Energy disaggregation techniques for low resolution whole-house energy consumption data
First Claim
1. A method for learning an energy consumption signature associated with a specific appliance from low resolution energy consumption interval data associated with a specific house, comprising:
- receiving at a processor low-resolution energy consumption interval data corresponding to whole house energy consumption for the specific house, wherein the low-resolution energy consumption interval data is sampled periodically with periods ranging from minute to hourly;
selectively communicating by the processor with a first database comprising non-electrical information;
selectively communicating by the processor with a second database comprising training data, the training data comprised at least in part of high resolution energy consumption data received from a plurality of homes associated with appliances at least some of which are the same type as the specific appliance, wherein the high resolution energy consumption data is sampled periodically with periods of less than one minute;
wherein training data comprises at least in part feedback information by a user through an interactive user interface using interactive charts;
determining a correlation between the low-resolution energy consumption interval data with a sample of the high resolution training data;
based on at least in part on the correlation and the non-electrical information, making a determination that the specific appliance was running during the sample of the interval data;
identifying the energy consumption signature of the specific appliance, at least in part by estimating of the energy consumption by the specific appliance at a hourly, daily or monthly scale; and
performing an action of energy management by presenting information regarding the energy consumption signature of the specific appliance to a user.
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Abstract
The present invention is generally directed to methods of disaggregating low resolution whole-house energy consumption data. In accordance with some embodiments of the present invention, methods may include steps of: receiving at a processor the low resolution whole house profile; selectively communicating with a first database including non-electrical information; selectively communicating with a second database including training data; and determining by the processor based on the low resolution whole house profile, the non-electrical information and the training data, individual appliance load profiles for one or more appliances.
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Citations
15 Claims
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1. A method for learning an energy consumption signature associated with a specific appliance from low resolution energy consumption interval data associated with a specific house, comprising:
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receiving at a processor low-resolution energy consumption interval data corresponding to whole house energy consumption for the specific house, wherein the low-resolution energy consumption interval data is sampled periodically with periods ranging from minute to hourly; selectively communicating by the processor with a first database comprising non-electrical information; selectively communicating by the processor with a second database comprising training data, the training data comprised at least in part of high resolution energy consumption data received from a plurality of homes associated with appliances at least some of which are the same type as the specific appliance, wherein the high resolution energy consumption data is sampled periodically with periods of less than one minute; wherein training data comprises at least in part feedback information by a user through an interactive user interface using interactive charts; determining a correlation between the low-resolution energy consumption interval data with a sample of the high resolution training data; based on at least in part on the correlation and the non-electrical information, making a determination that the specific appliance was running during the sample of the interval data; identifying the energy consumption signature of the specific appliance, at least in part by estimating of the energy consumption by the specific appliance at a hourly, daily or monthly scale; and performing an action of energy management by presenting information regarding the energy consumption signature of the specific appliance to a user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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Specification