Dissolved gas analysis and the Duval Triangle

by Michel Duval

-DGA is for Dissolved Gas Analysis.

-Still today, DGA is probably the most powerful tool for detecting faults in electrical equipment in service.

-Over one million DGA analyses are performed each year by more than 400 laboratories worldwide.

-Gases in oil always result from the decomposition of electrical insulation materials (oil or paper), as a result of faults or chemical reactions in the equipment.

-for example, oil is a molecule of hydrocarbons, i.e., containing hydrogen and carbon atoms,linked by chemical bonds (C-H, C-C).

-some of these bonds may break and form H*, CH3*, CH2* and CH* radicals.

All these radicals then recombine to form the fault gases observed in oil:

-in addition to these gases, the decomposition of paper produces CO2, CO and H2O, because of the presence of oxygen atoms in the molecule of cellulose:

Hydrogen H2

Methane CH4

Ethane C2H6

Ethylene C2H4

Acetylene C2H2

Carbon monoxide CO

Carbon dioxide CO2

Oxygen O2

Nitrogen N2

The main gases analyzed by DGA

-some of these gases will be formed in larger or smaller quantities depending on the energy content of the fault.

-for example, low energy faults such as corona partial discharges in gas bubbles, or low temperature hot spots, will form mainly H2 and CH4.

-faults of higher temperatures are necessary toform large quantities of C2H4.

-and finally, it takes faults with a very high energycontent, such as in electrical arcs, to form large amounts of C2H2.

-by looking at the relative proportion of gases in the DGA results it is possible to identify the type of fault occurring in a transformer in service.

6 basic types of faults detectable by DGA have thus been defined by the IEC and other organizations.

1.Partial discharges of the corona-type (PD).

-typical examples are discharges in gas bubbles or voids trapped in paper, as a resultof poor drying or poor oil-impregnation.

2.Discharges of low energy (D1)

-typical examples are partial discharges of the sparking-type, inducing pinholes or carbonized punctures in paper.

-or low-energy arcing, inducing carbonizedperforations or surface tracking of paper, orcarbon particles in oil.

3.Discharges of high energy (D2)

-typical examples are high energy arcing, flashovers and short circuits, with power follow-through, resulting in extensive damage to paper, large formation of carbon particles in oil, metalfusion, tripping of the equipment or gas alarms .

4.Thermal faults of temperatures < 300 °C (T1)

Faults T1 are evidenced by paper turning: -brown (> 200 °C). -black or carbonized (> 300 °C).

Typical examples are overloading, blocked oil ducts, stray flux in beams

5.Thermal faults of temperatures between 300 and 700°C (T2)

Faults T2 are evidenced by : -carbonization of paper.-formation of carbon particles in oil.

Typical examples are defective contacts or welds, circulating currents.

6.Thermal faults of temperatures > 700°C (T3)

Faults T3 are evidenced by : -extensive formation of carbon particles in oil.-metal coloration (800 °C) or metal fusion (> 1000 °C).

Typical examples are large circulating currents in tank and core, short circuits in laminations.

The first one was the Dornenburg method in Switzerland in the late 1960s, then the Rogers method in UK in the mid 1970s.

Variations on these methods have later been proposed by the IEC (60599) and IEEE.

Several diagnosis methods have been proposed to identify these faults in service.

Depending on the values of these gas ratios, codes or zones are defined for each type of fault.

One drawback of these methods is that no diagnosis can be given in a significant number of cases, because they fall outside the defined zones.

All these methods use 3 basic gas ratios: (CH4/H2, C2H2/C2H4 and C2H6/C2H4).

Another method used by IEEE is the so-called key-gas method, which looks at the main gas formed for each fault, e.g, C2H2 for arcing.

One drawback of this method is that it often provides wrong diagnoses.

Finally, there is the Triangle method, which was developed empirically in the early 1970s, and is based on the use of 3 gases (CH4, C2H4 and C2H2) corresponding to the increasing energy levels of gas formation.

One advantage of this method is that it always provides a diagnosis, with a low percentage of wrong diagnoses.

Comparison of diagnosis methods.

% Unresolveddiagnoses

% Wrong diagnoses

% Total

Key gases 0 58 58

Rogers 33 5 38

Dornenburg 26 3 29

IEC 15 8 23

Triangle 0 4 4

However, many people are not quite familiar with the use of triangular coordinates, so I will try to explain that in more detail today.

The triangle representation also allows to easily follow graphically and visually the evolution of faults with time.

The triangle method.

The triangle method plots the relative % of CH4, C2H4 and C2H2 on each side of the triangle, from 0% to 100%.

The 6 main zones of faults are indicated in the triangle, plus a DT zone (mixture of thermal and electrical faults).

