Automatic Network Device Electrical Phase Identification

• US 20160352103A1
• Filed: 03/01/2016
• Published: 12/01/2016
• Est. Priority Date: 05/28/2015
• Status: Active Grant

• Current Assignee: Itron Global Sarl (Itron, Inc.)
• Original Assignee: Itron, Inc.
• Inventors: Aiello, Roberto, Amihood, Patrick
• Granted Patent: US 10,312,681 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01R 19/2513 Arrangements for monitoring electric power systems, e.g. power lines or loads; Logging
• CPC Class Codes: G01R 29/18 Indicating phase sequence; Indicating synchronism
• CPC Class Codes: G05B 13/0265 the criterion being a learning criterion
• 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 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00022 using wireless data transmission
• CPC Class Codes: H02J 13/00034 the elements or equipment being or involving an electric power substation
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/12 for adjusting voltage in ac networks by changing a characteristic of the network load
• CPC Class Codes: H02J 3/26 Arrangements for eliminating or reducing asymmetry in polyphase networks
• CPC Class Codes: H02J 3/34 Arrangements for transfer of electric power between networks of substantially different frequency
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• 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 20/00 Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
• CPC Class Codes: Y04S 20/242 Home appliances
• CPC Class Codes: Y04S 40/126 using wireless data transmission

Abstract

Techniques detect an electrical phase used by electrical network devices (e.g., a transformer, electrical meter, etc.). Voltage measurement data is obtained, such as from electrical meters. The voltage measurement data may be associated with a timestamp, and may be made at intervals over a period of time. Voltage changes may be calculated using the voltage measurement data. In an example, the voltage change is a difference determined between sequential voltage measurements. In some instances, voltage changes data is removed if it exceeds a threshold. An initial classification of network devices (e.g., randomly or by assumed electrical phase) is determined. A clustering technique (e.g., k-means) is applied, wherein the classification is updated in a manner that segregates the network devices according to actual electrical phase.

Claims

1. A method, comprising:

under control of one or more processors configured with executable instructions;

obtaining voltage measurement data;

calculating voltage change data using the obtained voltage measurement data;

excluding voltage change data from among the calculated voltage change data that are outside a threshold range;

configuring an initial classification of network devices; and

iteratively updating the initial classification according to a clustering technique acting on the calculated voltage changes, thereby segregating the network devices according to electrical phase.

2. The method of claim 1, wherein the iterative updating comprises:

reclassifying at least some network devices based on the calculated voltage changes, to thereby cluster network devices having similar calculated voltage changes at similar times.

3. The method of claim 1, wherein the iterative updating comprises:

reclassifying the network devices to minimize a distance function as applied to the calculated voltage changes.

4. The method of claim 1, wherein the iterative updating comprises:

operating k-means clustering techniques to segregate the network devices according to electrical phase.

5. The method of claim 1, wherein obtaining voltage measurement data comprises:

obtaining at least 48 measurements over at least two days.

6. The method of claim 1, wherein obtaining voltage measurement data comprises:

using voltage measurements made less than two hours apart by a same network device to calculate a voltage change.

7. The method of claim 1, wherein excluding of the voltage change data comprises:

setting voltage change data to approximately zero, when the voltage change data exceeds the threshold.

8. The method of claim 1, additionally comprising:

connecting at least one network device, from among the network devices, to a different phase based at least in part on the iterative updates.

9. The method of claim 1, additionally comprising:

excluding data from network devices for which insufficient or incomplete data exists.

10. One or more computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising:

calculating voltage change data for a plurality of network devices;

limiting the voltage change data to that within a threshold range;

classifying meters according to an initial classification to prepare for application of a clustering technique to the voltage change data;

clustering the meters according to voltage changes over time, in an iterative manner to update the initial classification and to thereby cluster meters by electrical phase; and

providing information about an electrical service associated with at least one network device from among the plurality of network devices, the information sufficient to indicate an electrical load to be moved from a first phase to a second phase.

11. One or more computer-readable media as recited in claim 10, wherein calculating the voltage change data comprises:

calculating a voltage change vector for each of the plurality of network devices, wherein each voltage change vector comprises paired time and voltage change values.

12. One or more computer-readable media as recited in claim 10, wherein limiting voltage change data comprises:

setting to zero voltage change data outside the threshold range.

13. One or more computer-readable media as recited in claim 10, wherein clustering the meters comprises:

an iterative process by which convergence is indicated by minimizing a distance function.

14. One or more computer-readable media as recited in claim 10, wherein providing information comprises:

reconnecting a load measured by a first network device from a first phase to a second phase.

15. A computing device, comprising:

a processing unit;

memory, accessible by the processing unit;

a data module, defined in the memory and executed by the processing unit, to gather voltage data of a plurality of network devices;

a voltage change calculation module, defined in the memory and executed by the processing unit, to determine changes in voltage at each of the plurality of network devices; and

a clustering module, defined in the memory and executed by the processing unit, to determine a phase to which a network device from among the plurality of network devices is associated based at least in part on the changes determined by the voltage change calculation module.

16. The computing device as recited in claim 15, additionally comprising:

a phase-switching module, defined in the memory and executed by the processing unit, and configured to cause a load of one of the plurality of network devices to be switched from one phase to another phase.

17. The computing device as recited in claim 15, wherein the data module is configured to:

obtain data over a period of at least 24 hours; and

obtain measurements separated by 2 hours or less.

18. The computing device as recited in claim 15, additionally comprising:

a data threshold module configured to set voltage change data to approximately zero, when the voltage change data exceeds the threshold; and

a data cleaning module configured to remove data associated with network devices for which the gathered data is incomplete.

19. The computing device as recited in claim 15, wherein the clustering module is configured to:

utilize k-means techniques to cluster network devices having similar calculated voltage changes at similar times.

20. The computing device as recited in claim 15, wherein the clustering module is configured to perform:

an iterative process by which convergence is indicated by minimizing a distance function.