Event analysis in an electric power system

1. A method comprising:

receiving, via a communication interface of an event detection and classification module comprising a processor, data from one or more sensors in a system, wherein:

the event detection and classification module includes a detection module and a classification module, and

the system is a power network and the one or more sensors are associated with a plurality of nodes in the power network;

determining an event occurred based on the received data;

applying a coherency similarity process to the received data via the classification module, wherein the coherency similarity process determines whether the received data is similar, within one of a threshold value and a range of values, to expected data for the event;

determining whether the event is an actual event or a mal-doer event based on an output of the classification module, further comprising

calculating an event singular value decomposition for the received data based on the application of the coherency process;

identifying a post-event right singular value based on the calculated post-event singular value decomposition;

comparing the post-event right singular value to a reference value for the same at least one pair of nodes to output a classification threshold value; and

determining whether the classification threshold value is one of inside or outside a predetermined value or range of values;

transmitting the determination of the event as the actual or the mal-doer event; and

modifying operation of the system based on the transmitted output.

2. The method of claim 1 , wherein the data is synchrophasor data collected from phasor measurement units or Phasor Data Concentrators.

3. The method of claim 2 , wherein the synchrophasor data includes at least one of voltage angle current angle, voltage magnitude, current magnitude, and active power.

4. The method of claim 1 , wherein the reference value is at least one of a synthetic right singular vector (RSV) and a historical RSV.

5. The method of claim 1 wherein the event singular value decomposition is based on a moving window data of an electrical signal.

6. The method of claim 5 , wherein a window size of the moving window of data is determined based on model analysis using at least one of a network admittance matrix, generator location and inertia, load location and magnitudes.

7. The method of claim 1 , wherein the coherency process outputs a right singular vector as a coherency value.

8. The method of claim 1 , wherein comparing the post-event right singular vector to the reference value is a measure of one of: rotation angle, Manhattan distance, Euclidean distance, or Chebyshev distance.

9. The method of claim 1 , wherein classification threshold value is updated based on at least one of: an output of the event classification module, a user input, learning from historical data.

10. A system comprising:

an event detection and classification module, including an event detection module and a classification module;

an event detection and classification processor; and

a memory storing program instructions which, when executed by the event detection and classification processor result in performance of functions as follows:

receive data from one or more sensors in a system via the event detection and classification module;

determine an event occurred based on the received data;

apply a coherency similarity process to the received data, via the classification module, wherein the coherency similarity process determines whether the received data is similar, within one of a threshold value and a range of values, to expected data for the event;

determine whether the event is an actual event or a mal-doer event based on an output of the classification module, wherein the determination comprises program instructions to perform the functions as follows:

calculate an event singular value decomposition for the received data based on the application of the coherency process;

identify a post-event right singular value based on the calculated post-event singular value decomposition;

compare the post-event right singular value to a reference value for the same at least one pair of nodes to output a classification threshold value; and

determine whether the classification threshold value is one of inside or outside a predetermined value or range of values;

transmit the determination of the event as the actual or the mal-doer event; and

modify operation of the system based on the transmitted output.

11. The system of claim 10 , wherein the data is synchrophasor data collected from phasor measurement units or Phasor Data Concentrators.

12. The system of claim 11 , wherein the synchrophasor data includes at least one of voltage angle current angle, voltage magnitude, current magnitude, and active power.

13. The system of claim 10 , wherein the reference value is at least one of a synthetic right singular vector (RSV) and a historical RSV.

14. The system of claim 10 , wherein the event singular value decomposition is based on a moving window data of an electrical signal.

15. A non-transitory computer-readable medium storing instructions that, when executed by a computer processor, cause the computer processor to perform a method comprising:

receiving, via a communication interface of an event detection and classification module comprising a processor, data from one or more sensors in a system, wherein:

the event detection and classification module includes a detection module and a classification module, and

the system is a power network and the one or more sensors are associated with a plurality of nodes in the power network;

determining an event occurred based on the received data;

applying a coherency similarity process to the received data via the classification module, wherein the coherency similarity process determines whether the received data is similar, within one of a threshold value and a range of values, to expected data for the event;

determining whether the event is an actual event or a mal-doer event based on an output of the classification module, wherein the determination further comprises:

calculating an event singular value decomposition for the received data based on the application of the coherency process;

identifying a post-event right singular value based on the calculated post-event singular value decomposition;

comparing the post-event right singular value to a reference value for the same at least one pair of nodes to output a classification threshold value; and

determining whether the classification threshold value is one of inside or outside a predetermined value or range of values;

transmitting the determination of the event as the actual or the mal-doer event; and

modifying operation of the system based on the transmitted output.