IP Library Granted Patent US 9,292,794
Granted Patent B2
US 9,292,794 · App. 13/967,603 · Granted Mar 22, 2016

Voltage-based clustering to infer connectivity information in smart grids

Inventors: Vijay Arya (Bangalore, IN); Rajendu Mitra (Bangalore, IN)
Assignee: International Business Machines Corporation
G06N5/04G06N99/005
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 9,292,794
App. No.
13/967,603
Granted
Mar 22, 2016
Kind
B2
Abstract

Techniques, systems, and articles of manufacture for voltage-based clustering to infer connectivity information in smart grids. A method includes clustering multiple voltage time series measurements into one or more groups, wherein said multiple voltage time series measurements are derived from one or more sensors; determining a connectivity model based on the one or more groups; comparing the determined connectivity model to an existing connectivity model to detect one or more inconsistencies between the determined connectivity model and the existing connectivity model; and updating the existing connectivity model based on said one or more detected inconsistencies.

Claims (51)

1. A method comprising:

clustering multiple voltage time series measurements into multiple groups based on one or more distance metrics comprising at least (i) a distance metric that associates each of multiple voltage time series measurements with one of multiple sub-circuits, and (ii) a distance metric pertaining to distance between each of the voltage time series measurements that are associated with the same one of the multiple sub-circuits, wherein said multiple voltage time series measurements are derived from one or more sensors;

determining a connectivity model of the multiple groups, wherein said determining comprises inferring multiple connectivity relationships based on said clustering;

comparing the determined connectivity model to an existing connectivity model to detect one or more inconsistencies between the determined connectivity model and the existing connectivity model; and

updating the existing connectivity model based on said one or more detected inconsistencies;

wherein at least one of the steps is carried out by a computing device.

2. The method of claim 1 , wherein said one or more sensors comprise a set of multiple customer-associated meters.

3. The method of claim 1 , wherein said one or more sensors comprise a set of multiple smart plugs on customer premises.

4. The method of claim 1 , wherein said one or more sensors comprise a set of transformer meters.

5. The method of claim 1 , wherein said one or more sensors comprise a set of feeder meters.

6. The method of claim 1 , wherein said one or more sensors comprise a set of supervisory control and data acquisition devices.

7. The method of claim 1 , comprising:

generating a corrected version of the determined connectivity model and/or a corrected version of the existing connectivity model incorporating the one or more detected inconsistencies.

8. The method of claim 1 , wherein said clustering comprises clustering the multiple voltage time series measurements further based on one or more common phase associations.

9. The method of claim 1 , wherein said clustering comprises clustering the multiple voltage time series measurements further based on one or more clustering algorithms.

10. The method of claim 1 , wherein said clustering comprises clustering the multiple voltage time series measurements further based on one or more common circuit associations.

11. The method of claim 1 , wherein said connectivity model comprises information pertaining to how one or more customers and one or more assets are interconnected together in a network.

12. The method of claim 1 , wherein said comparing comprises comparing the determined connectivity model to the existing connectivity model to reconfirm the existing connectivity model after an outage and/or one or more restoration activities.

13. An article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising:

clustering multiple voltage time series measurements into multiple groups based on one or more distance metrics comprising at least (i) a distance metric that associates each of multiple voltage time series measurements with one of multiple sub-circuits, and (ii) a distance metric pertaining to distance between each of the voltage time series measurements that are associated with the same one of the multiple sub-circuits, wherein said multiple voltage time series measurements are derived from one or more sensors;

determining a connectivity model of the multiple groups, wherein said determining comprises inferring multiple connectivity relationships based on said clustering;

comparing the determined connectivity model to an existing connectivity model to detect one or more inconsistencies between the determined connectivity model and the existing connectivity model; and

updating the existing connectivity model based on said one or more detected inconsistencies.

14. A system comprising:

a memory; and

at least one processor coupled to the memory and configured for:

clustering multiple voltage time series measurements into multiple groups based on one or more distance metrics comprising at least (i) a distance metric that associates each of multiple voltage time series measurements with one of multiple sub-circuits, and (ii) a distance metric pertaining to distance between each of the voltage time series measurements that are associated with the same one of the multiple sub-circuits, wherein said multiple voltage time series measurements are derived from one or more sensors;

determining a connectivity model of the multiple groups, wherein said determining comprises inferring multiple connectivity relationships based on said clustering;

comparing the determined connectivity model to an existing connectivity model to detect one or more inconsistencies between the determined connectivity model and the existing connectivity model; and

updating the existing connectivity model based on said one or more detected inconsistencies.

15. A method comprising:

clustering multiple voltage time series measurements into multiple groups based on one or more distance metrics comprising at least (i) a distance metric that associates each of multiple voltage time series measurements with one of multiple sub-circuits, and (ii) a distance metric pertaining to distance between each of the voltage time series measurements that are associated with the same one of the multiple sub-circuits, wherein said multiple voltage time series measurements are derived from one or more sensors;

determining a partial connectivity model of the multiple groups, wherein said determining comprises inferring multiple connectivity relationships based on said clustering;

supplementing the partial connectivity model with one or more energy measurements derived from a grid and one or more energy measurements from one or more customers to generate a determined connectivity model;

comparing the determined connectivity model to an existing connectivity model to detect one or more inconsistencies between the determined connectivity model and the existing connectivity model; and

updating the existing connectivity model based on said one or more detected inconsistencies;

wherein at least one of the steps is carried out by a computing device.

16. The method of claim 15 , wherein said one or more sensors comprise a set of multiple customer-associated meters.

17. The method of claim 15 , wherein said one or more sensors comprise a set of multiple smart plugs on customer premises.

18. The method of claim 15 , wherein said one or more sensors comprise at least one of a set of transformer meters, a set of feeder meters, and a set of supervisory control and data acquisition devices.

19. The method of claim 15 , comprising:

obtaining the one or more energy measurements derived from a grid and the one or more energy measurements from one or more customers in synchronization.

20. The method of claim 15 , wherein said clustering comprises clustering the multiple voltage time series measurements further based on one or more common phase associations.

21. The method of claim 15 , wherein said clustering comprises clustering the multiple voltage time series measurements further based on one or more clustering algorithms.

22. The method of claim 15 , wherein said clustering comprises clustering the multiple voltage time series measurements further based on one or more common circuit associations.

23. An article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising:

clustering multiple voltage time series measurements into multiple groups based on one or more distance metrics comprising at least (i) a distance metric that associates each of multiple voltage time series measurements with one of multiple sub-circuits, and (ii) a distance metric pertaining to distance between each of the voltage time series measurements that are associated with the same one of the multiple sub-circuits, wherein said multiple voltage time series measurements are derived from one or more sensors;

determining a partial connectivity model of the multiple groups, wherein said determining comprises inferring multiple connectivity relationships based on said clustering;

supplementing the partial connectivity model with one or more energy measurements derived from a grid and one or more energy measurements from one or more customers to generate a determined connectivity model;

comparing the determined connectivity model to an existing connectivity model to detect one or more inconsistencies between the determined connectivity model and the existing connectivity model; and

updating the existing connectivity model based on said one or more detected inconsistencies.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 6, 2017
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: UTOPUS INSIGHTS, INC.
Reel/Frame 042700/0530 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 15, 2013
From: ARYA, VIJAY; MITRA, RAJENDRU
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 031018/0794 →
Continuity (1)
Related Publication 20150052088A1 · Feb 19, 2015