Together We Power The World Techniques for Interpretation of Data for DGA From Transformers Lance Lewand, Doble Engineering
Together We PowerThe World
Techniques for Interpretation of Data for DGA From Transformers
Lance Lewand, Doble Engineering
2006 IEEE Conference
Purpose of DGA
• To provide a non-intrusive means to determine if a transformer incipient fault condition exists or not
– Too conservative– Too liberal
• To have a high probability that when entering an transformer a problem is apparent
• To prevent an unexpected outage
• To reduce risk to the unit and the system/company
2006 IEEE Conference
Interpretation Techniques
• Incipient Fault Types, Frank M. Clark, 1933/1962
• Dörnenburg Ratios, E. Dörnenburg, 1967, 1970
• Potthoff’s Scheme, K. Potthoff, 1969
• Absolute limits, various sources, early 1970s
• Shank’s Visual Curve method, 1970s
• Trilinear Plot Method, 1970s
• Key Gas Method, David Pugh, 1974
• Duval Triangle, Michel Duval, 1974
2006 IEEE Conference
Interpretation Techniques
• Rogers Ratios, R.R. Rogers, 1975
• Glass Criterion, R.M Glass, 1977
• Trend Analysis, various sources, early 1980s– total volume per day– ppm per day
• Church Logarithmic Nomograph, J.O. Church, 1980s
• Expert System Analysis, Richard Lowe, 1985
2006 IEEE Conference
Interpretation Techniques
• Expert System Monitor Program, Karen Barrett, 1989
• Transformer Fingerprinting
• IEEE C57.104, Limits, rates and TDCG, 1978/1991
• Artificial Neural Networks (ANNs) and Fuzzy Logic– X. Ding, E. Yao, Y. Liu and Paul Griffin, 1996– Vladimiro Miranda and Adriana Garcez Castro, 2004– Donald Lamontagne, 2006
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Interpretation Techniques
• IEC 60599 Ratios, Limits and gassing rates, 1999
• Datamining and Log Transformation, Tony McGrail, 2000
• Vector Algorithm, Nick Dominelli, Mike Lau & David Pugh, 2004
2006 IEEE Conference
Most Commonly Used
• Duval Triangle• IEEE C57.104, Limits, rates and TDCG• Straight Limits• Key Gas Method• Dörnenburg Ratios• Rogers Ratios• IEC 60599 Ratios and Limits• Trend Analysis• Fingerprints• Expert System Analysis
2006 IEEE Conference
Dissolved Gas Acceptable Limits Various Sources
H2 CO CH4 C2H6 C2H4 C2H2 CO2 TCG
*IEEE 100101-700701-1800
>1800
350351-570571-1400
>1400
120121-400
401-1000>1000
6566-100
101-150>150
5051-100
101-200>200
3536-5051-80>80
25002500-4000
4001-10000>10000
720721-1920
1921-4630>4630
**Electra (CIGRE)
28.6 289 42.2 85.6 74.6 -- 3771 520
IEC 60599TypicalRange
60-150 540-900 40-110 50-90 60-280 3-50 5100-13000
Manufact. 200(250)
500(1000)
100(200)
100(200)
150(300)
15(35)
----
10651985
*IN THE PROCESS OF BEING REVISED**CORRECTED VALUES 1978( ) VALUE 6 – 7 YEARS
2006 IEEE Conference
Key Gases - Arcing
0
1020
30
40
5060
70
8090
100C
ombu
stib
les,
%
CO H2 CH4 C2H6 C2H4 C2H2
