Systems and methods for predictive monitoring including real-time strength and security analysis in an electrical power distribution system

• US 7,840,395 B2
• Filed: 04/12/2007
• Issued: 11/23/2010
• Est. Priority Date: 03/10/2006
• Status: Expired due to Fees

• Current Assignee: Power Analytics Corporation (PAC Global, Inc.)
• Original Assignee: EDSA Micro Corporation (PAC Global, Inc.)
• Inventors: Nasle, Adib, Nasle, Ali
• Primary Examiner(s): Shah; Kamini S
• Assistant Examiner(s): Calle; Angel J
• Application Number:
  US11/734,706
• Publication Number:
  US 20070286089A1
• Time in Patent Office: 1,321 Days
• Field of Search: 703/2, 703/13, 703/18, 702/57, 702/64, 702/182, 361/1, 361/42, 361/91.1, 361/93.1
• US Class Current: 703/18
• CPC Class Codes: G06F 2111/02 CAD in a network environment, e.g. collaborative CAD or distributed simulation
• CPC Class Codes: G06F 2119/06 Power analysis or power optimisation
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

A system for performing real-time failure mode analysis of a monitored system is disclosed. The system includes a data acquisition component, an analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the monitored system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and a machine learning engine.

Claims

1. A system for performing real-time failure mode analysis of a monitored system, comprising:

a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the monitored system;

an analytics server communicatively connected to the data acquisition component, comprising,

a virtual system modeling engine configured to generate predicted data output for the monitored system utilizing a virtual system model of the monitored system,

an analytics engine configured to monitor the real-time data output and the predicted data output of the monitored system, the analytics engine further configured to initiate a calibration and synchronization operation to update the virtual system model when a difference between the real-time data output and the predicted data output exceeds a threshold, and

a machine learning engine configured to store and process patterns observed from the real-time data output and the predicted data output, the machine learning engine further configured to forecast an aspect of the monitored system subjected to a simulated contingency event; and

a client terminal communicatively connected to the analytics server, the client terminal configured to allow for the selection of the simulated contingency event and display the forecasted aspect.

2. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 1, wherein the monitored system is an electrical system.

3. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 1, wherein the machine learning engine is comprised of:

an associative memory layer;

a sensory layer; and

a neocortical model.

4. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 1, wherein the virtual system model includes current system components and operational parameters comprising the monitored system.

5. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 2, wherein the current system components are comprised of static components and rotating components.

6. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 1, wherein the aspect is a predicted operational stability of the monitored system as influenced by the simulated contingency event.

7. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 6, wherein operational stability is a measure of the monitored system'"'"'s ability to maintain stability and recover from the contingency event without violating operational constraints of the monitored system.

8. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 1, wherein the simulated contingency event is an arc flash incident that occurs within the monitored system.

9. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 8, wherein the aspect is a level of personal protective equipment required to maintain the monitored system.

10. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 8, wherein the aspect is a quantity of energy released by the arc flash event.

11. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 8, wherein the aspect is an arc flash safety boundary area around components comprising the monitored system.

12. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 1, wherein the aspect is a predicted operational reliability of the monitored system as influenced by the contingency event.

13. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 12, wherein the predicted operational reliability of the monitored system is a measure of the monitored system'"'"'s susceptibility to load interruptions.

14. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 12, wherein the predicted operational reliability of the monitored system is a measure of the monitored system'"'"'s operational repair costs.

15. The system for performing real-time failure mode analysis of a monitored system, as recited in claim 12, wherein the predicted operational reliability of the monitored system is a measure of the monitored system'"'"'s failure rates.

16. A method for determining in real-time the operational stability of an electrical system subjected to a contingency event, comprising:

monitoring real time data and predicted data for the electrical system, the predicted data being generated using a virtual system model of the electrical system;

updating the virtual system model of the electrical system in response to real-time data, wherein updating the virtual system model further comprises initiating a calibration and synchronization operation to update the virtual system model when a difference between the real-time data and the predicted data exceeds a threshold, and wherein the virtual system model includes real-time domain model data for components comprising the electrical system;

choosing the contingency event to simulate;

determining the operational stability of the electrical system by running an analysis of the updated virtual system model operating under conditions simulating the contingency event chosen; and

generating a report that forecasts the operational stability of the electrical system subjected to the chosen contingency event.

17. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the electrical system is an electrical system.

18. The method for determining in real-time the operational stability of a electrical system subjected to a contingency event, as recited in claim 16, wherein the contingency event relates to execution of a start-up sequence for a component of the electrical system.

19. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 18, wherein the component is one of a motor or a generator.

20. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the contingency event relates to load shedding.

21. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the contingency event relates to critical clearing time of a tripped circuit breaker within the electrical system.

22. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the contingency event relates to a change in protective device operations and interactions.

23. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the contingency event relates to loss of utility power supply to the electrical system.

24. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the contingency event relates to loss of a generator in the electrical system.

25. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the contingency event relates to a loss of distribution infrastructure associated with the electrical system.

26. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes a forecast of the electrical system'"'"'s ability to maintain sufficient active and reactive power reserves to cope with the contingency event.

27. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes a forecast of the electrical system'"'"'s ability to operate safely after the contingency event.

28. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes a forecast of the electrical system'"'"'s ability to operate reliably after the contingency event.

29. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 28, wherein the electrical system'"'"'s operational reliability is measured as a system reliability index rating.

30. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes a forecast of the electrical system'"'"'s ability to continue to operate with minimum operating cost after the contingency event.

31. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes a forecast of the electrical system'"'"'s ability to provide an acceptably high level of power quality after the contingency event.

32. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 31, wherein the level of power quality is measured by the electrical system'"'"'s ability to maintain voltage and frequency within a tolerance.

33. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes an identification of system bottlenecks within the electrical system.

34. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the real-time domain model data includes built-in dynamic model data of components that comprise the electrical system.

35. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the real-time domain model data includes user-defined dynamic modeling data of components that comprise the electrical system.

36. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the virtual system model is updated to reflect real-time weather conditions impacting the electrical system.

37. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes a forecast of the electrical system'"'"'s operational stability under real-time weather conditions.

38. The method for determining in real-time the operational stability of an electrical system subjected to a contingency event, as recited in claim 16, wherein the report includes a forecast of the electrical system'"'"'s ability to recover from a contingency event without violating operational constraints of the electrical system.

39. A method for making real-time predictions about an alternating current arc flash event generated by a protective device interfaced with an electrical system, comprising:

monitoring real time data and predicted data for the electrical system, the predicted data being generated using a virtual system model of the electrical system;

updating the virtual system model of the electrical system in response to the real-time data, wherein updating the virtual system model further comprises initiating a calibration and synchronization operation to update the virtual system model when a difference between the real-time data and the predicted data exceeds a threshold;

simulating the arc flash event using the virtual system model;

calculating a quantity of energy released by the arc flash event using results from the simulation; and

generating a report that summarizes results of the simulation.

40. The method for making real-time predictions about an alternating current arc flash event generated by a protective device interfaced with an electrical system, as recited in claim 39, wherein the electrical system is an electrical system.

41. The method for making real-time predictions about an alternating current arc flash event generated by a protective device interfaced with an electrical system, as recited in claim 39, wherein the calculation of the quantity of energy released further includes:

determining bolted fault current values for the electrical system;

applying standardized equations to calculate a first arcing current value;

calculating a second arcing current value for the protective device using a ratio of the first arcing current value to the bolted fault current value;

performing a time-current curve analysis to determine a fault clearing time for the protective device; and

calculating the quantity of energy released by the protective device.

42. The method for making real-time predictions about an alternating current arc flash event generated by a protective device interfaced with an electrical system, as recited in claim 39, further including:

determining an arc flash protection boundary around the protective device.

43. The method for making real-time predictions about an alternating current arc flash event generated by a protective device interfaced with an electrical system, as recited in claim 42, wherein the report specifies an arc flash protection boundary around the protective device.

44. The method for making real-time predictions about an alternating current arc flash event generated by a protective device interfaced with an electrical system, as recited in claim 39, further including:

determining a level of required personal protective equipment (PPE) for personnel maintaining the protective device.

45. The method for providing real-time predictions of alternating current arc flash events generated by an electrical system, as recited in claim 44, wherein the report specifies a level of required personal protective equipment (PPE) for personnel maintaining the protective device.

46. A method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, comprising:

monitoring real time data and predicted data for the electrical system, the predicted data being generated using a virtual system model of the electrical system;

updating the virtual system model of the electrical system in response to the real-time data, wherein updating the virtual system model further comprises initiating a calibration and synchronization operation to update the virtual system model when a difference between the real-time data and the predicted data exceeds a threshold;

receiving real-time system reliability data for the electrical system;

choosing the contingency event to simulate;

determining the operational reliability of the electrical system by running an analysis of the updated virtual system model operating under conditions simulating the contingency event chosen; and

generating a report that forecasts the operational reliability of the electrical system subjected to the chosen contingency event.

47. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the electrical system is an electrical power system.

48. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein operational reliability is a function of the failure rates associated with components that comprise the electrical system.

49. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein operational reliability is a function of the repair rates associated with components that comprise the electrical system.

50. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein operational reliability is a function of the required availability of components that comprise the electrical system.

51. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the real-time system reliability data is reflective of real-time weather conditions impacting the electrical system.

52. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the contingency event relates to loss of utility power supply for the electrical system.

53. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the contingency event relates to loss of a generator in the electrical system.

54. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the contingency event relates to a loss of distribution infrastructure associated with the electrical system.

55. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the report includes a forecast of the electrical system'"'"'s susceptibility to load interruptions due to the contingency event.

56. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the report includes a forecast of the electrical system'"'"'s susceptibility to increased operational costs due to the contingency event.

57. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 46, wherein the report includes a forecast of system unavailability due to the contingency event.

58. The method for determining in real-time the operational reliability of an electrical system subjected to a contingency event, as recited in claim 57, wherein system unavailability is a function of time duration that the system remains offline.