ArticlePDF Available

Transformer reliability survey: Interim report

Authors:
mers. However, this survey was based on transformer
failures occurring in the period 1968 to 1978.
Working group A2.37 Transformer Reliability was
formed in 2008 with the following objectives:
•Reviewing all existing survey and study different
practices (in terms of data collection, compila-
tion, etc.)
•Conducting a new international survey on trans-
former failures
•Compiling and analysing the collected data, and
interpreting the results (calculation of failure
rates, classification into failure location, failure
causes and failure modes)
•Preparing a brochure documenting the above-
mentioned.
This interim report discusses the progress of the
working group to date in terms of data collection,
and will present results of the analysis in terms
of failure rates and the classification into failure
location. Because data collection is still in progress,
this report will refrain from giving a detailed inter-
pretation of the results.
Review of Existing Surveys
The working group collected publicly available
surveys from Canada, Germany and Japan [3, 4].
The main objective of these surveys is the syste-
matic collection of data on the availability and
disturbances of the electrical power supply, with
emphasis on the frequency, duration and extent
of the interruptions. Detailed statistics about the
failure location in the respective equipment, failure
cause or mode and repair activities are normally not
Introduction
In 1983, Cigré Working Group 12.05 published
a report summarizing the results of the analysis of
transformers that failed in the period 1968 to 1978 [1].
Thirteen countries from 3 different continents took
part in this survey. The authors reported of difficul-
ties to compile and analyse the data of the survey due
to incomplete or incompatible responses. Ten years
later, Working Group 12.14 attempted to upgrade this
survey but it was unsuccessful due to similar reasons.
Study Committee A2 also started an Advisory Group
on Reliability and their findings were presented at the
Cigré 2006 session in [2].
Some countries have published reliability surveys
locally with some being published annually. However,
this knowledge is not shared amongst the interna-
tional transformer community, where most benefit
can be drawn.
To date, the only international survey on large
power transformer failures was published in 1983. The
failed units were classified according to voltage level,
age and application, and for each class, corresponding
failure rates were calculated as well as classification
into failure component, presumed cause and failure
origin.
The survey concluded that the average failure rate
of transformers may be regarded as 2 % across all
voltage categories. Since then, this statistic has become
an international benchmark in the transformer
industry for the failure rate performance of transfor-
Members
Stefan Tenbohlen, Convenor (DE), Janine Jagers, Secretary (ZA),
Gilson Baston (BR), Brendan Diggin (IE), Michael Krüger (AT),
Piotr Manski (POL), Bhavin Desai (US), Johannes Gebauer (DE),
John Lapworth (UK), Anne McIntosh (UK), Antun Mikulecky (HR),
Pascal Müller (CH), Claude Rajotte (CA), Takehisa Sakia (JP),
Shirasaka Yukiyasu (JP)
Transformer Reliability Survey:
Interim Report
WG
A2.37
REPORT
46 No. 261 - April 2012 ELECTRA
general information about the population of the
operating transformers for the indicated failure
period. The population information requested
included the transformer application, type, number
of phases, voltage, rated power, typical loading, and
manufacturing period.
The second section captured the transformer
failure data, grouped data into 4 categories as
follows:
• Identification of the unit: application, type,
construction type, year of manufacture.
• Featuresoftheunit: rated power, nominal voltage,
number of phases, cooling system, type of oil, tap
changer, tap changer arrangement, oil preserva-
tion system, over voltage protection.
• Detailofoccurrence: year of failure, service years
to failure, loading immediately prior to failure.
• Consequences of failure: external effects, failure
location, service years of failed bushings (if
location is bushings), failure mode, failure cause,
action taken, and detection mode. It is important
to note that:
- Failure location referred to the primary location
in the transformer where the failure was
initiated.
- Failure cause referred to cause of failure in the
location where the failure was initiated.
- Failure mode referred to a description of the
nature of the failure, in the location where the
failure was initiated.
Collected data
Each participating utility was required to
complete the questionnaire described in section 3.1,
and all the responses were compiled into a database.
