Systems and methods for real-time advanced visualization for predicting the health, reliability and performance of an electrical power system

• US 8,170,856 B2
• Filed: 07/12/2007
• Issued: 05/01/2012
• Est. Priority Date: 04/12/2006
• Status: Active Grant

• Current Assignee: Power Analytics Corporation (PAC Global, Inc.)
• Original Assignee: Power Analytics Corporation (PAC Global, Inc.)
• Inventors: Nasle, Adib
• Primary Examiner(s): Rodriguez, Paul
• Assistant Examiner(s): Cothran, Bernard E
• Application Number:
  US11/777,121
• Publication Number:
  US 20080049013A1
• Time in Patent Office: 1,755 Days
• Field of Search: 714/47, 703/14, 706/18
• US Class Current: 703/14
• CPC Class Codes: G05B 23/0229 knowledge based, e.g. expert systems; genetic algorithms
• CPC Class Codes: H02J 13/00001 characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
• CPC Class Codes: H02J 13/00017 using optical fiber
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 41/22 comprising specially adapted graphical user interfaces [GUI]
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• CPC Class Codes: Y04S 10/40 Display of information, e.g. of data or controls
• CPC Class Codes: Y04S 40/00 Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
• CPC Class Codes: Y04S 40/124 using wired telecommunication networks or data transmission busses
• CPC Class Codes: Y04S 40/18 Network protocols supporting networked applications, e.g. including control of end-device applications over a network

Abstract

A system for real-time three-dimensional (3D) visualization of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine, a machine learning engine and a 3D visualization engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The machine learning engine stores and processes patterns observed from the real-time data output and the predicted data output to forecast an aspect of the electrical system. The 3D visualization engine renders the virtual system model and the forecasted aspect into a 3D visual model.

Claims

1. A system for real-time three-dimensional (3D) visualization of an electrical system, comprising:

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

a power analytics server communicatively connected to the data acquisition component, comprising

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

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

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 electrical system, and

a 3D visualization engine configured to render the virtual system model and the forecasted aspect into a 3D visual model of the electrical system; and

a client terminal communicatively connected to the power analytics server and configured to display the 3D visual model.

2. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 1, wherein, the machine learning engine includes an associative memory layer, a sensory layer, and a neocortical model.

3. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 1, wherein the virtual system model includes current system components and operational parameters comprising the electrical system.

4. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 1, wherein the forecasted aspect is a predicted ability of the electrical system to resist system output deviations from defined tolerance limits of the electrical system.

5. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 1, wherein the forecasted aspect is a predicted reliability and availability of the electrical system.

6. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 1, wherein the forecasted aspect is a predicted total power capacity of the electrical system.

7. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 6, wherein the forecasted aspect is a predicted ability of the electrical system to maintain availability of total power capacity.

8. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 6, wherein the forecasted aspect is a predicted utilization of the total power capacity of the electrical system.

9. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 1, wherein the forecasted aspect is a predicted ability of the electrical system to withstand a contingency event that results in stress to the electrical system.

10. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 9, wherein the contingency event relates to load shedding.

11. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 9, wherein the contingency event relates to load adding.

12. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 9, wherein the contingency event relates to loss of utility power supply to the electrical system.

13. The system for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 9, wherein the contingency event relates to a loss of distribution infrastructure associated with the electrical system.

14. A computer-implemented method for real-time three-dimensional (3D) visualization of an electrical system, where one or more processors are programmed to perform steps comprising:

acquiring real-time data from a sensor configured to acquire the real-time data from the electrical system;

generating predicted data output from the electrical system using the updated virtual system model;

monitoring the predicted data output for the electrical system generated using the virtual system model;

initiating a calibration and synchronization operation to update the virtual system model in real-time when a difference between the real-time data and the predicted data output exceeds a threshold;

storing and processing patterns observed from the real-time data output and the predicted data output using a machine learning engine;

forecasting an aspect of the electrical system using the machine learning engine; and

rendering the forecasted aspect into a 3D visual model of the electrical system using a 3D visualization engine.

15. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 14, wherein the forecasted aspect is a predicted ability of the electrical system to resist system output deviations from defined tolerance limits of the electrical system.

16. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 14, wherein the forecasted aspect is a predicted reliability and availability of the electrical system.

17. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 14, wherein the forecasted aspect is a predicted total power capacity of the electrical system.

18. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 14, wherein the forecasted aspect is a predicted ability of the electrical system to maintain availability of total power capacity.

19. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 14, wherein the forecasted aspect is a predicted utilization of the total power capacity of the electrical system.

20. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 14, wherein the forecasted aspect is a predicted ability of the electrical system to withstand a contingency event that results in stress to the electrical system.

21. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 20, wherein the contingency event relates to load shedding.

22. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 20, wherein the contingency event relates to load adding.

23. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 20, wherein the contingency event relates to loss of utility power supply to the electrical system.

24. The method for real-time three-dimensional (3D) visualization of an electrical system, as recited in claim 20, wherein the contingency event relates to a loss of distribution infrastructure associated with the electrical system.