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Luiz Cheim, Lan Lin - IEEE Fall Meeting - Milwaukee 10/23/2012 IEEE C57.104 Revision (Nov 2011) TF Database Analysis TF Database Analysis Luiz Cheim and.

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Presentation on theme: "Luiz Cheim, Lan Lin - IEEE Fall Meeting - Milwaukee 10/23/2012 IEEE C57.104 Revision (Nov 2011) TF Database Analysis TF Database Analysis Luiz Cheim and."— Presentation transcript:

1 Luiz Cheim, Lan Lin - IEEE Fall Meeting - Milwaukee 10/23/2012 IEEE C Revision (Nov 2011) TF Database Analysis TF Database Analysis Luiz Cheim and Lan Lin ABB Inc.

2 Building the Database + HQ = 521,700 records

3 Transformers Age Groups

4 Transformers Power Ratings

5 Transformers Voltage Classes

6 Transformers Oil Preservation Type

7 Reason for DGA

8 Percentiles of Hydrocarbons (all data) % ppm

9 Percentiles of CO,CO2 and TDCG (all data) % ppm

10 Percentiles of H2, C2H2 and CO vs. Age Groups % ppm

11 Percentiles of H2, C2H2 and CO vs. Voltage Class % ppm

12 Percentiles of H2, C2H2 and CO vs. Power Ratings % ppm

13 Percentiles of H2, C2H2 and CO vs. Source of Data % ppm

14 Percentiles of All Gases (Suspicious Units) % ppm

15 Percentiles of H2, C2H2 and CO vs. Power Ratings (Suspicious Units) % ppm

16 Percentiles of H2, C2H2 and CO vs. Voltage Class (Suspicious Units) % ppm

17 Percentiles of H2, C2H2 and CO vs. Oil Preservation % ppm

18 Annual Rate of Gas Formation (ppm/year) Percentiles of All Gases % ppm

19 After that… 1. HQ Data incorporated 2. Discussed unknown oil preservation system 3. Question of Rate of Gas Formation vs Levels

20 Montreal Meeting (May 2o12) Revisited Percentiles with Following Condition: O2/ (N2 + O2) 70,000 => N2 Blanket 5 – 15% Membrane/Rubber Bag > 15% Open Breather

21 Legend (next slides) IEEECondition 1 Limit CigreTypical Value (Brochure SCD1.32, 2010) AFMoArc Furnace, 90th Percentile (mineral oil) AFSiArc Furnace, 90th Percentile (Silicon oil)

22 H2 – All Data IEEE AFMo AFSi Cigre

23 CH4 – All Data IEEE AFMo AFSi Cigre

24 C2H2 – All Data IEEE AFMo AFSi Cigre

25 C2H4 – All Data IEEE AFMo AFSi Cigre

26 C2H6 – All Data IEEE AFMo AFSi Cigre

27 CO – All Data IEEE AFMo AFSi = 1936  Cigre

28 CO2 – All Data IEEE AFMo AFSi = 25,387  Cigre

29 TDCG – All Data IEEE AFMo AFSi = 2,160  Cigre

30 Further Breakdown… Given a type of oil preservation (say, N2 Blanket) What happens to Gas Levels vs Voltage Class, MVA, Age?

31 H2, 90th Percentile – Per Voltage Class IEEE AFMo AFSi Cigre

32 H2, 90 th Percentile – Per MVA Rating IEEE AFMo AFSi Cigre

33 H2, 90 th Percentile – Per Age Group IEEE AFMo AFSi Cigre

34 C2H6, 90th Percentile – Per Voltage Class Cigre

35 Revision C – TF on Data Analysis Gas Rate Subject 1. Should we calculate rates percentiles for all gases? 2. Should we associate rates to levels? How? 3. Cigre recent experience

36 Revision C – TF on Data Analysis Cigre Levels vs Sampling Intervals Cigre SCD1.32 Brochure, December 2010

37 Revision C – TF on Data Analysis Cigre Rates vs Sampling Intervals Cigre SCD1.32 Brochure, December 2010

38 Revision C – TF on Data Analysis Cigre SCD1.32 Brochure December 2010

39 Revision C – TF on Data Analysis Proposal Under Discussion – Level vs Rate Frequency of DGA

40 Revision C – TF on Data Analysis Proposal Under Discussion – Level vs Rate Severity of Fault (?)

41 Revision C – TF on Data Analysis Gas Rates (IEEE Database)

42 Revision C – TF on Data Analysis Gas Rates (IEEE Database)

43 Revision C – TF on Data Analysis Gas Rate Issues days

44 Revision C – TF on Data Analysis Gas Rate Issues days

45 Revision C – TF on Data Analysis Gas Rate Issues  ± 15% Cigre Typical Lab Accuracy 133 days

46 Revision C – TF on Data Analysis Gas Rate Issues days 68 ?

47 Revision C – TF on Data Analysis Gas Rate Issues

48 Revision C – TF on Data Analysis Another Example

49 Revision C – TF on Data Analysis Another Example 27 ppm/year 500 ppm/year

50 Revision C – TF on Data Analysis Inherent Uncertainty in Trend Calculation 1. Multiple Laboratories 2. Lab Variations (repeatability, reproducibility, accuracy) 3. Seasonal variations (temperature, etc) 4. Sampling errors (humans, sample contamination, etc) 5. Type of Transformer (N2, etc…) 6. Sampling interval??

51 Revision C – TF on Data Analysis Distribution of DGA Sampling Interval

52 Revision C – TF on Data Analysis Distribution of DGA Sampling Interval

53 Revision C – TF on Data Analysis Distribution of DGA Sampling Interval

54 Revision C – TF on Data Analysis Gas Rates Distribution vs DGA Sampling Interval

55 Revision C – TF on Data Analysis Gas Rates Distribution vs DGA Sampling Interval

56 Revision C – TF on Data Analysis Gas Rates Distribution vs DGA Sampling Interval

57 Revision C – TF on Data Analysis Gas Rates Distribution vs DGA Sampling Interval

58 Revision C – TF on Data Analysis Gas Rates Distribution vs DGA Sampling Interval

59 Revision C – TF on Data Analysis Gas Rates Distribution vs DGA Sampling Interval

60 Revision C – TF on Data Analysis Gas Rates Distribution vs DGA Sampling Interval 38%

61 Revision C – TF on Data Analysis Rates Distribution vs DGA Sampling Interval

62 Revision C – TF on Data Analysis

63 Revision C – TF on Data Analysis

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65

66

67 Food for Thought!

68 Revision C – TF on Data Analysis Proposal for Discussion – Level vs Rate Severity of Fault (N2 Blanket, etc) 90 th |  t 95 th |  t … Table conditioned to  t = Sampling Interval

69 Revision C – TF on Data Analysis Rate of Gas Increase vs Sampling Interval???

70 Revision C – TF on Data Analysis Rate of Gas Increase vs Sampling Interval???

71 Revision C – TF on Data Analysis Rate of Gas Increase vs Sampling Interval??? Food for Thought…

72


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