Cognitive electric power meter
AssigneeGeneral Electric Company
InventorsMichael Richard Durling, Zhiyuan Ren, Nikita Visnevski, Lauren Elizabeth Ray
Life of this patent
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Abstract
An electric power meter includes an embedded decomposition module that is configured to decompose a power meter signal into constituent loads to segregate and identify energy consumption associated with each individual energy consumption device within a plurality of energy consumption devices coupled to the power meter.
Claims77
An electric power meter comprising:
- at least one sensor configured to measure at least one desired energy consumption variable associated with a plurality of energy consumption devices, and to generate at least one output signal therefrom;
- and
- a decomposition module configured to decompose the at least one output signal into constituent individual loads and therefrom identify energy consumption corresponding to each energy consumption device within the plurality of energy consumption devices,
- wherein the decomposition module comprises a cognitive decomposition algorithm configured to store knowledge and learn, continuously adapting to changes in household power line characteristics to improve power line monitoring and energy consumption device control capabilities,
- and further wherein the decomposition algorithm employs invariant representation and associative processing to implement its learning.
An electric power meter comprising:
- at least one sensor configured to measure at least one desired energy consumption variable associated with a plurality of energy consumption devices, and to generate at least one output signal therefrom;
- and
- a decomposition module configured to decompose the at least one output signal into constituent individual loads and therefrom identify energy consumption corresponding to each energy consumption device within the plurality of energy consumption devices,
- wherein the decomposition module comprises a cognitive decomposition algorithm configured to store knowledge and learn, continuously adapting to changes in household power line characteristics to improve power line monitoring and energy consumption device control capabilities,
- and further wherein the decomposition algorithm is aggregated in a multidimensional associative array that is segmented based on the particular element of the cognitive cycle it supports.
An electric power meter comprising:
- at least one sensor configured to measure at least one desired energy consumption variable associated with a plurality of energy consumption devices, and to generate at least one output signal therefrom;
- and
- a decomposition module configured to decompose the at least one output signal into constituent individual loads and therefrom identify energy consumption corresponding to each energy consumption device within the plurality of energy consumption devices, wherein the decomposition module comprises a cognitive decomposition algorithm configured to identify, without requiring field training, energy consumption devices on a household power line.
A method of decomposing a household power meter signal, the method comprising:
- measuring a household meter power line signal;
- decomposing within the household power meter, the power line signal into constituent individual loads;
- and
- identifying within the household power meter, energy consumption corresponding to each individual load within a plurality of loads that operate together to generate the household meter power line signal;
- storing knowledge and learning, based on the measuring, decomposing and identifying, and continuously adapting to changes in household power line characteristics to improve power line monitoring and energy consumption device control capabilities, wherein the learning is based on invariant representation and associative processing techniques.
A method of decomposing a household power meter signal, the method comprising:
- measuring a household meter power line signal;
- decomposing within the household power meter, the power line signal into constituent individual loads;
- and
- identifying within the household power meter, energy consumption corresponding to each individual load within a plurality of loads that operate together to generate the household meter power line signal;
- and
- storing knowledge and learning, based on the measuring, decomposing and identifying, and continuously adapting to changes in household power line characteristics to improve power line monitoring and energy consumption device control capabilities, wherein storing knowledge comprises aggregating a multidimensional associative array that is segmented based on a particular element of a desired cognitive cycle.
A method of decomposing a household power meter signal, the method comprising:
- measuring a household meter power line signal;
- decomposing within the household power meter, the power line signal into constituent individual loads;
- and
- identifying within the household power meter, energy consumption corresponding to each individual load within a plurality of loads that operate together to generate the household meter power line signal, wherein the identifying comprises identifying, without requiring field training, energy consumption devices on a household power line.
An electric power meter comprising an embedded decomposition module configured for decomposing a power signal into constituent loads to segregate and identify energy consumption associated with each individual energy consumption device within a plurality of energy consumption devices, wherein the decomposition module comprises a cognitive decomposition algorithm configured to store knowledge and learn, continuously adapting to changes in household power line characteristics to improve power line monitoring and energy consumption device control capabilities, wherein the decomposition algorithm comprises invariant representation and associative processing to implement its learning.
An electric power meter comprising an embedded decomposition module configured for decomposing a power signal into constituent loads to segregate and identify energy consumption associated with each individual energy consumption device within a plurality of energy consumption devices, wherein the decomposition module comprises a cognitive decomposition algorithm configured to store knowledge and learn, continuously adapting to changes in household power line characteristics to improve power line monitoring and energy consumption device control capabilities, wherein the decomposition algorithm is aggregated in a multidimensional associative array that is segmented based on the particular element of the cognitive cycle it supports.
An electric power meter comprising an embedded decomposition module configured for decomposing a power signal into constituent loads to segregate and identify energy consumption associated with each individual energy consumption device within a plurality of energy consumption devices, wherein the decomposition module comprises a cognitive decomposition algorithm configured to identify, without requiring field training, energy consumption devices on a household power line.
Dependencies are inferred from the claim text.