Systems and methods for classifying power line events

• US 10,422,833 B2
• Filed: 06/07/2011
• Issued: 09/24/2019
• Est. Priority Date: 06/07/2010
• Status: Active Grant

• Current Assignee: ABB Schweiz AG (ABB Limited)
• Original Assignee: ABB Research Ltd. (ABB Limited)
• Inventors: Saarinen, Kari, Mousavi, Mirrasoul, Stoupis, James, McGowan, John
• Primary Examiner(s): Islam, Mohammad K
• Application Number:
  US13/155,236
• Publication Number:
  US 20120010830A1
• Time in Patent Office: 3,031 Days
• Field of Search: 702 58
• CPC Class Codes: G01R 11/25 Arrangements for indicating or signalling faults
• CPC Class Codes: G01R 31/086 in power transmission or distribution networks, i.e. with interconnected conductors
• CPC Class Codes: G01R 31/3274 Details related to measuring, e.g. sensing, displaying or computing; Measuring of variables related to the contact pieces, e.g. wear, position or resistance measuring contact resistance G01R27/205
• CPC Class Codes: G01R 31/58 Testing of lines, cables or conductors testing of electric windings G01R31/72
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/52 Outage or fault management, e.g. fault detection or location

Abstract

Systems and methods for classifying power line events are disclosed. Classifying power line events may include receiving measured data corresponding to a signal measured on a power line, such as proximate a substation bus or along the power line, determining from the measured data that the power line event has occurred, extracting at least one event feature from the measured data, and determining at least partially from the at least one event feature at least one probable classification for the power line event. The systems may include an Intelligent Electronic Device (IED) connected to the power line and a processor linked to the IED.

Claims

1. A computer implemented method for classifying a power line event on a power transmission or distribution system, the method comprising:

measuring, by an Intelligent Electronic Device (IED) connected to a power line of the power transmission or distribution system, first, second and third signals on the power line associated with first, second and third phases of a three phase system, respectively;

sending, by the IED, measured data corresponding to the first, second and third signals measured on the power line to at least one computer processor of a substation of the power transmission or distribution system;

receiving from the at least one computer processor at least one probable classification for the power line event, wherein the at least one computer processor is configured to;

determine from the measured data that the power line event has occurred and been cleared;

estimate from the measured data an estimated residual fault data;

estimate, using the estimated residual fault data, one or more characteristics of one or more fault clearing devices of the power line that responded to the power line event;

apply a transformation to the measured data associated with the first, second and third phases to generate a single complex signal;

isolate from the measured data transient data corresponding to the power line event based on the single complex signal generated by the transformation;

calculate at least one event feature from the isolated transient data;

project the at least one event feature onto a lower dimensional component space to obtain a feature vector for the power line event; and

determine from the feature vector the at least one probable classification for the power line event.

2. The computer implemented method of claim 1, wherein the first, second and third signals are currents associated with first, second and third phases along the power line measured proximate a substation bus.

3. The computer implemented method of claim 1, wherein the at least one computer processor being configured apply a transformation to the measured data associated with the first, second and third phases to generate a complex signal comprises the at least one computer processor being configured to apply Park'"'"'s transformation to the measured data.

4. The computer implemented method of claim 1, wherein the measured data is received from the IED, and the at least one computer processor is configured to:

define at least two monitoring zones for the IED; and

identify from the isolated transient data a probable one of the monitoring zones in which the power line event occurred.

5. The computer implemented method of claim 1, wherein the power line event is a fault that occurred in at least one phase and was cleared, and the at least one computer processor is configured to:

subtract reference data from the measured data to estimate the estimated residual fault data, and wherein the one or more characteristics of the one or more fault clearing devices includes at least a range of device sizes for the one or more fault clearing devices.

6. The computer implemented method of claim 5, wherein the at least one computer processor is configured to identify from the measured data a most probable monitoring zone in which the fault occurred.

7. The computer implemented method of claim 1, wherein the at least one computer processor being configured to determine the at least one probable classification for the power line event comprises the at least one computer processor being configured to:

identify a plurality of event classification groups; and

determine for each one of the plurality of event classification groups a probability that the power line event belongs to the one of the plurality of event classification groups.

8. The computer implemented method of claim 1, wherein the at least one computer processor is configured to:

identify a plurality of event classification groups;

calculate for the power line event a distance measure for each one of the plurality of event classification groups; and

determine a most probable classification for the power line event, wherein the most probable classification corresponds to an identified one of the plurality of event classification groups for which the distance measure is the smallest.