2006 IEEE Conference
Key Gases - Overheating, Oil
0
1020
30
40
5060
70
8090
100C
ombu
stib
les,
%
CO H2 CH4 C2H6 C2H4 C2H2
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Key Gases - Partial Discharge
0
1020
30
40
5060
70
8090
100C
ombu
stib
les,
%
CO H2 CH4 C2H6 C2H4 C2H2
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Key Gases - Overheating, Paper
0102030405060708090
100C
ombu
stib
les,
%
CO H2 CH4 C2H6 C2H4 C2H2
2006 IEEE Conference
Dörnenburg Ratio Method
• Started out as only two ratios– CH4/H2– C2H2/C2H4– plotted on a log-log scale. The areas corresponded to
thermal deterioration, arcing and partial discharge– too many faults missed - went to 4 ratios
• Ratio 1 (R1)=CH4/H2
• Ratio 2 (R2)=C2H2/C2H4
• Ratio 3 (R3)=C2H2/CH4
• Ratio 4 (R4)=C2H6/C2H2
2006 IEEE Conference
Dörnenburg Ratio Method
• Used to determine 3 general fault types– Thermal faults– Electrical Faults, low intensity discharges– Electrical Faults, high intensity arcing
2006 IEEE Conference
Dörnenburg Ratio-Minimum Gas Levels (Dörnenburg & IEEE Levels)
Hydrogen 200 100
Methane 50 120
Carbon Monoxide 1000 350
Acetylene 15 35
Ethylene 60 50
Ethane 15 65
2006 IEEE Conference
Dörnenburg Ratio
• Criteria for application - a fault exists – One Gas > 2 x minimum level– At lest one gas > minimum level
• Determine Validity, L1 norm test– One gas in each ratio > minimum
• Compare ratios to Fault Diagnosis Table
• All fall within one condition-valid diagnosis
2006 IEEE Conference
Dörnenburg Ratio-Fault Diagnosis Table, from the oil
R1CH4/H2
R2C2H2/C2H4
R3C2H2/CH4
R4C2H6/C2H2
1-ThermalDecomp >1.0 <0.75 <0.3 >0.42-LowIntensity PD <0.1 Not Sig <0.3 >0.4
3-Arcing >0.1,<1.0 >0.75 >0.3 <0.4
Valid only if all the ratios for a particular fault type are met.
2006 IEEE Conference
Dörnenburg Flowchart
From IEEE C57.104 - 1991
2006 IEEE Conference
Initial Roger’s Ratios
• Took information from Halstead’s thermal equilibrium and Dörnenberg ratios along with information from faulted units
• Originally developed four ratios– CH4/H2
– C2H6/CH4
– C2H4/C2H6
– C2H2/C2H4
• Came up with a 4 number code that identified 11 incipient fault conditions and a normal condition
2006 IEEE Conference
Halstead’s Thermal Equilibrium
2006 IEEE Conference
Initial Roger’s Ratios
Ratio Range Code
CH4/H2 ≤ 0.1>0.1 <1≥1 <3≥ 3
5012
C2H6/CH4< 1≥ 1
01
C2H4/C2H6< 1≥ 1 <3≥ 3
012
C2H2/C2H4< 0.5≥0.5 <3≥ 3
012
2006 IEEE Conference
Roger’s Fault Diagnosis Table
CH4/H2 C2H6/CH4 C2H4/C2H6 C2H2/C2H4 Diagnosis0 0 0 0 Normal5 0 0 0 Partial Discharge½ 0 0 0 Slight Overheating – below 150°C½ 1 0 0 Slight Overheating –150°C to 200°C0 1 0 0 Slight Overheating –200°C to 300°C0 0 1 0 General conductor overheating1 0 1 0 Winding circulating currents1 0 2 0 Core and tank circulating currents,
