Dissolved Gas Analysis (DGA) Test for Transformer Health Monitoring

This module explains the importance of transformers in electrical circuits, the need for their maintenance and monitoring, and the Dissolved Gas Analysis (DGA) test for evaluating transformer health. It also covers the estimated outcome of DGA analysis, interpretation of the test, and the role of an asset manager in decision making. Subject: Electrical Engineering, Course Code: NA, Course Name: NA, College/University: NA.

ABSTRACT
Transformers have been a necessary and vital component in electrical and
electronic circuits since 1830s. Even though novice electronic equipments reduce the
usage of transformers, they still play their major part in the power distribution system.
There is a necessity of the transformers which should be maintained annually and it
should be regularly monitored. There are several tests for analysis and in this particular
module we had explained regarding the Dissolved Gas Analysis (DGA) test and the
decision had to be made by this analysis test whether a transformer should function or
not. An asset manager plays a major role in this contribution.

SNO TITLE PAGENO
1. INTRODUCTION 3
2. DISSOLVED GAS ANALYSIS (DGA) 3
3. ESTIMATED DGA OUTCOME 5
4. INTERPRETATION OF DGA TEST 6
5. ASSET MANAGER DECISION MAKING 8
6. CONCLUSION 9
REFERENCES 10

INTRODUCTION:
Transformers are the most important component in the field of electrical engineering which
could have a long life and said to be a cost intensive component. These transformers constitute
an electrical supply networks. A transformer works on the principle of electromagnetism to
modify an AC voltage to another. The oil sample analysis is said to be a maintenance method
which is carried out to monitor the transformer health. There are various types of analysis test
such as standard oil test, Dissolved Gas Analysis (DGA) and furan analysis through which
detailed information regarding the operation of the transformer is collected. Normally the
Dissolved Gas Analysis (DGA) test is carried out to find the electrical (Hjartason, 2006)
abnormalities. Through this method we can able to determine the electrical fault as well as the
thermal faults. Each fault can be categorized into three different division based on the
international standard IEC 60599. Though there are different techniques, the Dissolved Gas
Analysis became most accepted technique in the last decade. In this paper, the discussion is done
regarding the DGA and also brief information is given about the decision making of an asset
manager with the data received from the analysis.
Dissolved Gas Analysis (DGA):
Performance which is carried out by DGA (Hjartason& Otal, 2006) in the insulating oil
with the oil sampling analysis test is used as an evaluation of the transformer health. Any
malfunction that happens inside a transformer and its required equipment could generate some
gases inside it. Therefore, the identification of these gases and the information obtained from that
could be very useful for some maintenance and prevention. There are many methods to estimate
these gases but the Dissolved Gas Analysis (DGA) is said to be the most efficient. In order to
measure the concentration of the dissolved gases, there are two process carried out: 1) Sampling
the oil obtained 2) Testing the samples. This DGA analysis should be carried out at least a year
and the details should be compared with the previous analysis data. There are several standards
such as ASTM D3613, ASTM D3612, and ANSI/IEEE C57.104(Rowland & Bahadoorsingh,
2008), respectively to evaluate the result.

The main causes of the formation of the gases are due to the electrical strife and thermal
putrefaction. At some point, each and every transformer could produce gases in usual working
temperature. The transformer insulation process is done through several mineral oils which is
said to be the composition of several hydrocarbons. The decomposition process in these
hydrocarbons is said to be tedious due to the thermal and the electrical fault (Abu-Elanien &
Salama, 2009). The basic reaction occurs due to the breakage of C-H bonds and C-C bonds.
Hence we could get the fragments of hydrocarbon and some hydrogen atoms. This leftover
mingle with each other and leads to the formation of gases such as hydrogen (H2), methane
(CH4), acetylene (C2H2), ethylene (C2H4), and ethane (C2H6). Moreover, due to the cellulose
insulation, thermal decomposition or electrical problem generates methane (CH4), hydrogen (H2),
carbon monoxide (CO), and carbon dioxide (CO2). These gases are considered to be the key
gases and their property is said to be combustible (here the exceptional gas is CO2 which is non-
combustible).
This key gas depends highly on their temperature (John, 2006) which is based on their
volume of material at that circumstantial temperature. The small volume at high temperature
could produce the same quantity of gases as produced by the huge volume at restrained
temperature. This is mainly caused due to the effect on volume. For this reason, the gases which
are formed due to the transformer’s insulating oil is used for the evaluation process by
comparing with the past history of these transformers (Ridwan, Talib & Ghazali, 2014) in order
to find out any faults that could happen potentially or thermally.
Later the appropriate samples is examined and evaluated, the foremost step of the DGA analysis
is to find the concentration levels of each and every key gases samples. This could be expressed
in parts per million (ppm). It is endorsed that the concentration of the key gases change in time
and therefore the rate of change of the concentration is calculated (Jongen, Gulski, Morshuis,
Smith, Janseen, 2007). Fundamentally, the probable fault in the transformer could be indicated
by the sharp rise in the value of key gas concentration. Therefore it could be said that the result
of the DGA analysis gives a sharp rise in the value of the concentration level of the gases. If the
normal value limit is surmounted, then supplementary analysis of the sample should be taken and
once again we have to confirm where the key gas concentration level is accumulating. When the
level reach the action level point then the transformer (Ledwich and Islam, 2000) should be