In order to achieve a data security and anonymity,
the failure data from each source was labelled by
a code based on the geographical location and a
sequence number. Information about the trans-
former manufacturer was not collected.
To date, the working group has collected 685
failures which occurred in the period 1996 to 2010,
with a total population of 156,186 unit-years,
contributed by 48 utilities from 16 countries. The
year of manufacture of the units span from the
1950’s up to 2009. The data analysis was performed
for all failures which happened after 2000.
Data collection is still in progress and will
continue until May 2012.
Calculation of failure rate
Failure rate was calculated according to the defini-
tion in Bossi [1983], which was expressed as: 
included. The benefit of these statistics with respect
to asset management is therefore limited. Additio-
nally, the failure surveys of utilities, manufacturers
and consulting companies are being collected and
analysed by the working group. However, diffe-
rent definitions and information content constrain
forming a coherent database from these individual
sources.
Initial working group discussions concentrated
on analysing the readily available statistics, but it
was agreed that the scope needed to be broadened to
allow comparison with the failure statistic of 1983
survey. A questionnaire was therefore developed
to collect utility failure statistics in a standardised
way. Besides information about the population
under investigation, failure data is being collected
for various groups of transformers in terms of
the failure locations, failure causes, failure modes,
actions, external effects and others parameters.
Data collection
and preparation for analysis
Definition of failure
The definition of failure was limited to major
failures. Based on the experience of previous
working groups on this subject, it was decided to
limit the data requested from the sources by concen-
trating only on major failures of power transfor-
mers and shunt reactors of operational voltages
higher than 60 kV only.
According to the working group, a major failure
was defined as any situation which required the
transformer to be removed from service for a period
longer than 7 days for investigation, remedial work
or replacement. Where repairs were required, this
should have involved major remedial work, usually
requiring the transformer to be removed from
its installation site and returned to the factory. A
major failure would require at least the opening
of the tank, including the tap changer tank, or an
exchange of the bushings. A reliable indication
that the condition of the transformer prevents safe
operation is considered a major failure, if remedial
work (longer than 7 days) was required for restoring
it to the initial service capability.
Reliability questionnaire
A questionnaire consisting of two major sections
were developed to collect data, in accordance with
the definition of major failure in section 3.1. [5]
The first section of the questionnaire requested
REPORT
WG
A2.37
No. 261 - April 2012 ELECTRA 47
section 3.3. The data were grouped into substation,
and generator step-up transformers, and further
categorised into 5 voltage classes.
Failure rates
The calculated failure rates according to the
voltage category for the substation and generator
step-up transformers, as well as the combined
group of transformers, are given in Table 1 to
Table 3. It is important to note that the number
of generator step-up unit failures, and units
in voltages classes above 500 kV, as well as the
(1)
Where:
ni = the number of transformers that failed in the
ith year
Ni = the number of transformers in service during
the ith year
Data analysis
The analysis presented was based on the popula-
tion and failure data collected to date, as described in
Table 1: Failure Rates of Substation Transformer
Table 2: Failure Rates of Generator Step-Up Transformers
Figure 1: Failure locations of Substation Transformers
(>100kV) (based on 364 failures)
Figure 2: Failure Locations in Generator Step-Up
Transformers (>100 kV) (based on 82 failures)
WG
A2.37
REPORT
48 No. 261 - April 2012 ELECTRA
HIGHEST SYSTEM VOLTAGE [kV]
FAILURES &
POPULATION
INFORMATION69 kV < 100
100 kV <
200
200 kV <
300
300 kV <
500 kV 700 All
Failures145
TransformerYears 15077
FAILURE RATE 0.96%
206 136 95 7589
4615242635 29437219 135491
0.45% 0.32%0.32% 3.20%0.43%
-
HIGHEST SYSTEM VOLTAGE [kV]
FAILURES &
POPULATION
INFORMATION 69 kV < 100
100 kV <
200
200 kV <
300
300 kV <
500 kV 700 All
Failures 62759496
Transformer -Years143 2842 4838 12132740 20695
FAILURE RATE 0.00%0.21% 0.56%0.49% 0.54%0.46%
HIGHEST SYSTEM VOLTAGE [kV]FAILURES &
POPULATION
INFORMATION69 kV < 100
100 kV <
200
200 kV <
300
300 kV <
500 kV 700 All
Failures145 212 163 15411685
Transformer-Years 15220 4899447473 41569959 156186
FAILURE RATE 0.95%0.43% 0.34%0.37% 1.15%0.44%
0
failure data can therefore be analysed and inter-
preted for various types of transformers in terms
of failure locations, failure causes, failure modes,
actions, external effects and failure rates in trans-
formers. In contrast to several public available
statistics, the results of this questionnaire deliver
valuable information which can be used for asset
management of a power transformer fleet.