overheated joints0 0 0 1 Flashover without power follow through0 0 ½ ½ Arc with power follow through0 0 2 2 Continuous sparking to floating potential5 0 0 ½ Partial discharge with tracking
2006 IEEE Conference
Refined Roger’s Ratio
• Three ratios– Ratio 1 (R1)=CH4/H2
– Ratio 2 (R2)=C2H2/C2H4
– Ratio 5 (R5)=C2H4/C2H6
• No minimum levels– suggested when normal levels exceeded
2006 IEEE Conference
Refined Roger’s Ratio-Fault Diagnosis
Case R2C2H2/C2H4
R1CH4/H2
R5C2H4/C2H6
Fault
0 <0.1 >0.1,<1.0 <1.0 Normal
1 <0.1 <0.1 <1.0 Low energyPD
2 0.1-3.0 0.1-1.0 >3.0 Arcing
3 <0.1 >0.1<1.0 1.0-3.0 Low tempthermal
4 <0.1 >1.0 1.0-3.0 Thermal<700°C
5 <0.1 >1.0 >3.0 Thermal>700°C
2006 IEEE Conference
Roger’s Ratios Flowchart
From IEEE C57.104 - 1991
2006 IEEE Conference
IEC 60599
• Identifies 6 different fault types– PD: Partial Discharge– D1: Discharge of low energy– D2: Discharge of high energy– T1: Thermal fault, t <300°C– T2: Thermal fault, 300°C < t < 700 °C– T3: Thermal fault, t > 700 °C
• Uses a combination of ratios (based on Roger’s Ratios), gas concentrations and rates of gas increase
2006 IEEE Conference
IEC 60599 Ratio-Fault DiagnosisR2
C2H2/C2H4
R1CH4/H2
R5C2H4/C2H6
Fault
NS <0.1 <0.2 PD
>1 0.1-0.5 >1 D1 -Lowenergy
0.6-2.5 0.1-1 >2 D2 –Highenergy
NS >1 (NS) <1 T1 <300C
<0.1 >1 1-4 T2 >300C<700°C
<0.2 >1 >4 Thermal>700°C
NS = not significant regardless of valueConcentrations should be 10 x S (MDL)
2006 IEEE Conference
IEC 60599 Rates of gas increase
• >10% increase per month above typical levels = active fault
• >50% per week or evolving faults of higher energy = serious
2006 IEEE Conference
IEC 60599 Typical Gas Levels
H2 CO CH4 C2H6 C2H4 C2H2 CO2
IEC 60599TypicalRange
60-150 540-900 40-110 50-90 60-280 3-50 5100-13000
CommunicatingOLTC
75-150 400-850 35-130 50-70 110-250 80-270 5300-12000
Note in IEC 60599: Typical values are higher in sealed transformers than free breathing transformers
2006 IEEE Conference
Ratio Methods
• Advantages– quantitative– independent of oil volume– can be computer programmed
• Disadvantages– don’t always yield an analysis– not always correct– dependence of preservation system– Dornenburg has fallen out of favor because it misses
too many incipient faults
2006 IEEE Conference
Ratio Methods
• Solid insulation handled separately using carbon monoxide and carbon dioxide ratios
2006 IEEE Conference
Trend Analysis
• Historical Information
– Has the percent TCG in the gas space risen suddenly?
– Has the percent TCG in the oil risen suddenly?
– Nameplate information
– How old in the transformer?
2006 IEEE Conference
Trend Analysis
– Did a bushing fail at some point?
– Did the transformer fail previously?
– If the unit has been repaired and was the oil filtered or degassed?
– Is the unit heavily loaded or overloaded?
– Previous dissolved gas-in-oil test?
