Probabilistic determination of transformer end of life

1. A method of generating an expected remaining lifetime of a transformer, comprising:

generating probabilistic models of factors that affect effective aging of the transformer;

generating a plurality of probabilistic profiles of the factors that affect effective aging of the transformer based on the probabilistic models;

generating a plurality of probabilistic hot spot profiles from the plurality of probabilistic profiles and hot spot temperature characteristics of the transformer;

simulating a plurality of future aging scenarios of the transformer based on the probabilistic hot spot profiles; and

estimating an expected remaining lifetime of the transformer from the plurality of future aging scenarios.

2. The method of claim 1 , wherein the plurality of probabilistic profiles are generated for a first time period, and wherein the future aging scenarios are generated over a second time period that is different from the first time period.

3. The method of claim 2 , wherein simulating the plurality of future aging scenarios comprises:

generating a plurality of aging profiles that simulate aging of the transformer over the first time period;

for each of the plurality of aging profiles, estimating an effective aging amount of the transformer to provide a plurality of effective aging amounts; and

summing the plurality of effective aging amounts to provide an estimated effective aging amount over the second time period.

4. The method of claim 3 , wherein the first time period comprises a 24-hour time period and the second time period comprises a one-year time period.

5. The method of claim 1 , wherein the factors affecting the effective aging of the transformer comprise load conditions, ambient temperature, moisture levels inside the transformer and/or oxygen levels inside the transformer.

6. The method of claim 1 , wherein simulating the plurality of future aging scenarios comprises performing a Monte Carlo simulation of future aging scenarios based on the plurality of probabilistic hot spot profiles.

7. The method of claim 1 , wherein generating probabilistic profiles of factors that affect the effective aging of the transformer comprises generating a plurality of ambient temperature profiles based on historical variations in ambient temperature.

8. The method of claim 7 , wherein the ambient temperature profiles describe expected ambient temperatures over a predetermined time period.

9. The method of claim 8 , further comprising generating the ambient temperature profiles based on probability distributions of ambient temperature at a plurality of intervals within the predetermined time period.

10. The method of claim 9 , wherein the probability distributions comprise uniform probability distributions.

11. The method of claim 9 , wherein the probability distributions comprise probability distributions generated based on actual ambient temperature data.

12. The method of claim 1 , wherein generating probabilistic profiles of factors that affect the effective aging of the transformer comprises generating a plurality of expected load profiles based on predicted loading of the transformer.

13. The method of claim 12 , wherein the expected load profiles describe expected loads over a predetermined time period.

14. The method of claim 13 , further comprising generating the expected load profiles based on probability distributions at a plurality of time intervals within the predetermined time period.

15. The method of claim 14 , wherein the probability distributions comprise uniform probability distributions.

16. The method of claim 14 , wherein the probability distributions comprise estimates of actual probability distributions of the expected load.

17. The method of claim 1 , wherein estimating future aging of the transformer from the plurality of future aging scenarios comprises generating a histogram of simulated future aging scenarios; and

generating a confidence interval of an expected remaining life of the transformer based on the histogram of simulated future aging scenarios and associated mean and standard deviation of a distribution of the simulated future aging scenarios.

18. The method of claim 17 , wherein the future aging scenarios comprise expected annual aging scenarios, the method further comprising generating an estimate of the expected remaining life of the transformer based on a nominal expected life of the transformer and the expected annual aging scenarios.

19. The method of claim 1 , further comprising:

collecting operational data representing factors that affect effective aging of the transformer during operation of the transformer; and

updating the probabilistic models of the factors that affect effective aging of the transformer.

20. The method of claim 19 , further comprising:

determining an effective current age of the transformer based on the operational data;

wherein the expected remaining life of the transformer is estimated from the plurality of future aging scenarios, from the effective current age of the transformer and a nominal expected life of the transformer.

21. The method of claim 1 , wherein the probabilistic models comprise probability distributions of the factors that affect aging of the transformer.

22. The method of claim 1 , wherein the factors that affect aging of the transformer comprise ambient temperature and load, and wherein the probabilistic models comprise uniform probability distributions.

23. The method of claim 1 , further comprising performing maintenance on the transformer and/or adjusting a load of the transformer based on the estimated future aging of the transformer.

24. A method of estimating an expected remaining life of a transformer based on probabilistic models of factors that affect aging of the transformer, the method comprising:

collecting operational data representing the factors that affect effective aging of the transformer during operation of the transformer;

updating the probabilistic models of the factors that affect effective aging of the transformer based on the operational data; and

determining an effective current age of the transformer based on the operational data;

wherein the expected remaining life of the transformer is estimated from a plurality of future aging scenarios generated based on the probabilistic factors, from the effective current age of the transformer and from a nominal expected life of the transformer.

25. The method of claim 24 , wherein collecting the operational data comprises collecting the operational data from a sensor in the transformer.

26. The method of claim 24 , wherein the factors affecting the effective aging of the transformer comprise load conditions, ambient temperature, moisture levels inside the transformer and/or oxygen levels inside the transformer.

27. A device for estimating future aging of a transformer, comprising:

a processing circuit; and

a memory coupled to the processing circuit, wherein the memory stores computer program instructions that, when executed by the processing circuit, cause the device to perform operations comprising:

generating probabilistic models of factors that affect effective aging of the transformer;

generating a plurality of probabilistic profiles of the factors that affect effective aging of the transformer over a first time period based on the probabilistic models;

generating expected hot spot profiles from the probabilistic profiles and hot spot temperature characteristics of the transformer;

simulating a plurality of future aging scenarios of the transformer based on the expected hot spot profiles over a second time period; and

estimating future aging of the transformer from the plurality of future aging scenarios.

28. The device of claim 27 , wherein the factors affecting the effective aging of the transformer comprise load conditions, ambient temperature, moisture levels inside the transformer and/or oxygen levels inside the transformer.