9. The computer implemented method of claim 8, wherein the at least one computer processor is configured to:

acquire at least two classification threshold parameters based on the identified plurality of event classification groups;

indicate that the most probable classification has relatively high probability of being a correct classification for the power line event when the smallest distance measure is less than a first one of the at least two classification threshold parameters; and

indicate that the most probable classification is not the correct classification for the power line event when the smallest distance measure is greater than a second one of the at least two classification threshold parameters.

10. The computer implemented method of claim 1, wherein the at least one computer processor being configured to determine the at least one probable classification for the power line event comprises the at least one computer processor being configured to:

identify a plurality of event classification groups;

calculate for the power line event a Mahalanobis distance for each one of the plurality of event classification groups;

identify a smallest one of the calculated Mahalanobis distances; and

determine that none of the plurality of event classification groups correspond to the probable classification for the power line event if the smallest one of the calculated Mahalanobis distances is larger than a predetermined threshold.

11. The computer implemented method of claim 1, wherein the at least one computer processor is configured to:

retrieve tunable parameters for a plurality of power line events; and

wherein;

the at least one computer processor being configured to calculate the at least one event feature from the isolated transient data comprises the at least one computer processor being configured to calculate a spectrum for the isolated transient data; and

the at least one computer processor being configured to project the at least one event feature onto the relatively lower dimensional component space to obtain the feature vector for the power line event comprises the at least one computer processor being configured to project the spectrum onto the relatively lower dimensional component space to obtain the feature vector for the power line event.

12. The computer implemented method of claim 11, wherein the at least one computer processor is configured to:

scale the isolated transient data, wherein the spectrum is calculated from the scaled transient data; and

subtract a mean spectrum from the spectrum calculated for the scaled transient data to obtain a mean-centered spectrum, wherein the at least one computer processor being configured to project the spectrum onto the relatively lower dimensional component space to obtain the feature vector for the power line event comprises the at least one computer processor being configured to project the mean-centered spectrum onto the relatively lower dimensional component space to obtain the feature vector for the power line event.

13. The computer implemented method of claim 11, wherein the power line is a distribution feeder and the power line event is a distribution feeder event.

14. The computer implemented method of claim 1, wherein the at least one computer processor is configured to estimate a probability that the determined at least one probable classification is correct.

15. The system of claim 1, wherein the at least one computer processor configured to project the at least one event feature onto a relatively lower dimensional component space to obtain a feature vector for the power line event comprises at least one computer processor configured to mean center and project the at least one event feature onto a relatively lower dimensional component space to obtain a feature vector for the power line event.

16. The computer implemented method of claim 1, wherein the at least one computer processor configured to isolate from the measured data transient data corresponding to the power line event based on the complex signal generated by the transformation comprises at least one computer processor configured to isolate from the measured data transient data corresponding to the power line event based on a magnitude of the complex signal generated by the transformation.

17. The computer implemented method of claim 1, wherein the one or more characteristics includes at least a range of device sizes for the one or more fault clearing devices, and wherein the at least one computer processor is further configured to:

evaluate an operating point of the one or more fault clearing devices to one or more Time-Current Characteristics (TCC) curves associated with the one or more fault clearing devices to determine a candidate device size of the one or more fault clear devices.

18. The computer implemented method of claim 17, wherein the one or more fault clearing devices includes one or more of:

a fuse, a switch, a circuit breaker, or a recloser, and wherein the candidate device size corresponds to a device size for which the one or more TCC curves associated with the one or more fault clearing devices is closest to the operating point of the one or more fault clearing devices.

19. The computer implemented method of claim 17, wherein the evaluation of the operating point of the one or more fault clearing devices to the one or more TCC curves associated with the one or more fault clearing devices includes determining a region from a plurality of regions that the operating point of the one or more fault clearing devices falls within, and wherein each of the plurality of regions corresponds to different ranges of estimated clearing times.

20. The computer implemented method of claim 17, wherein the one or more TCC curves associated with the one or more fault clearing devices includes minimum melt time (MMT) curves and maximum clearing time (MCT) curves.

