Automatic matching of sources to loads

• US 10,205,319 B2
• Filed: 06/11/2010
• Issued: 02/12/2019
• Est. Priority Date: 06/11/2010
• Status: Active Grant

• Current Assignee: Eaton Intelligent Power Limited (Eaton Corporation PLC.)
• Original Assignee: Eaton Intelligent Power Limited (Eaton Corporation PLC.)
• Inventors: Pereira, Luis R., Lallement, Dominique L.
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US12/814,087
• Publication Number:
  US 20110307115A1
• Time in Patent Office: 3,168 Days
• Field of Search: 706 12
• CPC Class Codes: G06F 1/3209 Monitoring remote activity, e.g. over telephone lines or network connections
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2310/58 The condition being electrical
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

A method of matching sources to loads includes affecting load activity at a load with a pattern, receiving source activity data representing source activity at a plurality of sources, and matching the load to at least one source based on the source activity data. A system for matching sources to loads includes a load activity manipulator operably connected to a load and configured to affect load activity of the load with a pattern. The system for matching sources to loads further includes an activity monitor configured to receive source activity data representing source activity at the sources. The system for matching sources to loads also includes a matching engine operably connected to the activity monitor and configured to match the load to at least one source based on the source activity data.

Claims

1. A computer implemented method for determining a connectivity relationship between a source and a load on a network, the method comprising:

manipulating a load activity of at least one load of a plurality of loads on a network over a time period;

receiving, for each of the plurality of loads, load activity data characterizing the load activity of each respective load over the time period;

receiving source activity data associated with at least one source on the network characterizing a source activity of the source over the time period;

calculating a plurality of scores, wherein each score is indicative of a similarity between the load activity data of a given load of the plurality of loads and the source activity data of the at least one source; and

identifying a given score of the plurality scores corresponding to an optimal score, wherein the optimal score is indicative of a connectivity relationship between the at least one load and the at least one source on the network.

2. The computer-implemented method of claim 1, wherein the load activity of the at least one load corresponds to at least one of power consumption, signal strength, heat dissipation, torque, pressure, flow, operations per unit time, CPU utilization, I/O utilization, and network utilization.

3. The computer-implemented method of claim 1, wherein the source activity of the at least one source corresponds to at least one of power consumption, current, harmonic distortion, power factor, real power, apparent power, pressure, and flow.

11. The computer-implemented method of claim 1, wherein the manipulating of the load activity of the at least one load of the plurality of loads is based on a condition associated with a given one of the plurality of loads.

12. The computer-implemented method of claim 1, wherein the at least one source corresponds to a plurality of sources;

wherein the source activity data includes aggregated source activity data indicative of the manipulation of the load activity data of the at least one load at the plurality sources; and

wherein the optimal score is indicative of a connectivity relationship between at least two sources of the plurality of sources and the at least one load of the plurality loads.

13. The computer-implemented method of claim 1,

wherein the source activity data includes data indicative of the manipulation of the load activity data of at least two loads;

and

wherein the optimal score is indicative of a connectivity relationship between the at least two loads of the plurality of loads and the at least one source.

14. The computer-implemented method of claim 1, further comprising:

generating connectivity relationship data characterizing the determined connectivity relationship between the at least one load and the at least one source on the network; and

generating a connection map representing the connectivity relationship between the at least one load and the at least one source on the network based on the connectivity relationship data.

4. A computer implemented method for determining a connectivity relationship between a source and a load on a network, the method comprising:

affecting a load activity of at least one load of a plurality of loads on a network with a known pattern;

receiving source activity data characterizing a source activity of at least one source of a plurality of sources on the network, wherein the source activity data comprises data indicative of the known pattern; and

evaluating load activity data of each of the plurality of loads relative to the source activity data of the at least one source to identify the known pattern to determine a connectivity relationship between the at least one load and the at least one source on the network.

5. The computer-implemented method of claim 4, further comprising receiving the load activity data representing the load activity of each of the plurality of loads.

6. The computer-implemented method of claim 4, wherein the source activity data is indicative of aggregated load activity corresponding to load activity at the plurality of loads on the network.

7. A computer-implemented method for determining a connectivity relationship between a load and a source on a network comprising:

applying a known pattern to at least one load of a plurality of loads on a network to affect a load activity of the at least one load, the known pattern corresponding to information identifying the at least one load of the plurality of loads on the network;

receiving at least one of load activity data characterizing the load activity for each of the plurality of loads and source activity data characterizing a source activity of at least one source on the network; and

evaluating the source activity data to identify the known pattern applied to the at least one load of the plurality of loads to determine a connectivity relationship between the at least one source at the least one load on the network.

8. The computer-implemented method of claim 7, wherein the source activity data includes data indicative of aggregated load activity corresponding to the plurality of loads connected to the at least one source on the network.

9. The computer-implemented method of claim 7, wherein the source activity corresponds to at least one of power consumption, current, harmonic distortion, power factor, real power, apparent power, pressure, and flow.

10. The computer-implemented method of claim 7, wherein to evaluate the source activity data comprises decoding the information identifying the at least one load and associating the at least one source with the at least one load based on the decoded information, wherein the association is indicative of the connectivity relationship between the at least one source and the at least one load.