The preliminary results, based on a transformer
population with more than 150.000 unit-years and
685 major failures in 48 utilities, indicate a failure
rate of 0.44%.Winding related failures appear to
be the largest contributor of major failures, and a
significant decrease in tap changer related failures
has been observed in comparison with results of the
1983 survey.
In order to improve the validity of the failure
statistics, the working group invites participation
from utilities to provide failure data, in particular
shunt reactors, generator step-up transformers,
and transformers with operational voltages above
500 kV.
REFERENCES
[1] A. Bossi, et al., “An International Survey on Failures in Large Power
Transformers in Service” – Final report of CIGRE Working Group
12.05, Electra, No.88, pp. 22 – 48,1983.
[2] J. Lapworth: Transformer reliability surveys, A2-114, Cigré
Biennial Conference, Paris 2006
[3] The Canadian Electricity Association. forced outage performance
of transmission equipment , Equipment Reliability Information
System. canada : s.n., 2000-2009.
[4] VDN-Störungs- und Verfügbarkeitsstatistik , Verband der
Netzbetreiber VDN, Berlin, www.vde.com/fnn, Berichtsjahr 2004.
[5] Questionnaire of CIGRE WG A2.37 “Transformer Reliability
Survey”, November 2011,url: http://www.uni-stuttgart.de/ieh/
wga237.html., last accessed: November, 2011
[6] S. Tenbohlen, et al., “Assessment of Power Transformer Reliability”,
Int. Symp. on High Voltage Engineering, Hannover, Germany,
G-026, August 2011
population of these two categories, has been low
to date. The calculated failure rates should thus be
considered with caution.
The working group further invites participa-
tion from utilities and countries for failure data,
in particular the abovementioned two transformer
groups, to improve the statistical significance of the
results. Data may be supplied by completing and
submitting the questionnaire (available via the web
link given as [5]) to the convenor or secretary of the
working group.
Failure location
The contributions of failure locations in substa-
tion transformers and generator step-up transfor-
mers for voltages higher than 100 kV are given in
Figure 1 to Figure 2.
As seen in previous surveys, major failures can
originate from several transformer components.
Windings related failures appear to be the main
contributor of major failures. The contribution of
tap changer related failures decreased significantly
in comparison with the statistics from 1983 given
in [1]. 95% of the failed substation transformers
and 91% of the failed generator step-up units were
equipped with a tap changer.
It is important to note that failure locations in
some cases have an operating voltage dependency.
Regional significance also has an impact [6]. A more
detailed analysis and interpretation of the results
will be provided in the brochure, which will be
published after completion of the working group’s
expected outcomes.
