Utility data processing system

• US 8,825,583 B2
• Filed: 12/20/2010
• Issued: 09/02/2014
• Est. Priority Date: 12/18/2009
• Status: Active Grant

• Current Assignee: Onzo Ltd.
• Original Assignee: Onzo Ltd.
• Inventors: Sanchez Loureda, Jose Manuel, Westbrooke, Adam Richard
• Primary Examiner(s): CHANG, LI WU
• Application Number:
  US13/061,050
• Publication Number:
  US 20110313964A1
• Time in Patent Office: 1,352 Days
• Field of Search: None
• US Class Current: 706/50
• CPC Class Codes: G01D 2204/24 Identification of individual loads, e.g. by analysing current/voltage waveforms
• CPC Class Codes: G01D 4/002 Remote reading of utility meters
• 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 2310/14 The load or loads being home appliances
• CPC Class Codes: H02J 2310/64 The condition being economic, e.g. tariff based load management
• CPC Class Codes: H02J 2310/70 Load identification
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/30 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 70/3225 Demand response systems, e.g. load shedding, peak shaving
• 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 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/242 Home appliances
• CPC Class Codes: Y04S 20/30 Smart metering, e.g. specially adapted for remote reading
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

A utility data processing system for processing data relating to consumption of a utility comprises: a fact memory for storage of facts relating to utility consumption received from fact sources, at least one fact source module for deriving facts from utility consumption data and adding the derived facts to the tact memory, an inference module for inferring new facts relating to utility consumption from one or more facts stored in the fact memory, and an interlace module.

Claims

1. A utility data processing system for processing data relating to consumption of a utility, the system comprising:

a non-transitory machine readable fact memory for storage of facts relating to utility consumption received from fact sources;

at least one fact source module for deriving facts from utility consumption data and adding the derived facts to the non-transitory machine readable fact memory, wherein one of the at least one fact source modules comprises an appliance identification module configured to identify one or more appliances using data based on utility consumption by the one or more appliances and to add the identity of the one or more appliances as one or more facts in the non-transitory machine readable fact memory;

an inference module for inferring new facts relating to utility consumption from one or more facts stored in the non-transitory machine readable fact memory, wherein the inference module is configured to instruct the appliance identification module to search for one or more further unidentified appliances, wherein the search for each of the one or more further unidentified appliances is identified based on the one or more appliances stored as one or more facts that are likely to be present in view of the presence of an identified appliance by analyzing the utility consumption data, and wherein the search comprises matching signature profiles of candidate appliances stored in a database with measured profiles of events of electricity consumption, wherein a signature profile is represented by a series of events associated with the rate of change in power demand from one time point to the next; and

an interface module.

2. The system of claim 1, wherein the appliance identification module comprises:

a profile generator for generating a utility consumption profile from utility consumption data, the utility consumption data comprising a plurality of utility consumption values measured at a corresponding plurality of measurement points; and

an event identifier for identifying an event within the utility consumption profile that matches the profile of a known event associated with operation of a known device, said known event stored in a database of utility consumption profiles.

3. The system of claim 2, wherein the appliance identification module is further configured to add the time of use or duration of use the one or more appliances present within the household as one or more facts in the non-transitory machine readable fact memory.

4. The system of claim 1, wherein the at least one fact source module comprises a statistics module configured to generate statistical facts on energy consumption from the utility consumption data.

5. The system of claim 4, wherein the statistical facts is at least one of an energy use per period of time, variations in energy usage per period of time, and a baseload energy.

6. The system of claim 5, wherein the period of time is one or more of 1 hour, 1 day, 1 week, 1 month and 1 year.

7. The system of claim 1, further comprising a data memory for storage of utility consumption data received from at least one utility meter.

8. The system of claim 1, wherein the interface module is a presentation interface configured to present facts on a display screen.

9. The system of claim 8, wherein the system is configured to receive data from the presentation interface.

10. The system of claim 8, wherein the non-transitory machine readable fact memory is configured to receive facts declared by a user of the system via the interface.

11. The system of claim 10, wherein the system is configured to prompt a declaration of a fact by a user.

12. The system of claim 1, wherein the interface module is a control interface.

13. The system of claim 12, wherein the control interface is configured to control utility consumption within a household managed by the utility data processing system based on control parameters determined by one or more facts.

14. The system of claim 4, wherein the statistics module is further configured to generate average utility consumption by a group of households.

15. A computer-implemented method of processing utility consumption data, the method comprising:

receiving utility consumption data;

deriving at least one fact from utility consumption data, wherein the deriving comprises identifying one or more appliances using data based on utility consumption by the one or more appliances;

storing the at least one fact in a non-transitory machine readable fact memory;

inferring at least one new fact from the at least one fact stored in the non-transitory machine readable fact memory; and

based on the inference, instructing a search for one or more further identified appliances, wherein the search for each of the one or more further unidentified appliances is identified based on the one or more appliances stored as one or more facts that are likely to also be present in view of the presence of the identified appliance by analyzing the utility consumption data, and wherein the search comprises matching signature profiles of candidate appliances stored in a database with measured profiles of events of electricity consumption, wherein a signature profile is represented by a series of events associated with the rate of change in power demand from one time point to the next.

16. An article of manufacture, comprising:

a non-transitory machine-readable storage medium; and

executable program instructions embodied in the non-transitory machine readable storage medium that when executed by a programmable system causes the system to perform the function of processing utility consumption data comprising;

receiving utility consumption data;

deriving at least one fact from the utility consumption data, wherein the deriving comprises identifying one or more appliances using data based on utility consumption by the one or more appliances;

storing the at least one fact in a non-transitory machine-readable fact memory;

inferring at least one new fact from the at least one fact stored in the non-transitory machine readable fact memory; and

based on the inference, initiating a search for one or more further identified appliances, wherein the search for each of the one or more further unidentified appliances is identified based on the one or more appliances stored as one or more facts that are likely to be present in view of the presence of the identified appliance by analyzing the utility consumption data, and wherein the search comprises matching signature profiles of candidate appliances stored in a database with measured profiles of events of electricity consumption, wherein a signature profile is represented by a series of events associated with the rate of change in power demand from one time point to the next.