer mechanism monitoring, vibration monitoring and cooling system monitoring, etc. The use of sensor, data acquisition and measurement techniques for on-line applications together with a mechanism for generation of alarms when an anomaly is predicted aids maintenance decision.  Offline condition diagnostic measurements (standard diagnostic tests and measurements) Offline diagnostic techniques should be applied in order to determine the current condition of power transformers. There are several standard diagnostics techniques used to assess the current condition of power transformer. For effective utilization, these techniques are prioritized as (1) visual inspection – inspection of oil conservator, oil level, tank external condition, gaskets and oil sampling valves, assessment of radiators, coolers, gaskets, fans and pumps, oil temperature, winding temperature, oil leakage checks, bushings external condition, bushing oil levels, pressure relief devices, buchholz relays, displays alarm and trip signals indicators and inspection of dehydrating breather; (2) chemical test – dissolved gas analysis (DGA) and physical chemical and electrical analysis of oil quality (PCEA); (3) dielectric test – insulation resistance/polarization index, power factor, capacitance test and (4) electrical test – turns ratio, winding resistance, leakage reactance, excitation current, magnetic balance test. The priorities of condition diagnostic techniques can distinguish which diagnostic parameter affects the transformer’s current condition. These tests must be applied in the order of priorities as recommended by the authors to identify and estimate the actual power transformer condition and its performances. The high priority chemical based DGA and oil quality tests are performed initially. The dielectric tests are performed when there are faults detected from oil analysis. Finally, electrical tests are performed when there are faults detected from dielectric analysis. In addition to the standard diagnostic tests, there are some advanced tests including Polarization–Depolarization Current (PDC), Return voltage measurement (RVM), Frequency domain spectroscopy (FDS), Frequency response analysis (FRA), Frequency response stray loss (FRSL) Frequency response dissipation factor (FRDF), Partial discharges (PD), thermal imaging, vibration analysis of transformer components, and degree of polymerization. These monitoring tests may detect problems such as moisture in insulation paper and ageing of paper, conductivity, winding deformation, mechanical faults, local partial discharge, hot spot at connectors, as well as insulation degradation.

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Predicting current condition by online monitoring and offline diagnosis testing

Evaluation process Does the current condition reach the failure limit or not?

No

Yes

Maintenance before term

1,4

Maintenance decision

3

Maintenance after term

2

Replacement Fig. 8. CBM decision model for effective maintenance of power transformer.

7.2. Step 2. Evaluation process Evaluation process activities are helpful to identify the existing faults or weaknesses and also give some indication of expected service reliability and remaining life of power transformers. These are performed based on online monitoring and offline diagnostic measurement results which provide guidance on the current condition of the transformer. Online condition monitoring evaluation processes consists of limit checking and trend analysis. Limit checking consists of comparing actual measurements with configured limit values. A notification (alarm) is generated when the limit values exceed. Trend analysis consists of discerning whether the level of a measured variable has increased or decreased over time, and if it has, how quickly or slowly the increase or decrease has occurred. Offline measurement results are evaluated from the recommended standards i.e. International Electro technical Commission (IEC) or Institute of Electrical and Electronics Engineers (IEEE) or those provided by institutions i.e. International Council on Large Electric Systems (CIGRÉ), Electric Power Research Institute (EPRI) or guidelines of diagnostic instrument manufacturer in order to predefine the failure limit. In general, these interpretation criteria are applicable to all kinds of transformers. On the other hand, the criteria are applicable when an actual test is compared to a reference test such as factory test or previous test. In case the transformer is not in a satisfactory state, diagnostic measurement results are compared with allowable condition limit (inline to the standards) to determine the current condition of the power transformer. If the current condition exceeds allowable limit, proceed for maintenance. 7.3. Step 3. Maintenance decision process The evaluation process outcome is important for maintenance decisions in electric utilities. The power transformer maintenance decision is determined based on inspection, analysis of measurement results, failure analysis and condition of the equipment. This can be in four conditions. These four conditions are considered to be independent. Further it has been discussed as follows:  If power transformer is not in an acceptable operational performance condition and if failures have occurred, maintenance can be performed ahead of schedule if the components are repairable type (condition 1).  If power transformer is not in an acceptable operational performance condition and if failures have occurred, replacement can be performed ahead of schedule if the components are not repairable type (condition 2).  If power transformer is in a good operating state, maintenance can be deferred for a specified time, unless it reaches the failure limit or is about to exceed the failure limit in the mean time (condition 3).  If the operational performance of power transformer is marginally acceptable but the timing is remote enough for the condition to become an unacceptable operational performance, and if failures have occurred, maintenance can be performed ahead of schedule (condition 4).