Conclusion
A questionnaire was developed by the CIGRE
working group A2.37 (Transformer Reliability
Survey) by which utility failure statistics could be
collected in a standardised way [5]. Transformer
Table 3: Failure Rates of Combined Group of Transformers
GT
A1.16
491
REPORT
WG
A2.37
No. 261 - April 2012 ELECTRA 49
HIGHEST SYSTEM VOLTAGE [kV]
FAILURES &
POPULATION
INFORMATION69 kV < 100
100 kV <
200
200 kV <
300
300 kV <
500 kV 700 All
Failures145
TransformerYears 15077
FAILURE RATE 0.96%
206 136 95 7589
4615242635 29437219 135491
0.45% 0.32%0.32% 3.20%0.43%
-
HIGHEST SYSTEM VOLTAGE [kV]
FAILURES &
POPULATION
INFORMATION 69 kV < 100
100 kV <
200
200 kV <
300
300 kV <
500 kV 700 All
Failures 62759496
Transformer -Years143 2842 4838 12132740 20695
FAILURE RATE 0.00%0.21% 0.56%0.49% 0.54%0.46%
HIGHEST SYSTEM VOLTAGE [kV]FAILURES &
POPULATION
INFORMATION69 kV < 100
100 kV <
200
200 kV <
300
300 kV <
500 kV 700 All
Failures145 212 163 15411685
Transformer-Years 15220 4899447473 41569959 156186
FAILURE RATE 0.95%0.43% 0.34%0.37% 1.15%0.44%
0
... In 2008, the Conseil International des Grands Réseaux Électriques (CIGRÉ) formed Working Group A2. 37 Transformer Reliability and published the resulting Transformer Reliability Survey material [4], with contributions from 58 concessionaires from 21 countries. A total of 964 failures occurring in transformers were examined, with 799 occurring in transmission substation transformers and 165 occurring in power plant step-up transformers. ...
... Considering that dielectric failure is the main failure mode in transmission substation transformers in Brazil and worldwide [4], articles specifically addressing oil analysis and insulation moisture were also examined, as insulating oil has dielectric and cooling functions in power transformers. Physicochemical and gas chromatography tests are carried out on the equipment's insulating oil to confirm that operating conditions are adequate and to analyze dissolved gases, respectively. ...
... Classification of failure modes occurring in power transformers according to concessionaires[4]. ...
Article
Full-text available
The present study undertakes a scoping review of research on the methodologies and techniques used for the maintenance and condition assessment of power transformers, which are the main asset in the electrical power transmission sector. It addresses articles on asset management, monitoring and diagnostics, oil analysis, and insulation moisture, with these articles originating from twenty-five countries and being published in journals in the last fifteen years, with more than half of them published in the last five years. The aim of this research is to map the literature linked to the topic in a broader and more exploratory manner and to identify any existing gaps in knowledge. Guidelines such as eligibility criteria, sources of evidence, data charting, and result summaries are described. This study finds that data analysis methodologies related to identifying failures and aiding decision-making can add value to power transformer asset management and this scoping review was the basis for the development of an inedited methodology to aid decision-making regarding investments in the maintenance of power transformers.
... circuit electromagnetic impulses gradually decreases because of cumulative effects [3]. According to CIGRE statistics, winding loosening and deformation are common mechanical issues [4]. These issues occur because of the squared relationship between electromagnetic force and current, resulting in varying degrees of axial and radial winding deformations under short-circuit impulses. ...
Article
Full-text available
Power transformer windings are susceptible to deformation after multiple short‐circuit impulses, threatening power grid stability. Currently, there is a lack of experimental data on various characteristic parameters of failures after multiple short‐circuit impulses. To investigate winding deformation and its gradual deterioration, a mock‐up transformer was constructed to study the cumulative effects. Short‐circuit tests were conducted under different current ratios, and the cumulative effect was quantified based on short‐circuit impedance and axial force variations. A correlation was established between different current ratios, impulse number and cumulative winding deformation. The cumulative effects of winding deformation are categorised into four levels: none, minor, significant and severe. Thresholds indicating severe deformation and degraded short‐circuit withstand ability are defined by an absolute impedance change rate exceeding 1.1% and a relative rate exceeding 0.3%. Additionally, an axial force change rate of ± 20% serves as an early warning indicator, providing greater sensitivity to detecting impulse effects on winding stability compared to impedance change rate. Monitoring impedance and axial force changes provides a reliable approach to assessing transformers affected by the cumulative effects of short‐circuit and identifying the risk of winding deformation.
... Given the scenario of aging infrastructure and the technical and economic impracticality of replacing all fully depreciated assets from a regulatory standpoint, actions to mitigate assumed risks must be developed and implemented. Considering that dielectric failures are the main failure mode in transmission substation transformers in Brazil and worldwide [3], data analysis methodologies related to such failures can assist in preventive actions. Therefore, this article proposes a data analysis methodology to assist in directing maintenance investments in power transformers, the main asset in the transmission sector. ...
