System and Method of Waveform Analysis to Identify and Characterize Power-Consuming Devices on Electrical Circuits

• US 20130191103A1
• Filed: 01/19/2012
• Published: 07/25/2013
• Est. Priority Date: 01/19/2012
• Status: Active Grant

• Current Assignee: Verdigris Technologies, Inc.
• Original Assignee: Verdigris Technologies, Inc.
• Inventors: Chu, Jonathan Michael, Wu, Eric Ping, Chung, Yungnun Mark, Kuo, Bertrand J.
• Granted Patent: US 8,694,291 B2
• Time in Patent Office: Days
• US Class Current: 703/14
• CPC Class Codes: G06F 2119/06 Power analysis or power optimisation
• CPC Class Codes: G06F 30/367 Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods

Abstract

Waveform analysis is performed to identify and characterize power-consuming devices operating on a building electrical circuit. Current waveforms are measured from the building circuit with electrical devices operating thereon. The waveforms are separated into wavelets and analyzed to identify a representative wavelet model which is transmitted to a server for analysis. The server compares the representative wavelet model to a predictive model built from waveform signatures of known electrical devices operating on a circuit. When the predictive model matches the representative wavelet model, the electrical devices contributing to the representative wavelet, their operating mode(s) (e.g., “on”, “off”, “paused”, “hibernating”) and/or their performance state(s) (e.g., normal operation, deterioration, or failure modes) can be identified. This information can be communicated as feedback to the consumer to facilitate more efficient and more cost-effective energy usage.

Claims

1. A method of characterizing an electrical device comprising:

a. measuring an aggregated waveform from a building electrical circuit, the aggregated waveform resulting from current flow on the building electrical circuit through one or more device connected to the building electrical circuit;

b. determining a representative wavelet model from the aggregated waveform;

c. communicating the representative wavelet model over a network to a server;

d. creating a combined predictive model by combining two or more known waveform signatures, each known waveform signature obtained from a known electrical device;

e. comparing at the server the combined predictive model to the communicated representative wavelet model; and

f. characterizing at least one of the one or more electrical devices connected to the building electrical circuit when the compared combined predictive model and the representative wavelet model match.

2. The method of claim 1 further comprising creating another combined predictive model combination when the combined predictive model and the representative wavelet model do not match, and repeating steps (e) and (f) with the another combined predictive model in place of the combined predictive model.

3. The method of claim 1 further comprising a step of digitizing and denoising the aggregated waveform before the step of determining a representative wavelet model from the aggregated waveform and wherein the step of determining a representative wavelet model from the aggregated waveform is determining a representative wavelet model from the digitized and denoised aggregated waveform.

4. The method of claim 3 wherein the representative wavelet model comprises a mean current and a standard deviation at each time index of a representative wavelet, the means and standard deviations of the representative wavelet being calculated from a sample of wavelets from the denoised digitized aggregated waveform, each sample wavelet having a current measurement at each of multiple time indices throughout the wavelet.

5. The method of claim 1 wherein the step of characterizing at least one of the one or more electrical devices connected to the building electrical circuit comprises identifying at least one of the one or more electrical devices.

6. The method of claim 1 wherein the known waveform signatures comprise a known waveform signature for an operating mode of the known electrical device.

7. The method of claim 6 wherein the step of characterizing at least one of the one or more electrical devices connected to the building electrical circuit comprises identifying the operating mode of at least one of the one or more electrical devices.

8. The system of claim 1 wherein the known waveform signatures comprise a known waveform signature for a performance state of the known electrical device.

9. The method of claim 8 wherein the step of characterizing at least one of the one or more electrical devices connected to the building electrical circuit comprises identifying the performance state of at least one of the one or more electrical devices.

10. The method of claim 1 wherein the step of comparing the combined predictive model to the representative wavelet model comprises performing a transform and frequency analysis.

11. The method of claim 10 wherein the transform and frequency analysis is a Fourier analysis.

12. The method of claim 1 wherein the step of comparing the combined predictive model to the representative wavelet model comprises performing a statistical time domain comparison analysis.

13. The method of claim 1 wherein the step of comparing the combined predictive model to the representative wavelet model comprises performing a fingerprinting analysis.

14. The method of claim 13 wherein the fingerprinting analysis is a Frechet analysis.

15. The method of claim 1 wherein the step of comparing the combined predictive model to the representative wavelet model comprises performing a machine learning analysis.

17. The system of claim 14 wherein the energy monitor is further configured to digitize and denoise the aggregated waveform.

18. The system of claim 14 wherein the server configured to characterize at least one of the one or more electrical devices operating on the building electrical circuit is further configured to identify at least one of at least one of the one or more electrical devices.

19. The system of claim 14 wherein the known waveform signatures comprise a known waveform signature for an operating mode of the known electrical device.

20. The system of claim 19 wherein the server configured to characterize at least one of the one or more electrical devices operating on the building electrical circuit is further configured to identify the operating mode of at least one of the one or more electrical devices.

21. The system of claim 14 wherein the known waveform signatures comprise known waveform signatures for more than one performance state of the known electrical device.

22. The system of claim 21 wherein the server configured to characterize at least one of the one or more electrical devices operating on the building electrical circuit is further configured to identify the performance state of at least one of the one or more electrical devices.

16. A system to characterize an electrical device connected to a building electrical circuit comprising:

an energy monitor configured to

connect to the building electrical circuit;

measure an aggregated waveform from the building circuit, the aggregated waveform resulting from current flow on the building circuit through one or more device connected to the building circuit;

determine a representative wavelet model from the aggregated waveform; and

communicate across a communication network; and

a server configured to

communicate across the communication network with the energy monitor to obtain the representative wavelet model;

create a combined predictive model by combining two or more known waveform signatures, each known waveform signature obtained from a known electrical device;

compare the combined predictive model to the representative wavelet model; and

characterize at least one of the one or more of the electrical devices operating on the building circuit based on a comparison of the combined predictive model with the representative wavelet model.

23. A non-transitory computer readable storage medium having stored thereupon computing instructions comprising:

a code segment to measure an aggregated waveform from a building electrical circuit, the aggregated waveform resulting from current flow on the building electrical circuit through one or more device connected to the building electrical circuit;

a code segment to determine a representative wavelet model from the aggregated waveform;

a code segment to create a combined predictive model by combining two or more known waveform signatures, each known waveform signature obtained from a known electrical device;

a code segment to compare the combined predictive model to the communicated representative wavelet model; and

a code segment to characterize at least one of the one or more electrical devices connected to the building electrical circuit when the compared combined predictive model and the representative wavelet model match.

24. The non-transitory computer readable storage medium of claim 23 further comprising a code segment to digitize and denoise the aggregated waveform before determining a representative wavelet model from the aggregated waveform and wherein the code segment to determine a representative wavelet model from the aggregated waveform is a code segment to determine a representative wavelet model from the digitized and denoised aggregated waveform.