21. A system for classifying a power line event on a power transmission or distribution system, the system comprising:

an Intelligent Electronic Device (IED) connected to a power line of the power transmission or distribution system and configured to measure first, second and third signals on the power line associated with first, second and third phases of a three phase system, respectively;

one or more fault clearing devices of the power line configured to respond to the power line event on the power transmission or distribution system; and

a substation of the power transmission or distribution system in electrical communication with the TED, the substation comprising a processor configured to execute instructions to perform a method, the instructions comprising instructions to;

determine from the measured signals that the power line event has occurred and been cleared in at least one phase;

estimate from the measured data an estimated fault data;

estimate, using the estimated fault data, one or more characteristics of one or more fault clearing devices that responded to the power line event;

apply a transformation to the measured first, second and third signals to generate a single complex signal;

isolate from the measured signals a transient signal corresponding to the power line event based on the single complex signal generated by the transformation;

calculate at least one event feature from the isolated transient signal;

project the at least one event feature onto a lower dimensional component space to obtain a feature vector for the power line event; and

determine from the feature vector at least one probable classification for the power line event.

22. The system of claim 21, wherein at least two monitoring zones are defined for an TED, and the instructions comprise instructions to identify from the isolated transient signal a most probable one of the monitoring zones in which the power line event occurred.

23. The system of claim 21, wherein the power line event is a fault in the at least one phase that was cleared, and the instructions comprise instructions to:

subtract a reference signal from the measured signals to estimate the estimated residual fault signal, and wherein the one or more characteristics of the one or more fault clearing devices includes at least a range of device sizes for the one or more fault clearing devices.

24. The system of claim 23, wherein the instructions comprise instructions to identify from the measured signals a probable monitoring zone in which the fault occurred.

25. The system of claim 21, wherein the instructions to determine at least one probable classification for the power line event comprise instructions to:

identify a plurality of event classification groups;

calculate for the power line event a distance measure for each one of the plurality of event classification groups;

identify one of the plurality of event classification groups for which the distance measure is the smallest; and

determine that the identified one of the plurality of event classification groups provides a most probable classification for the power line event when the smallest distance measure is less than a predetermined threshold.

26. The system of claim 21, wherein the instructions comprise instructions to estimate a probability that the determined at least one probable classification is correct.

27. A system for classifying a power line event on a power transmission or distribution system, the system comprising:

one or more fault clearing devices of a power line of the power transmission or distribution system, the one or more fault clearing devices configured to respond to the power line event;

a non-transitory computer readable storage medium of a substation of the power transmission or distribution system having embodied thereon a plurality of machine-readable instructions that when executed by at least one computer processor of the substation of the power transmission or distribution system cause the at least one computer processor to classify a power line event, the plurality of machine-readable instructions comprising instructions to;

measure first, second and third signals on the power line proximate a substation bus associated with first, second and third phases of a three phase system, respectively, wherein the first, second and third signals are measured by an Intelligent Electronic Device (IED) connected to the power line of the power transmission or distribution system and in electrical communication with the substation;

receive measured data corresponding to the first, second and third phases measured on the power line proximate the substation bus;

estimate from the measured data an estimated residual fault data;

estimate, using the estimated residual fault data, one or more characteristics of one or more fault clearing devices that responded to the power line event;

determine from the measured data that the power line event has occurred in at least one phase;

apply a transformation to the measured data associated with the first, second and third phases to generate a single complex signal;

isolate from the measured data transient data corresponding to the power line event based on the single complex signal generated by the transformation;

calculate at least one event feature from the isolated transient data;

project the at least one event feature onto a lower dimensional component space to obtain a feature vector for the power line event; and

determine from the feature vector at least one probable classification for the power line event.

28. The system of claim 27, wherein the instructions to determine at least one probable classification for the power line event comprise instructions to:

identify a plurality of event classification groups;

calculate for the power line event a distance measure for each one of the plurality of event classification groups;

identify one of the plurality of event classification groups for which the distance measure is smallest; and

determine that the identified one of the plurality of event classification groups corresponds to a most probable classification for the power line event if the smallest distance measure is below a predetermined threshold.

29. The system of claim 27, wherein the power line event is a fault in the at least one phase that was cleared, and the instructions comprise instructions to:

subtract reference data from the measured data to estimate the estimated residual fault data, and wherein the one or more characteristics of the one or more fault clearing devices includes at least a range of device sizes for the one or more fault clearing devices; and

identify from the measured data a most probable monitoring zone in which the fault occurred.

30. The system of claim 27, wherein the measured data is received from the IED, at least two monitoring zones are defined for the IED, and the instructions comprise instructions to identify from the isolated transient data a probable one of the monitoring zones in which the power line event occurred.

31. The system of claim 27, comprising instructions to estimate a probability that the determined at least one probable classification is correct.