Question: how corona PDs, which form a lot of H2, can be identified in the Triangle without using this gas ?

Answer: in such faults, CH4 is formed in smaller amounts than H2 (typically 10 to 20 times less), but it can still be measured easily by DGA.

Answer: because CH4 provides better overall diagnoses for all types of faults.

Another question: in the Triangle, why not use H2 rather than CH4 to represent low energy faults ?

A possible explanation (?): H2 diffuses much more rapidly than hydrocarbon gases from transformer oil. This will affect gas ratios using H2 but not those using hydrocarbon gases.

So, how to use the triangle ?

First calculate: CH4 + C2H4 + C2H2 = 300 ppm.

If for example the DGA lab results are: CH4 = 100 ppm C2H4 = 100 ppm C2H2 = 100 ppm

Then calculate the relative % of each gas: relative % of CH4 = 100 / 300 = 33,3 % relative % of C2H4 = 100 / 300 = 33,3 % relative % of C2H4 = 100 / 300 = 33,3 %

These values are the triangular coordinates to be used on each side of the triangle.

To verify that the calculation was done correctly, the sum of these 3 values should always give100%, and should correspond to only one point in the triangle.

Each DGA analysis received from the lab will always give only one point in the triangle.

The zone in which the point falls in the Triangle will identify the fault responsible for the DGA results.

The calculation of triangular coordinates can easily be done manually, or with the help of a smallalgorithm or software.

Errors are often made when developing such an algorithm, so check it first with the free software available from duvalm@ireq.ca.

For those familiar with computer graphics, it is also possible to develop a software displaying the point and the fault zones graphically in the triangle.

Several commercial software are available for that purpose, e.g., from Serveron, Kelman or Delta-X Research in Canada.

.The Triangle, being a graphical method, allowsto easily follow the evolution of faults with time, for instance from a thermal fault to a potentially much more severe fault such as D2.

.

Fault zones in the triangle have been defined by using a large number of cases of faulty transformers in service which had been inspected visually.

Cases of faults PD and D1

� tracking; sparking; small arcing.

Cases of faults D2

� circulating currents ; laminations ; bad contacts

Cases of thermal faults in oil only

brownish paper ; � carbonized paper ; not mentioned

Cases of thermal faults in paper

A popular ratio used for that purpose is the CO2 / CO ratio.

If the CO2 / CO ratio is < 3, this is a strong indication of a fault in paper, either a hot spot or electrical arcing.

A fault in paper is generally considered as more serious than a fault in oil only, because paper is often placed in a HV area (windings, barriers).

The CO2 / CO ratio, however, is not very accurate, because it is also affected by the background of CO2 and CO coming from oil oxidation.

The amounts of furans in oil may also be used in some cases to confirm paper involvement, however, the interpretation of results is often difficult.

. Other useful gas ratios:

-C2H2/ H2 : a ratio > 3 in the main tank indicates contamination by the LTC compartment

-O2/ N2: a decrease of this ratio indicates excessive heating (< 0.3 in breathing transformers).

.

Gassing not related to faults in service:

-Catalytic reactions on metal surfaces: formation of H2 only.

-“Stray” gassing of oil: the “unexpected gassing of oil at relatively low temperatures (80 to 200 °C)”.

Stray gassing after 16hours of test at 120°C, in ppm :

.Oil H2 CH4 C2H4 C2H6 C2H2 CO CO2

Non-stray gassing 3 1 - - - 3 43

Strongly stray gassing 1088 172 11 27 - 500 1880

in ppm

It has been found at CIGRE that stray gassing:

. -may interfere with DGA diagnoses in service only in the case of the most stray gassing oils, or under overloading conditions.

- will not interfere with diagnoses during factory tests.

.

Now, a critical look at DGA results coming from the laboratory.

DGA labs are not perfect. Like everyone else they will sometimes make mistakes, and some are not as accurate as we expect them to be.

Laboratory accuracy, however, has a direct effect on diagnosis accuracy and on diagnosis uncertainty.

The accuracy of the “average” lab has been found by CIGRE to be ± 15% at medium (routine) gas concentration levels (> 10 ppm for hydrocarbons).

Accuracy will thus fall to ~ ± 30% at 6 ppm, and ± 100% near the detection limit.

Accuracy decreases rapidly as gas concentration decreases, following approximately the equation: ±15% ± 2 ppm (detection limit).

Effect of laboratory accuracy (±15% and ±30%, respectively) on DGA diagnosis uncertainty.

When an area of uncertainty crosses several fault zones in the triangle, a reliable diagnosis cannot be given.