Article
Full-text available
This article proposes an original contribution to assist in evaluating the condition of power transformers, the main asset of the electrical energy transmission sector. Due to constructive similarity, reactors are also evaluated. Data from the insulating oil moisture of the equipment and the following categorical variables were used: voltage class, installation region (regional), criticality, type, and age of the equipments. The feasibility of applying the methodology stands out, since these categories are technical registration data of transformers and reactors and the water content is an essential characteristic for determining the operational condition of the insulating oil, being one of the measured properties in the physical-chemical tests carried out on the oil. The main contribution presented is the selection of categories with higher weight and categorical variables with higher predictive power to direct maintenance actions. This goal was achieved using the statistical metrics Weight of Evidence (WoE) and Information Value (IV). The methodology was applied to a dataset of nearly 10 thousand samples of oil from 795 power transformers and reactors from the ISA CTEEP park, an electric power utility company in Brazil.
... This is documented in many publicly available studies that present the fact that the downtime of an electrical machine is commonly associated with the presence of an EIS and bearings in general failures. Of course, the majority of main failure modes and further specific failure-related mechanisms and locations depend on power and voltage ratings and on the particular type of machine, as this might include transformers [4][5][6][7], low-voltage through high-voltage motors [8][9][10], and alternators [11,12]. Thus, it is important to study the relevant effects that degrade such a machine or its specific elements or material. ...
Article
Full-text available
The degradation of electrical insulating materials has been a subject of interest for decades as they are commonly applied in many fields of electrical engineering. Suitably modeling such a process is important since the known and well-described degradation process reveals the effect of ambient conditions, and this allows us to possibly estimate a material’s remaining useful life. However, not many studies are dealing with the effect of the hygrothermal degradation of impregnating mono-component epoxy resins in the context of electrical engineering. Therefore, this study deals with this issue and discusses both the dielectric response (based on the measurement of relative permittivity, dissipation factor, and dielectric strength) and the mechanical response (based on measurements of tensile strength and Shore D hardness) to a hygrothermal degradation experiment. In addition, the results of thermal analyses are presented for the evaluation of the pristine specimen manufacturing process and possible post-curing processes. Furthermore, this study presents several methodologies for modeling the degradation process, including a novel methodology in this area based on Bayesian experimental design. As an outcome, mechanical parameters are proven to be specific in terms of the actual condition of the material and the Bayesian enhanced degradation model seems to be superior to the conventional evaluation methods in this particular study.
... It could also be required to install a tap-changer on the LV side of the transformer, to accommodate solar panel deterioration over time [6]. A large percentage (26%) of transformer failures are due to the failure of on-load tap changers [23]. Frequent switching in PV plants, will require increased maintenance on the tap changer. ...
Conference Paper
Within South Africa, the drive for electrical energy from renewable sources has seen the exponential growth (since 2011) of independent power producers (IPPs). The renewable sources used for the majority of these IPPs are solar and wind. Due to conversions required in these plants, from direct current (DC) power to alternating current (AC), harmonics and transients affect the equipment installed. Variation in loading due to fluctuating availability of resources also affects the equipment within these systems. In this paper the focus will be on the effects of grid-connected photo-voltaic (PV) plants on the distribution transformers utilised within them. These transformers connect the IPP to the grid, and therefore it is important to understand the effects that such an installation could have on these units. This paper explores the existing literature on problems within PV systems, which include harmonics, non-liner loading and transients. It further analyses the effects that these problems could have on PV transformers. It also identifies the responsibilities of both the manufacturer and the utility and elaborates on the role that each play to ensure the compatibility of a transformer for a PV plant.
