Automated hierarchy classification in utility monitoring systems

• US 20070005277A1
• Filed: 07/01/2005
• Published: 01/04/2007
• Est. Priority Date: 07/01/2005
• Status: Active Grant

• Current Assignee: Square D Company (Schneider Electric SE)
• Original Assignee: Square D Company (Schneider Electric SE)
• Inventors: Bickel, Jon, Carter, Ronald
• Granted Patent: US 7,272,518 B2
• Time in Patent Office: Days
• US Class Current: 702/61
• CPC Class Codes: G01D 2204/24 Identification of individual loads, e.g. by analysing current/voltage waveforms
• CPC Class Codes: G01D 2204/47 Methods for determining the topology or arrangement of meters in a network
• CPC Class Codes: G01D 4/004 Remote reading of utility meters to a fixed location
• 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: Y04S 20/30 Smart metering, e.g. specially adapted for remote reading

Abstract

An auto-learned hierarchy algorithm that learns the hierarchical layout of a power monitoring system. Historical power data from each meter is received and placed into a data table. The main is assumed to be at the top of the hierarchy and is designated as the reference. A check matrix is developed indicating whether a possible connection exists between each meter pair combination. A correlation coefficient matrix (CCM) is calculated based on the data table, and entries in which no connection is possible are zeroed. The column for the reference meter from the CCM is copied to a correlation reference array (CRA), and the meter having the highest correlation with the reference meter in the CRA is marked as connected to the reference meter in a connection table. That meter'"'"'s power is subtracted from the data table and the procedure is repeated until all meters have been analyzed.

Claims

1. A method of automatically learning relationships among N elements including a reference element arranged in a hierarchy in a radial distribution system, comprising:

receiving from each of said elements at least one criterion associated with each of said elements;

calculating, using a correlation algorithm, a correlation coefficient between said reference element and every other element in said radial distribution system to produce N-1 correlation coefficients;

determining the highest correlation coefficient among said N-1 correlation coefficients; and

responsive to said determining, automatically interrelating the element associated with said highest correlation coefficient and said reference element.

2. The method of claim 1, further comprising:

calculating, using a correlation algorithm, a correlation coefficient between said reference element and every other element in said radial distribution system except for said element associated with said highest correlation coefficient to produce N-2 correlation coefficients;

determining the highest correlation coefficient among said N-2 correlation coefficients; and

responsive to said determining, automatically interrelating the element associated with said highest correlation coefficient among said N-2 correlation coefficients and said reference element.

3. The method of claim 1, wherein said radial distribution system is a utility system, wherein said utility is selected from the group consisting of water, air, gas, electricity, and steam.

4. The method of claim 1, wherein said radial distribution system is a power monitoring system.

5. The method of claim 1, wherein said at least one criterion is selected from the group consisting of power, voltage, current, voltage distortion, BTU per hour, MBTU per hour, energy, gallons per minute, and cubic feet per minute.

6. The method of claim 1, wherein said at least one criterion is power.

7. The method of claim 1, wherein N is at least two.

8. The method of claim 1, wherein said elements include power meters.

9. The method of claim 1, wherein said elements are monitoring devices that monitor at least one criterion selected from the group consisting of power, energy, volume of water per minute, volume of air per minute, volume of gas per minute, and volume of steam per minute.

10. The method of claim 1, wherein said elements include at least one element selected from the group consisting of a main, a feeder, a header, and a load.

11. The method of claim 1, further comprising receiving the time that said at least one criterion was received from each of said elements.

12. A computer readable medium encoded with instructions for directing a controller to perform the method of claim 1.

13. A method of automatically determining the hierarchy of monitoring devices arranged within a power monitoring system, wherein monitoring devices at the top of the hierarchy generally measure more power than monitoring devices lower on the hierarchy, comprising:

receiving electrical parameter data from each monitoring device in said power monitoring system at periodic time intervals for a predetermined time period;

arranging said electrical parameter data into a data table that tabulates said electrical parameter data for each monitoring device at each of said periodic time intervals;

forming at least a portion of a correlation matrix that includes correlation coefficients between at least some combination pairs of said monitoring devices, said correlation coefficients being calculated according to a correlation algorithm; and

analyzing said correlation matrix to identify an interrelationship between a combination pair of said monitoring devices.

14. The method of claim 13, further comprising:

removing from said data table a monitoring device for which an interrelationship was identified;

recalculating said correlation coefficients; and

analyzing said recalculated correlation coefficients to identify another interrelationship between a second combination pair of said monitoring devices.

15. The method of claim 13, further comprising forming at least a portion of a matrix that indicates for each pair combination of said monitoring devices in said data table whether an interrelationship exists between a given pair of monitoring devices;

16. The method of claim 13, wherein said electrical parameter data includes power, voltage, current, voltage distortion, or current distortion.

17. The method of claim 13, wherein said interrelationship is a direct link.

18. The method of claim 13, wherein said power monitoring system is radially distributed.

19. The method of claim 13, further comprising:

identifying the monitoring device having the highest electrical parameter value; and

responsive to said identifying, identifying the monitoring device as a reference monitoring device,

wherein said combination pair includes said reference monitoring device and another monitoring device.

20. The method of claim 13, wherein said analyzing includes determining whether a correlation coefficient exceeds a correlation threshold for any given combination pair of monitoring devices, and if so, identifying that combination pair as interrelated.

21. The method of claim 13, wherein said analyzing includes determining the maximum correlation coefficient in said correlation matrix, and identifying the combination pair associated with said maximum correlation coefficient as being interrelated.

22. The method of claim 13, wherein said receiving is carried out after a new monitoring device is added to said power monitoring system.

23. The method of claim 13, further comprising:

forming a hierarchy having a plurality of levels, at least some of said monitoring devices being linked together directly in said hierarchy among said plurality of levels, a monitoring device on a first level being interrelated to another monitoring device on a second level when they are directly linked together, said forming including determining, using a correlation algorithm, which of said at least some of said monitoring devices are directly linked together in said hierarchy and on which level of said plurality of levels each of said at least some of said monitoring devices is located in said hierarchy; and

responsive to said forming, displaying said hierarchy to an operator.

24. The method of claim 13, wherein said monitoring devices arranged within said power monitoring system include power meters.

25. The method of claim 13, wherein said power monitoring system includes loads coupled to said monitoring devices, each of said periodic time intervals being longer than the shortest duty cycle of any load in said power monitoring system.

26. A method of automatically determining how devices in a multi-level hierarchy are linked to one another, comprising:

receiving data from at least some of said devices in said hierarchy, said data representing a unidirectional flow of a utility measured by said at least some of said devices; and

determining whether at least a first device and a second device are directly interlinked using a correlation algorithm that produces a correlation coefficient based on respective data from said first device and said second device.

27. The method of claim 26, wherein said utility is at least one utility selected from the group consisting of water, air, gas, electricity, and steam.

28. The method of claim 26, wherein said first and second devices are meters.

29. The method of claim 26, wherein said determining includes identifying said first device and said second device as being directly interlinked when said correlation coefficient between said first device and said second device exceeds a threshold.

30. The method of claim 26, wherein said determining includes identifying said first device and said second device as being directly interlinked when said correlation coefficient between said first device and said second device exceeds a correlation coefficient with respect to every other device in said hierarchy.

31. The method of claim 26, wherein said hierarchy is a radial distribution hierarchy.

32. The method of claim 26, wherein said data is representative of electrical power.