2006 IEEE Conference
Transformer Fingerprints
GAS (PPM) Initial 3 Initial 3Hydrogen 350 260 110 210Methane 44 61 11 13Carbon Monoxide 670 650 520 630Ethane 26 25 3 4Carbon Dioxide 3000 1900 5000 3900Ethylene 9 5 8 10Acetylene -- -- -- --
2006 IEEE Conference
GAS (PPM) Initial 3 Initial 3Hydrogen 0 1 0 0Methane 92 69 15 18Carbon Monoxide 370 400 33 57Ethane 2300 2300 560 520Carbon Dioxide 6000 6800 1800 2200Ethylene 180 180 9 6Acetylene 0 0 0 0
Transformer Fingerprints
2006 IEEE Conference
Carbon Oxide Gases and Ratios
Cellulose Insulation• Shell form > CO2 than core form - due to
mass• Accidental CO2
• CO2/CO : 3 -14:1• CO2/CO Avg. 7:1• Approach 1 high temperature faults• High CO2 with low CO-lack of
cooling/general overheating
2006 IEEE Conference
Pitfalls
• Gases produced not as a result of incipient fault condition– Leaking between tap changers and main tank– lower voltage transformers having higher CO
and CO2 values as a result of non-vacuum Hitreatment
– Welding producing acetylene and other gases– Out-gassing of paints and gaskets, usually CO
and CO2– Stray gassing characteristics
2006 IEEE Conference
Pitfalls
• Incipient Faults not really covered– production of hydrogen from overheated oil
thin films on core laminations (>140°C)– Oxidation and thermal heating of the oil
causing the production of CO and CO2
• Gases produced not as a result of incipient fault condition– Leaking between the tap changer and main
tank
2006 IEEE Conference
Pitfalls
– Galvanic reactions (steel + water + O2 = hydrogen production)
– lower voltage transformers having higher CO and CO2 values as a result of non-vacuum treatment, oxygen + heat
– Welding producing acetylene and other gases
– Out-gassing of paints, gaskets & polymers, usually CO and CO2
2006 IEEE Conference
Pitfalls
– Stray gassing characteristics (highly refined oils ⇒ H2)
– Contaminants produce gases
– Decomposition of additives such as passivators can produce gases as well (H2 and CO2)
2006 IEEE Conference
In Reality - Expert Systems are Used
• History• Key gases• Ratios• Fingerprints - similar populations• Trend analysis• Internal databases• Total combustible gas• Rate of gas generation• A human expert
Use the tools in the toolbox, not
just one!!!
2006 IEEE Conference
THANK YOU FOR YOUR ATTENTION
IEEE/PES Transformer CommitteeMontreal, Canada
Tuesday, October 24, 2006
Dissolved gas analysis and the Duval Triangle
by Michel Duval
-DGA is for Dissolved Gas Analysis.
-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.
Gas formation patterns
-are related only to the materials used and faultsinvolved.
-are the same in all equipment where these materials are used (e.g., sealed or air-breathingpower transformers, reactors, instrumenttransformers, LTCs, etc).
Standards/ Guides for the interpretation of DGA:-IEC Publication 60599 (1999).-IEEE Guide C57.104 (1991) (under revision).
Other useful information in:-IEEE EI.Mag., Apr. 2001, June 2002, Aug. 2005.-CIGRE Brochure # 296 (2006).
6 basic types of faults detectable by DGA have been defined by the IEC:
1.Partial discharges of the corona-type (PD).
-typical examples: discharges in gas bubblesor voids trapped in paper, as a result of poor drying or poor oil-impregnation.
2.Discharges of low energy (D1)
-typical examples: partial discharges of the sparking-type, inducing carbonized punctures in paper.
-or low-energy arcing, inducing surface trackingof paper and carbon particles in oil.
3.Discharges of high energy (D2)
-typical examples: 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: overloading, blocked oil ducts
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: defective contacts, defective 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: 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.
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).
Depending on the values of these gas ratios, codes or zones are defined for each type of fault.
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 which is used by the IEC.
It 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).
FAQ: How fault zones have been defined in the Triangle ?
Answer: Fault zones are based on a large number of cases of faulty transformers in service which have 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
FAQ: 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 indeed formed in smaller amounts than H2 (typically 10 to 20 times less), but can still be measured easily by DGA.
Answer: because CH4 provides better overall diagnoses for all types of faults.
FAQ: 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.
First calculate: CH4 + C2H4 + C2H2 = 300 ppm.
FAQ: So, how to use the triangle ?
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 C2H2 = 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 algorithm available from me ([email protected]).