Article
Full-text available
Nanocomposites are pivotal for enhancing epoxy resin performance, but traditional inorganic nanofillers' poor compatibility and nonrecyclability pose environmental concerns. This study utilises recyclable organic cellulose nanocrystals (CNC) to explore their modification impact on epoxy composite properties. Through infrared spectroscopy and X‐ray photoelectron spectroscopy (XPS), the degree of modification for CNC and its derivatives—KH560‐modified CNC (KH560‐CNC) and methyl methacrylate‐modified CNC (MMA‐CNC)—was assessed. Scanning electron microscope (SEM) performance characterisation of modified CNC/epoxy composites showed that higher CNC modification levels significantly improve the toughness of the composites. Regarding thermal conductivity, modified CNCs affected the epoxy composites differently; KH560‐CNC/EP exhibited the best thermal conductivity at low filler concentrations, whereas MMA‐CNC/EP showed higher thermal conductivity at high concentrations. Additionally, nanocellulose's varying degrees of modification differently impacted the composites' moisture absorption and dielectric properties. The higher the CNC modification level, the stronger its moisture absorption capability, with minimal effect on dielectric loss. This paper provides experimental evidence for CNC/epoxy composite applications, offering practical guidance for future design and manufacturing of epoxy resin composites.
Article
Full-text available
A proper and effective maintenance and replacement schedule help to restore power equipment health condition, increase cost efficiency, and reduce the failure risk of the power grid. Imperfect maintenances cannot restore the equipment to a “as good as new” state as replacement did, but the financial cost of maintenance is much lower than that of replacement. The optimal balance and coordination between imperfect maintenances and replacements leads to the optimal substation operational cost. In this paper, a risk-based optimization model for power substation equipment maintenance and replacement scheduling is proposed in the presence of imperfect maintenances for the aging power equipment. The degradation process is firstly established based on historical trending analysis of failure data. Afterwards, a virtual age model is proposed for each equipment and the imperfect maintenance effectiveness is represented by the rejuvenation of this virtual age. Eventually, equipment failure risk, maintenance risk, and replacement risk are obtained, which are then incorporated into a MILP problem to obtain the optimal scheduling results. Case studies are performed on substations with three different bus-bar layout schemes. Results shows that the proposed method achieves a 34% lower total risk and 12.1% higher cost efficiency, compared to the traditional maintenance strategies.
Article
Timely detection of insulation faults in power transformers is essential to prevent damage, outages, and financial losses. Locating partial discharge (PD) sources in transformers with complex windings poses a significant chal- lenge, leading to insulation failure. This paper presents a novel approach combining a learning vector quanti- zation (LVQ) network with frequency response analysis (FRA) to locate PDs along the windings, even in noisy environments, without using noise suppression techniques. The method obtains sectional winding transfer functions (SWTFs) using vector fitting (VF). A Gaussian function is injected into each SWTF, and the responses are captured as PD reference signals to train the LVQ network. In addition, a 5000 pC PD test pulse from a calibrator is injected into randomly selected laboratory winding sections, while a traveling rectangular wave is injected into the estimated SWTFs, obtained from FRA using vector fitting. The resulting responses are utilized as PD test signals to assess the proposed method across various PD pulse waveforms. The simulation and experi- mental results demonstrate that the proposed method achieves superior performance, particularly in high-level background noise, leading to significantly improved PD localization accuracy. Finally, the method’s efficiency is compared with previous studies, particularly regarding performance in noisy conditions.
Article
Full-text available
The power transformer is the core equipment of the power system, a sudden failure of which will seriously endanger the safety of the power system. In recent years, artificial intelligence techniques have been applied to the dissolved gas analysis evaluation of power transformers to improve the accuracy and efficiency of power transformer fault diagnosis. However, most of the artificial intelligence techniques are data-driven algorithms whose performance decreases when the data are limited or significantly imbalanced. In this paper, we propose an active learning framework for power transformer dissolved gas analysis, in which the model can be dynamically trained based on the characteristics of the data and the training process. In addition, this paper also improves the original active learning spatial search strategy and uses the product of sample feature differences instead of the original sum of differences as a measure of sample difference. Compared to passive learning algorithms, the novel approach could significantly reduce the data labeling effort while improving prediction accuracy.
Assessment of Power Transformer Reliability
  • S Tenbohlen
S. Tenbohlen, et al., "Assessment of Power Transformer Reliability", Int. Symp. on High Voltage Engineering, Hannover, Germany, G-026, August 2011