considered and that particular transformer should be removed. Therefore care must be taken
while taking this sample analysis test. This particular test involves in the calculation of the key
gas ratio and then correlating it with certain limit range.
Table 1: The description of the gas with their limit range and their fault type
Gas Description Normal Limit(<) Actual Limit(>) Potential fault type
H2(Hydrogen) 150 1000 Corona, Arcing
CH4(Methane) 25 80 Sparking
C2H2(Acetylene) 15 70 Arcing
C2H4(Ethylene) 20 150 Severe Overheating
C2H6(Ethane) 10 35 Local Overheating
CO(Carbon Monoxide) 500 1000 Severe Overheating
CO2(Carbon dioxide) 10000 15000 Severe Overheating
TDCG(TotalCombustibles
)
720 4630
The Gas Description with their respective key gas concentration is given in the above
table. When the value exceeds the normal limit then the sample frequency should be increased
with the consideration given to planned outage in near term for the further evaluation. When the
value exceeds the Action limits then the particular transformer should be removed immediately
from the service.
ESTIMATED DGA OUTCOME:
At the table given below, consists of the data composed as part of a random sampling test
from the Buchholz relay of transformer C2. This subsequent test of DGA analysis (Paul,

Barringer &Associates, 2003) was carried out in all the transformers and the result is given in
the form of a bar graph shown in figure 1. The transformer is an autotransformer which is of
core-type with 132/66kV and 90MVA.
Table 2: Estimated result from the DGA analysis test
Install
Date
Sub Transforme
r
H2 CH4 C2H6 C2H4 C2H
2
CO C02
06/201
3
A A1 11.7 9.98 6.40 6.19 0.05 323.8 3001.1
6
06/201
3
A A2 19.68 92.93 362.0
6
3.57 0.05 243.9
4
3002.2
7
06/201
3
B B1 18.04 75.02 306.7
6
7.54 0.05 204.1
5
2589.9
3
06/201
3
C C1 46.23 366.5
5
391.8
7
464.1
5
0.05 247.4
1
3733.9
9
06/201
3
C C2 150.8
1
365.8
7
183.9
7
899.4
2
6.48 35.72 1583.5
4
06/201
3
D D1 12.86 55.84 233.1
4
5.47 0.79 192.4
9
2150.2
3
06/201
3
D D2 25.04 134.3
9
637.1
4
23.67 0.05 218.5 1695.5
2
06/201
3
D D3 17.86 123.2
2
582.3
7
25.27 0.59 199.9
6
1769.8
5
06/201
3
E E1 13.75 86.17 350.7
3
5.35 0.05 127.2
6
2485.0
8
06/201
3
E E2 15.95 94.17 223.0
2
8.85 0.05 201.2 2015.3
9

A
A
B
C
C
D
D
D
E
E
0 1000 2000 3000 4000 5000 6000
H2
CH4
C2H6
C2H4
C2H2
CO
CO2
Figure 1: Representation of the Estimated DGA analysis in the form of bar graph
INTERPRETATION OF DGA TEST:
The foremost step in the elucidation of DGA data is to examine the glitches with the
rectitude of the data. Any problems with the perceived data must be handled before any
culmination is declared regarding the transformer. This interpretation (Andress, Endrenyi, and
Yung(2010) of the DGA analysis test should be concluded once it is compared with the previous
result of the analyzed data from the old samples. If the result of the data goes well with the
previous one, then the data could be considered and based on that the transformers could be
stated. If it does not agree with the earlier sample data, then the particular data should be
inspected before the fault outcomes are made.
1. Concentration of the gas can alter based on the sample:
The best sampling could be acquired from the transformer with is rich in the insulation oil and
therefore best concentration measurement can also be obtained. The uncertainty of this sampling
process could be 10-15% (Bertling, 2002). Deprived repeatability measurement of gas