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 software packages are available for DGA interpretation using the triangle method
.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.
.
The most severe faults:
-faults D2 in paper and in oil (high-energy arcing)
-faults T2-T3 in paper (>300 °C)
-faults D1 in paper (tracking, arcing)
-faults T3 in oil (>700 °C)
The less severe faults:
-faults PD/ D1 in oil (sparking)
-faults T1 in paper (<300 °C)
-faults T2 in oil (<700 °C)
-are difficult to find by inspection
A popular ratio used to detect paper involvement 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.
.
-C2H2/ H2 : a ratio > 3 in the main tank indicates contamination by the LTC compartment
Other useful gas ratios:
-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)”: gassing of the T1 or T2 type.
-first limit is related to lab accuracy.
-second limit to economic reasons.
Minimum gas formation to attempt a diagnosis:
First limit: lab accuracy
The accuracy of the “average” CIGRE /IEC lab is ~ ± 15% at medium (routine) gas concentrations (> 10 ppm for hydrocarbons).
Its accuracy decreases to ~ ± 30% at 6 ppm, and ± 100% near the lab detection limit (2 ppm).
Effect of lab accuracies of 15 and 30% on DGA diagnosis uncertainty (in red and blue).
When an area of uncertainty crosses several fault zones in the triangle, a reliable diagnosis cannot be given.
This is particularly true for lab accuracies > 30%.
This applies not only to the triangle but to all diagnosis methods.
Diagnosis uncertainty corresponding to lab inaccuracies of ± 15, 30, 50 and 75 %:
How inaccurate are the laboratories at medium gas concentrations ?
How inaccurate areat low gas concentrations ?
Minimum gas concentrations to attempt a diagnosis.
If for example lab accuracy is ±15% at medium gas levels (>10 ppm):
If some gases are < 6 ppm, diagnoses will be uncertain, and a calculation of diagnosis uncertainty should be done.
Commercial software is available for that purpose.
If lab accuracy is between 15% and 30%, diagnoses will be uncertain at all gas concentrations, and a calculation of diagnosis uncertainty necessary.
Above 30% or 50%, diagnoses become too uncertain.
Lab and gas monitor accuracies can be obtained by using gas-in-oil standards.
Such standards are available commercially.
Second limit: typical values
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.
Also, there is always a small level of gases in service, and it would not be economically viable to suspect all pieces of equipment.
So, 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 consensus has been reached at CIGRE on typical values observed in service worldwide (CIGRE Brochure # 296, 2006).
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 individual loading conditions, equipment used, manufacturers, climate, etc.
Each individual network therefore should preferably calculate its own specific typical values.
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 ?).
-Typical values are not affected by oil volume (suggesting that larger faults are formed in larger transformers ?).
-Typical values are very similar in air-breathing and in sealed or nitrogen blanketed equipment, contrary to a common belief in the US.
90% typical values in California vs. CIGRE values, in ppm:
C2H2 H2 CH4 C2H4 C2H6 CO CO2
CIGRE/ IEC 2-20
50-150
30-130
60-280
20-90
400-600
3800-14000
California 3 96 88 57 79 613 5991
When DGA results in service reach typical values:
-a diagnosis may be attempted to identify the fault (if lab accuracy is good enough).
-the equipment should not be considered at risk.
-however, it should be monitored more frequently by DGA.
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 at HQ
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 concentration 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, and 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.
Pre-failure rates of gas increase (slope 3) are in preparation at CIGRE.
Concentration
Time
Pre-failure rates of gas increase in power transformers, in ppm/ day
C2H2 H2 CH4 C2H4 C2H6 CO CO2
0.5 3 5 5 11 NS NS
On-line gas monitors
-are best suited for measuring rates of gas increase (trends).
-will detect faults between regular oil samplings.
-may now also provide on-line diagnosis.
The triangle can also be used to identify faults in tap changers.