Lab accuracies worse than 30% in general will provide unreliable or totally wrong diagnoses.

Diagnosis uncertainty corresponding to lab accuracies of ± 15, 30, 50 and 75 %:

Accuracy of laboratories at medium gas concentrations

Accuracy of laboratories at low gas concentrations

Users should ask their DGA labs to indicate the accuracy of their DGA results, to be able to calculate the uncertainty on the diagnoses.

To verify the accuracy of routine DGA analyses, users should also from time to time send to the lab a “blind” sample of gas-in-oil standard.

Such gas-in-oil standards are now available commercially, e.g., from Morgan Schaffer in Canada

They can also be prepared by the laboratory, following procedures or concepts described in IEC 60567 or ASTM D3612.

Inaccurate DGA results, whatever their cost, low or high, are a waste of money since they cannot be used reliably.

Furthermore, they may lead to wrong diagnoses, with possibly serious consequences for the equipment.

A similar investigation is presently underway at CIGRE TF15 to evaluate the accuracy of on-line and portable gas monitors.

A recommendation of CIGRE and the IEC is that DGA diagnosis should be attempted only if gas concentrations or rates of gas increase in oil are high enough to be considered significant.

Low gas levels may be due to contamination or aging of insulation, not necessarily to an actual fault.

Gas levels in service

Also, there is always a small level of gases in service, and it would not be economically viable to suspect all pieces of equipment.

It is better to concentrate on the upper percentile of the transformer population with the highest gas levels.

This is the philosophy behind the use of 90% typical concentrations and 90% typical rates of increase, in order to concentrate maintenance efforts on the 10% of the population most at risk.

A lot of work has been done recently at CIGRE and the IEC in these areas, and a consensus reached on typical values observed in service worldwide.

Ranges of 90 % typical concentration values for power transformers, in ppm:

C2H2 H2 CH4 C2H4 C2H6 CO CO2

All transformers 50-150

30-130

60-280

20-90

400-600

3800-14000

No OLTC 2-20

Communicating OLTC

60-280

Ranges of 90 % typical rates of gas increase for power transformers, in ppm/year:

C2H2 H2 CH4 C2H4 C2H6 CO CO2

All transformers 35-132

10-120

32-146

5-90

260-1060

1700-10,000

No OLTC 0-4

Communicating OLTC

21-37

90% typical values are within the same range on all networks, with some differences related to the individual loading conditions, equipment used, weather, etc.

Influence of some parameters on typical values:

-Typical values are significantly higher in young equipment (suggesting there are some unstable chemical bonds in new oil and paper ?). -A bit higher in very old equipment.

-Significantly lower in instrument transformers. -Higher in shell-type and shunt reactors (operating at higher temperatures ?).

-Not affected by oil volume (suggests that larger faults are formed in larger transformers ?).

When DGA results are above typical values:

-a diagnosis may be attempted to identify the fault producing these gases.

-the equipment should not be considered at risk.

-however, the equipment should be monitored more frequently by DGA.

The typical values surveyed by CIGRE are ranges of values observed worldwide on a large number of networks.

Each individual network should preferably calculate its own specific typical values.

To calculate typical concentration values, the cumulative number of analyses should be drawn as a function of concentration, for each gas.

Cumulative number of DGA analyses, in %vs. gas concentration, in ppm

T = the 90% typicalconcentration value

As long as DGA values in service remain relatively close to typical values, there is no reason to be concerned by the condition of the transformer.

To evaluate how much at risk a transformer may become above typical values, the probability of failure in service (PFS) has to be examined.

PFS has been defined as the number of DGA analyses followed by a failure-related event (e.g., tripping, fault gas alarm, fire, etc), divided by the total number of analyses, at a given gas concentration.

90 98 99 Norm, in %

Probability of having a failure-related event ( PFS, % )vs. the concentration of C2H2 in ppm

100 300 400 ppm

PFS, in %

The PFS remains almost constant below and above the 90% typical value, until it reaches an inflexion point on the curve (pre-failure value).

DGA monitoring should be done more and more frequently as gas concentrations increase from typical to pre-failure value.

Pre-failure values were found by CIGRE to be surprisingly close on different networks,

H2 CH4 C2H4 C2H6 C2H2 CO

240-1320

270-460

700-990

750-1800

310-600

984-3000

(in ppm)

This suggests that failure occurs when a critical amount of insulation is destroyed.

In-between typical and pre-failure values, specific alarm values can be defined, depending on the tolerance to risk of the maintenance personnel, also on the maintenance budget available.

For example, higher alarm values may be used when the maintenance budget is low, and lower alarm values in the case of strategic equipment.

Summary of typical, alarm and pre-failure values:

Concentration

Time