System and methods for intuitive modeling of complex networks in a digital environment

• US 9,846,752 B2
• Filed: 03/11/2016
• Issued: 12/19/2017
• Est. Priority Date: 02/14/2006
• Status: Active Grant

• Current Assignee: Bentley Systems Incorporated
• Original Assignee: Power Analytics Corporation (PAC Global, Inc.)
• Inventors: Nasle, Adib
• Primary Examiner(s): PIERRE LOUIS, ANDRE
• Application Number:
  US15/068,105
• Publication Number:
  US 20160196375A1
• Time in Patent Office: 648 Days
• Field of Search: 703 13, 703 18, 716109, 716120, 716127, 716133, 700286, 700290, 700291, 700292
• CPC Class Codes: G06F 17/10 Complex mathematical operations function generation by table look-up G06F1/03; evaluation of elementary functions by calculation G06F7/544
• 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

Abstract

Systems and methods for modeling an electrical power system are disclosed. A computer and an analytics server are in network connection. The computer comprises a processor coupled with a memory. The memory is configured to maintain at least one engine element and a component database. The analytics server comprises a virtual system modeling engine and an analytics engine. The component database is operable to store power system components. The at least one engine element is operable to generate a virtual system model of the electrical power system and generate predicted output based on the virtual system model. The analytics engine is operable to monitor the predicted output and real-time output from at least one sensor of the electrical power system, and calibrate the virtual system model based on a difference between the predicted output and the real-time output.

Claims

1. A system for modeling and managing an electrical power system, comprising:

a client terminal device and an analytics server in network connection;

wherein the client terminal device comprises a processor coupled with a memory;

wherein the memory is configured to maintain at least one engine element and a component database;

wherein the analytics server comprises a virtual system modeling engine and an analytics engine;

wherein the component database is configured to store power system components;

wherein the at least one engine element is configured to generate a virtual system model of the electrical power system and generate predicted output based on the virtual system model;

wherein the analytics engine is configured to monitor the predicted output and real-time output from at least one sensor of the electrical power system, and calibrate the virtual system model based on a difference between the predicted output and the real-time output;

wherein the analytics engine is further configured to calculate a real-time system security index value based on stability indices generated from the virtual system model once a disturbance event within the electrical power system has occurred, wherein the stability indices comprise an angular stability index, a frequency stability index, and a voltage stability index;

wherein the real-time system security index value reflects a real-time security and stability level of the electrical power system following the disturbance event;

wherein the client terminal device is operable to display the real-time system security index value once the disturbance event within the electrical system has occurred; and

a central analytics server configured to control an aspect of a monitored system, when its corresponding analytics server is out of operation, wherein the central analytics server is further configured to take over functionality of the analytics server and to modify operating parameters of one or more sensors that are interfaced with the monitored system.

2. The system of claim 1, further comprising an input device, wherein the input device is configured to select and position power system components within a framework.

3. The system of claim 2, wherein the at least one engine element comprises a component control engine, and wherein the component control engine is configured to receive the selection and position of power system components and interface the selected power system components within the framework.

4. The system of claim 2, wherein the at least one engine element comprises a power system topology modeling engine, and wherein the power system topology modeling engine is configured to render each of the selected power system components and render a topology of the electrical power system comprising the selected power system components.

5. The system of claim 4, wherein the virtual system model comprises virtual component data corresponding to the selected power system components.

6. The system of claim 4, wherein the power system topology modeling engine is further configured to suggest interface options for the selected power system components.

7. The system of claim 1, wherein the at least one engine element comprises a component configuration engine, and wherein the component configuration engine is configured to enable modifying configurations of the power system components stored in the component database.

8. The system of claim 1, wherein the analytics server further comprises a comparison engine, wherein the comparison engine is configured to continuously compare the predicted output and the real-time output.

9. The system of claim 1, wherein the analytics engine is configured to calibrate the virtual system model when the difference between the predicted output and the real-time output falls between a set value and an alarm condition value.

10. The system of claim 9, wherein the analytics engine is configured to generate an alarm message when the difference between the predicted output and the real-time output exceeds the alarm condition value.

11. A method for modeling and managing an electrical power system, comprising:

generating a virtual system model of the electrical power system;

generating predicted output based on the virtual system model;

monitoring real-time output from at least one sensor of the electrical power system;

calibrating the virtual system model based on a difference between the predicted output and the real-time output;

calculating a real-time system security index value based on stability indices data generated from the virtual system model once a disturbance event within the electrical power system has occurred, wherein the stability indices comprises an angular stability index, a frequency stability index, and a voltage stability index, wherein the real-time system security index value reflects a real-time security and stability level of the electrical power system following the disturbance event;

displaying the system security index value; and

controlling an aspect of a monitored system, using a central analytics server, when its corresponding analytics server is out of operation, wherein the central analytics server takes over functionality of analytics server and modifies operating parameters of one or more sensors that are interfaced with the monitored system.

12. The method of claim 11, further comprising selecting and positioning power system components within a framework.

13. The method of claim 12, further comprising receiving the selection and position of power system components and interfacing the selected power system components within the framework.

14. The method of claim 12, further comprising rendering each of the selected power system components and rendering a topology of the electrical power system comprising the selected power system components.

15. The method of claim 12, wherein the virtual system model comprises virtual component data corresponding to the selected power system components.

16. The method of claim 12, further comprising suggesting interface options for the selected power system component.

17. The method of claim 12, further comprising modifying a configuration of the selected power system component.

18. The method of claim 11, further comprising continuously comparing the predicted output and the real-time output.

19. The method of claim 11, further comprising calibrating the virtual system model when the difference between the predicted output and the real-time output falls between a set value and an alarm condition value.

20. The method of claim 19, further comprising generating an alarm message when the difference between the predicted output and the real-time output exceeds the alarm condition value.