: Normal operation; :Severe coking; : Light coking; : “Heating”;: strong arcing D2; : Arcing D1
Thanks a lot for your attention.
An Artificial Neural Networks An Artificial Neural Networks Approach to Transformer Approach to Transformer
Dissolved Gas Analysis and Dissolved Gas Analysis and Problem NotificationProblem Notification
Donald LamontagneDonald LamontagneSection LeaderSection Leader
T&D Reliability Analysis and ManagementT&D Reliability Analysis and ManagementArizona Public ServiceArizona Public Service
EPRI Substation Equipment Diagnostic Conference XIVEPRI Substation Equipment Diagnostic Conference XIVMarriott Hotel and MarinaMarriott Hotel and Marina
San Diego, CASan Diego, CAJuly 17, 2006July 17, 2006
AgendaAgenda
EventsEventsOnOn--Line DGA MonitoringLine DGA MonitoringNeural NetworksNeural NetworksAPS TOAN SystemAPS TOAN SystemConclusionsConclusionsQuestions?Questions?
EventsEvents
WestwingWestwing
6/14/2004 and 7/4/2004 Events6/14/2004 and 7/4/2004 Events
6/14/20046/14/2004
Sustained fault on 230kV Westwing Sustained fault on 230kV Westwing ––Liberty lineLiberty lineOne breaker failed to openOne breaker failed to openInitial fault split between three banksInitial fault split between three banksCommunication error on breaker statusCommunication error on breaker statusLast fault through one bank onlyLast fault through one bank onlyPost event DGA and Post event DGA and thermographythermography
Damaged TransformersDamaged Transformers
Five 500MVA, Single Phase, Five 500MVA, Single Phase, 525/230/13.8kV Autotransformers w/ LTC525/230/13.8kV Autotransformers w/ LTCWestinghouse 1973 vintageWestinghouse 1973 vintage14,500 gals of oil in the main tank14,500 gals of oil in the main tank
Damaged Phases
7/5/2004
Deer ValleyDeer Valley
7/20/2004 7/20/2004 –– T928 Type U bushing failureT928 Type U bushing failure167MVA, three phase, 230/69kV167MVA, three phase, 230/69kVFPE 1978 vintageFPE 1978 vintageBushing was Bushing was DobleDoble tested in 2002 with no tested in 2002 with no issuesissues
Replacement T873Replacement T873
167MVA, three phase, 230/69kV167MVA, three phase, 230/69kVWestinghouse 1979 vintageWestinghouse 1979 vintageRemoved from service 5/2004 for upgrade Removed from service 5/2004 for upgrade to 188MVAto 188MVAReturned to service 7/25/2004 to replace Returned to service 7/25/2004 to replace failed T928failed T928
T873 DGA ResultsT873 DGA Results
002233339917172131213159261592616276273/26/20043/26/2004
2635263561761770704464463922392241418068066625266252273427343/28/20053/28/2005
0033363637371313545410151015463746377507508/18/20048/18/2004
C2H2C2H2C2H4C2H4C2H6C2H6CH4CH4H2H2COCOCO2CO2N2N2O2O2
All gases from the 8/18/2004 sample were below the All gases from the 8/18/2004 sample were below the IEEE C57.104 “Condition 1” levels IEEE C57.104 “Condition 1” levels –– indicating the indicating the transformer was behaving normally.transformer was behaving normally.The 3/28/2004 sample has H2, C2H4, C2H2 and TDCG The 3/28/2004 sample has H2, C2H4, C2H2 and TDCG at “Condition 4” and CH4 at “Condition 3.”at “Condition 4” and CH4 at “Condition 3.”
