IP Library Granted Patent US 8,170,856
Granted Patent B2
US 8,170,856 · App. 11/777,121 · Granted May 1, 2012

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

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Quick Facts
Patent No.
US 8,170,856
App. No.
11/777,121
Granted
May 1, 2012
Kind
B2
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 (38)

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.

Assignments (6)
RELEASE OF SECURITY INTEREST Recorded Jul 28, 2017
From: PACIFIC WESTERN BANK
To: POWER ANALYTICS CORPORATION
Reel/Frame 043133/0976 →
SECURITY INTEREST Recorded Sep 21, 2016
From: POWER ANALYTICS CORPORATION
To: PACIFIC WESTERN BANK
Reel/Frame 039820/0257 →
RELEASE OF SECURITY INTEREST Recorded Aug 27, 2014
From: DP THREE LLC
To: POWER ANALYTICS CORPORATION
Reel/Frame 033645/0715 →
CHANGE OF NAME Recorded Feb 1, 2012
From: EDSA MICRO CORPORATION
To: POWER ANALYTICS CORPORATION
Reel/Frame 027649/0941 →
SECURITY INTEREST Recorded Aug 13, 2010
From: EDSA MICRO CORPORATION
To: DP THREE LLC
Reel/Frame 024823/0959 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 27, 2007
From: NASLE, ADIB
To: EDSA MICRO CORPORATION
Reel/Frame 019888/0046 →