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The power transformer after maintenance or replacement, proceed to Step 1 as a routine process. The maintenance decisions in electric utilities enable operation and maintenance personnel in priority of work, initiation of work order and what repair (maintenance) or replacement is to be performed. For example, if the equipment’s current condition level reaches or exceeds the failure limit, the power transformer will be prepared for maintenance or replacement. Otherwise, the power transformer is presumed to be in good condition and can still be used. 8. Result and discussions Failure analysis of power transformer is very important in electric utilities. In this study, the failure analysis of power transformer in TANTRANSCO/TANGEDCO electric utility was investigated and the following results were obtained. (1) Transformer voltage level failures revealed the voltage levels having highest failures and their associated causes across nine zones of electric utilities. Voltage level 110/11 kV, 110/33 kV and 33/11 kV encountered the major failures due to network overloading, cyclic loading and network transient faults. (2) Geographical zone wise power transformer failures indicated the critical zone according to their highest percentage of failures. The main reasons for failures were (i) most of the transformers were located in adverse working environment conditions and no special attention was given to the operating conditions, (ii) maintenance personnel shortage in their respective zones, (iii) ageing factor, (iv) deterioration of insulating oil due to varying load fluctuations. (3) Power transformer component based failures reveal that insulation, winding, bushing, on-load tap changer have the highest failures during the study period. The various root causes for failures against each component were identified for in-depth understanding of the causes for failures. (4) These failure results can be utilized to support maintenance activity in electric utilities. Therefore, condition based maintenance has been proposed for implementation. But there are some issues in implementing CBM approach in power transformer as follows: (i) Technological factors associated with CBM. Behind the CBM strategy, information communication and technology (ICT) challenges are to be solved within power transformer applications. On one side, it refers to the advances in sensors and on the other side, to the advances in the field of communications. Other technological advances are still in their infancy like information data quality, frequency, noise and level of details of data availability. It means that there are some limitations in ensuring the accuracy of diagnostics and prognostics. (ii) Economical factors associated with CBM. The initial cost of CBM can be high. CBM requires sophisticated instrumentation and usage of various online monitoring devices. Also, to implement the CBM, in addition to investment in software cum hardware, training of personnel for operation and maintenance makes it expensive. 9. Conclusion The power transformer must be reliable for continuing operation due to its key role in the functioning of the electric power system network. Through the collection of failure data of power transformers, voltage level, geographical zone and component based operational failures were presented over the study period using statistical analysis. Subsequently, primary causes were identified in power transformer component related failure using root cause analysis. The outcome of failure analysis highlights the various causes of the failures providing crucial input data to decide on effective maintenance in electric utilities. Until recently, TBM practices in TANTRANSCO/TANGEDCO electric utilities experienced many drawbacks. Therefore, CBM has been proposed with a view to reduce the failures based on the current condition of equipment instead of scheduled time based maintenance. For effective maintenance implementation, CBM decision model was developed. The CBM decision model predicts the current condition of the transformer by online monitoring parameters followed by offline diagnostic measurement, evaluation criteria and maintenance decision. With the proposed condition based maintenance practices, power transformers can be effectively maintained according to its actual condition by reducing failures tremendously. This will enhance the operating conditions, extend the lifetime of power transformer and reduce maintenance costs. Finally, the proposed method can also be further applied to other kinds of electrical equipments in the electric utility. Acknowledgments The authors acknowledge Tamil Nadu Generation and Distribution Corporation (TANGEDCO) & Tamil Nadu Transmission Corporation (TANTRANSCO) for their valuable discussions, data, and support. This work has been supported through Anna Centenary Research Fellowship, Anna University, Chennai. The Grant number is M.H.No:14/CR/ACRF/2014. References [1] Metwally IA. Failures monitoring, and new trends of power transformers. IEEE Potentials 2011:36–43. [2] Wardani NUA, Purnomoadi AP, Septiani HI, Arifianto I, Cahyono B. Condition assessment of 500/150 kV power transformer based on condition based maintenance. Int Conf Electr Eng Inf 2011:14–7. [3] Abdelfatah M, EL Shimy M, Ismail HM. Outage data analysis of utility power transformers based on outage reports during 2002–2009. Int J Electr Power Energy Syst 2013;47:41–51.

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[4] Mijailovic V. Probabilistic model for planning keeping of power transformer spare components with general repair time distribution. Electr Power Syst 2013;97:109–15. [5] CIGRE Working Group 12.05. An international survey on failures in large power transformers in service. Electra 1983;88:21–48. [6] Minhas MSA, Reynders JP, De Klerk PJ. Failure in power system transformers and appropriate monitoring techniques. Presented at the 11th International Symposium on High Voltage Engineering London; 1999. [7] Jagers JN, Khosa J, De Klerk PJ, Gaunt CT. Transformer reliability and condition assessment in a South African Utility. Presented in XV International Symposium on High Voltage Engineering Slovenia; 2007. [8] Jongen R, Peter Morshuis, Gulski E, Smit J. Statistical analysis of power transformer component life time. 8th International Power Eng Conf Singapore; 2007. p. 1273–7. [9] Abdelfatah M, El-Shimy M, Ismail HM. Reliability analysis of 220 kV power transformers in Egypt. Ain Shams Eng J 2011;2:183–94. [10] Suwanasri Thanapong, Chaidee Ekkachai, Adsoongnoen Cattareeya. Failure statistics and power transformer condition evaluation by dissolved gas analysis technique. International Conference on Condition Monitoring and Diagnosis China; 2008. [11] McElroy AJ. On the significance of recent EHV transformer failures involving winding resonance. IEEE Trans Power Ap Syst 1975;94:1301–6. [12] Madu CN. Competing through maintenance strategies. Int J Qual Reliab Manage 2000;17:937–48. [13] Mariajayaprakash A, Senthilvelan T. Failure detection and optimization of sugar mill boiler using FMEA and Taguchi method. Eng Fail Anal 2013;30:17–26. [14] Jayswal A, Li X, Zanwar A, Lou HH, Huang Y. A sustainability root cause analysis methodology and its application. Comput Chem Eng 2011;35:2786–98. [15] Plavsic T. The contribution of failure analyses to transmission network maintenance preferentials. Eng Fail Anal 2013;35:262–71. [16] Abu-elanien AEB, Salama MMA. Asset management techniques for transformers. Int J Electr Power Energy Syst 2010;80:456–64.