concentration can hide minute fluctuations that could be an indication of problem in the early
stage and make it very arduous to detect and evaluate any fault that is identified.
2. Different sample values obtained:
Human error is common and these errors could be: interchanging the sample values between
two gases; changing the sample from a distant oil compartment or from a distant
transformer; replicating or withdrawing digits in a numbers (Li, and Pai, 2002). This could also
be possible due to the inappropriate oil sample and due to the aging and improper maintenance of
the equipments.
3. Environmental factors could affect the concentration:
If the concentration of the hydrogen gas decreases it means that the gas is exposed by the oxygen
content which could be caused due to some air bubbles from the sample syringe. If other gases
concentration is decreased or increased except hydrogen then there could be some possibilities of
transcription error and sometimes it could be due to the stray gassing.
4. Concentration of H2 gas is low in every sample:
H2 gas has a property to escape very quickly at any instant, (Li , Jonas, Yan, Corns, Choudhury,
and Vaahedi, 2007) and the transformer could lose other gases due to their design or there could
be an outflow through an erupted conservator diaphragm. When this happens then care should be
taken since this could lead to the missing of certain fault or their asperity could be underrated.
The decrease in the H2 gas could be due the problem in the sensors or the gas chromatography. If
this is the case then there could be some possibility of the inaccurate measurement of the other
gases.
5. Replacement of oil:
Oil that is kept inside the layers of paper winding separator (Werle, 2003) is generally
unsophisticated by degassing or substituting the oil from the main tank. Later, the gas from the
winding cover oil undergo diffusion over weeks or months into the clean oil until the gas
concentrations interior and exterior the paper separator gets balanced. More often than not

(accepting that no novice gas is formed in the mean time) the ultimate impact is to reestablish
approximately 10% to 15% of the gas level decline (Li & Korczynski, 2004). The increase in the
concentration of the gas, taken after degassing or oil substitution must not be mixed up with the
dynamic gas generation.
ASSET MANAGER DECISION MAKING:
The Resource Chief must choose on a consolidation of various activities that imitate plant
stacking and stretch levels, support plans, and substitution timetabling. These things are for the
most part forbid additionally depend upon the framework (Perkins, Pettersson, Fantana,
Oommen, Jordan, 1999) necessities of the gear. It is conceivable that one course to resource
cultivation includes changing the working environment of the thing to expand life or reduce
prompt disappointment probability. These things are by and large forbid additionally depend
upon the framework necessities of the gear (Aubin, Bourgault, Rajotte, Gervais, 2002). It is
conceivable that one course to resource cultivation includes changing the working environment
of the thing to amplify life or decrease quick disappointment probability.

Figure 2: The decision made by an asset manager based on the following consideration
CONCLUSION:
Transformers are the most important equipment and essential asset in a substation and the
failure of the transformers could result in the heavy damage both electrically and economically.
Hence regular monitoring of the transformer is necessary and the details should be maintained
properly. The sampling methods so far we discussed above is the best method and this could be
done with the various equipment. The test carrying equipment should also be maintained
properly. An asset manager should play a major role in these cases and the decisions made by an
asset manager should be viable.

REFERENCES:
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Current Health Index and Maintenance Level, Albuquerque, NM, USA:IEEE 11th International
Conference on Transmission & Distribution Construction, Operation and Live-Line
75 Maintenance.
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and Power Network Asset Management. Vancouver: IEEE International Symposium on
Electrical Insulation.
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Transformers. University of Waterloo, Waterloo, ON, Canada: Electric Power Systems Research
John, W.(2006)PAS 55 - Asset Management: Concept and Practise. Daytona Beach Florida:
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Transformer Component Life Time Data. Singapore: IEEE. 3-6, December. pp 16-18
Ledwich, G., Wu, T. and Islam, S.M(2000) A Novel Fuzzy Logic Technique for Power
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York: IEEE Computer Application in Power. pp. 20-26.
Bertling, L. (2002) Reliability Centered Maintenance for Electric Power Distribution Systems.
Ph.D. thesis. Stockholm: Royal Institute of Technology (KTH).

Li, W. and Pai, S. (2002) Evaluating Unavailability of Equipment Aging failures. IEEE Power
Engineering Review. February. pp52-54
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