OnOn--Line DGA MonitoringLine DGA Monitoring
OnOn--Line DGA MonitoringLine DGA Monitoring
Began utilizing in the summer of 2003Began utilizing in the summer of 2003Currently using Serveron Currently using Serveron TrueGasTrueGas and TM8 and TM8 modelsmodelsContinuously sample eight gases (hydrogen, Continuously sample eight gases (hydrogen, acetylene, methane, ethane, ethylene, CO, COacetylene, methane, ethane, ethylene, CO, CO22, , OO22) and report every four hours through gas ) and report every four hours through gas chromatographychromatographyCurrently installed on fiftyCurrently installed on fifty--two 230kV and above two 230kV and above transformers and shunt reactors.transformers and shunt reactors.
Source: www.serveron.com
Laboratory Grade Gas Laboratory Grade Gas ChromatographyChromatography
11--3,000 3,000 ppmppm<2%<2%±5% or ±1 ±5% or ±1 ppmppmAcetylene C2H2Acetylene C2H2
55--5,000 5,000 ppmppm<1%<1%±5% or ±5 ±5% or ±5 ppmppmEthane C2H6Ethane C2H6
33--5,000 5,000 ppmppm<1%<1%±5% or ±3 ±5% or ±3 ppmppmEthylene C2H4Ethylene C2H4
55--30,000 30,000 ppmppm<1%<1%±5% or ±5 ±5% or ±5 ppmppmCarbon Dioxide Carbon Dioxide
CO2CO2
55--10,000 10,000 ppmppm<2%<2%±5% or ±5 ±5% or ±5 ppmppmCarbon Monoxide Carbon Monoxide COCO
55--7,000 7,000 ppmppm<1%<1%±5% or ±5 ±5% or ±5 ppmppmMethane CH4Methane CH4
3030--25,000 25,000 ppmppm<1%<1%±5% or +30/±5% or +30/--0 0
ppmppmOxygen O2Oxygen O2
33--3,000 3,000 ppmppm<2%<2%±5% or ±3 ±5% or ±3 ppmppmHydrogen H2Hydrogen H2
RangeRangeRepeatabilityRepeatabilityGas AccuracyGas Accuracy
Artificial Neural NetworksArtificial Neural Networks
Artificial Neural NetworksArtificial Neural Networks
A network of nodes and weighted A network of nodes and weighted connections, which are loosely analogous connections, which are loosely analogous to the neurons and synapses in the brain. to the neurons and synapses in the brain. Each node sums the inputs from several Each node sums the inputs from several incoming weighted connections and then incoming weighted connections and then applies a transfer function to the sum. applies a transfer function to the sum. The transfer function is a smooth, nonThe transfer function is a smooth, non--linear functionlinear function
logistic functionlogistic functionhyperbolic tangenthyperbolic tangent
∑
Neural NetworksNeural Networks
∑
∑ ∑
∑
∑
∑
InputInputLayerLayer
HiddenHiddenLayer 1Layer 1
HiddenHiddenLayer 2Layer 2
OutputOutputLayerLayer
ii22
ii11
iinn
Neural Network TrainingNeural Network Training
UnderfittingUnderfitting and and OverfittingOverfitting
xx
xx
x
x
xx xx xx
xx
x
x
xx xx xx
xx
x
x
xx xx
Underfitting Correct Fit Overfitting
APS TOANAPS TOAN(Transformer Oil Analysis and (Transformer Oil Analysis and
Notification)Notification)
Traditional AnalysisTraditional Analysis
Testing accuracy of traditional methodsTesting accuracy of traditional methods
32.4%32.4%24.8%24.8%42.9%42.9%IEC 599IEC 599
62.9%62.9%12.4%12.4%24.8%24.8%Rogers RatioRogers Ratio
11.9%11.9%65.2%65.2%22.9%22.9%DornenbergDornenberg RatioRatioNot IdentifiableNot IdentifiableErrorErrorSuccessSuccessDiagnosis MethodsDiagnosis Methods
APS TOANAPS TOAN
~ 114,000 DGA samples/year~ 114,000 DGA samples/yearUtilizes VT’s ANNEPS engine (w/ Utilizes VT’s ANNEPS engine (w/ modifications)modifications)
ANN combined with Expert SystemANN combined with Expert System
Tested at ~ 93% accuracy in predicting Tested at ~ 93% accuracy in predicting fault typefault typeException based processing systemException based processing system
APS TOANAPS TOAN
Some Modifications to Some Modifications to VTsVTs System:System:Gassing ratesGassing ratesNine vs. eight gasesNine vs. eight gasesMinimum gas levelsMinimum gas levelsAdded a Polling EngineAdded a Polling EngineAdded a Notification EngineAdded a Notification Engine
TOAN Provides AnswersTOAN Provides Answers
Who Who –– Transformer IDTransformer IDWhen When –– WhenWhen the sample was taken?the sample was taken?What What –– WhatWhat are the gas values and what are the gas values and what type of fault is it?type of fault is it?How How –– How severe is it?How severe is it?Where Where –– WhereWhere is the fault likely located?is the fault likely located?
SERVERONTaken By
FC3 U4 GSU SO. XFMR 345Y/199.186-22KV, 308MVA 1-PDescription
T629 (Four Corners 350KV) [ Level = 1 : IMMEDIATE ATTENTION ]Transformer
6/5/2006 2:58:09 PM6/5/2006 1:00:00 PM7410
0.1676/5/2006 5:58:25 PM6/5/2006 5:00:00 PM7412
DaysSample Received DateSample DateSample ID
Example ReportExample ReportWho and WhenWho and When
Gas in Oil
-0.0930.01.01.0TCG%
-52.800-20.33335.7++ 3315.4TDCG
-36.221-21.42797.8++ 2776.4THG
37.9241062.058284.859346.8N2
-3.017-58.210671.610613.4O2
0.26014.16681.3++ 6695.4CO2
-9.1130.6503.2++ 503.8CO
-0.896-1.2342.7++ 341.5Ethane
-21.445-13.01888.4++ 1875.4Ethylene
0.063-8.924.6++ 15.7Acetylene
-21.2591.7542.1++ 543.8Methane
-13.8060.534.735.2Hydrogen
Rate (ppm/day)Delta
Previous Sample
Current Sample
WhatWhat
Fault Analysis
0.8330.9900.833Cellulose Degradation - CD
1.0000.9901.000Overheating of Oil - OHO
1.0000.9901.000Overheating - OH
0.0000.0100.000Low Energy Discharge - LED
0.0000.0100.000High Energy Discharge - HEDA
0.0000.0100.000Normal - NR
CombinedEPSANN
WhatWhat
Duval Analysis
2434.977.00.622.3
Total Gas% C2H4% C2H2% CH4
T3 - Thermal fault > 700degCDuval Diagnosis
Diagnosis
Degradation of cellulose involved.CD Diagnosis
Overheating of oil involved.OHO Diagnosis
Possible overheating of oil or cellulose.OH Diagnosis
LED Diagnosis
HEDA Diagnosis
HEDA Severity
Est. temp is above 700 c degrees.OH Temperature
Unit is ABNORMALSimple Criteria
Sample oil daily. Consider removal of unit from service. Advise manufacturer.
Recommended Action
Overall condition needs IMMEDIATE ATTENTION.Recommended Condition
1Previous Result
1Final Recommendation
WhatWhat
LocationFault Location Confidence
0.0000.0000.0001.0000.001
OtherWindingsBushings/LeadsCore/TankLTC
1-core/tank1-core/tank
Previous Fault LocationFault Location
WhereWhere
ConclusionsConclusions
Met our goal to build an “exception based” Met our goal to build an “exception based” systemsystemAlthough accuracy is good (93%) APS is Although accuracy is good (93%) APS is researching and training improved researching and training improved ANNsANNsANNsANNs are capable of detecting the are capable of detecting the underlying, complex patterns of DGA and underlying, complex patterns of DGA and are a good partner with onare a good partner with on--line monitoringline monitoring
Questions?Questions?