Systems and methods for system measurements integrity determination

• US 10,110,976 B2
• Filed: 10/09/2017
• Issued: 10/23/2018
• Est. Priority Date: 10/10/2016
• Status: Active Grant

• Current Assignee: Utilidata, Inc.
• Original Assignee: Utilidata, Inc.
• Inventors: Bell, David Gordon
• Primary Examiner(s): Barakat, Mohamed
• Application Number:
  US15/728,415
• Publication Number:
  US 20180103302A1
• Time in Patent Office: 379 Days
• CPC Class Codes: G01D 2204/22 Arrangements for detecting or reporting faults, outages or leaks
• CPC Class Codes: G01D 4/002 Remote reading of utility meters
• CPC Class Codes: G01D 4/004 Remote reading of utility meters to a fixed location
• CPC Class Codes: G01R 21/133 by using digital technique
• CPC Class Codes: G01R 35/00 Testing or calibrating of apparatus covered by the other groups of this subclass
• CPC Class Codes: G01R 35/005 Calibrating; Standards or reference devices, e.g. voltage or resistance standards, "golden" references G01R33/0035, G01R35/002 take precedence
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 20/20 Ensemble learning
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H04Q 2209/60 for transmitting utility meters data, i.e. transmission of data from the reader of the utility meter
• CPC Class Codes: H04Q 2209/823 where the data is sent when the measured values exceed a threshold, e.g. sending an alarm
• CPC Class Codes: H04Q 9/00 Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
• CPC Class Codes: Y02B 70/34 Smart metering supporting the carbon neutral operation of end-user applications in buildings
• 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 20/30 Smart metering, e.g. specially adapted for remote reading
• CPC Class Codes: Y04S 40/128 involving the use of Internet protocol

Abstract

Systems and methods of the present disclosure are directed to determining the integrity of system measurements. The system and methods of the present disclosure can detect corrupted process measurement signals that can originate in instrumentation used with electricity distribution and transmission systems. These process measurement signals may be delivered by digital communications networks.

Claims

1. A method of detecting signal deviations in a utility grid, comprising:

receiving a first sampled time series of a first signal of a first process or a first operational characteristic of electricity in the utility grid, the first sampled time series of the first signal measured by a first digital device connected to the utility grid;

receiving a second sampled time series of a second signal of a second process or a second operational characteristic of electricity in the utility grid, the second sampled time series of the second signal measured by a second digital device connected to the utility grid;

identifying a pair of signals formed from the first sampled time series of the first signal and the second sampled time series of the second signal responsive to identifying a physical co-dependence between the first signal and the second signal, the physical co-dependence between the first signal and the second signal identified based on at least one of a dependence as indicated by one or more physical factors between the first digital device and the second digital device or a common phase between the first signal and the second signal, wherein the one or more physical factors includes at least one of connectivity between the first digital device and the second digital device or a connection topology of an electric circuit of the utility grid;

selecting, based on the pair of signals identified based on the physical co-dependence, an estimator from a predetermined list of estimators configured for the pair of signals;

determining, based on the estimator configured for the pair of signals identified based on the physical co-dependence, a metric for the pair of signals;

comparing the metric for the pair of signals with a nominal metric for the estimator configured for the pair of signals;

detecting, responsive to the comparison, a deviation between the metric for the pair of signals and the nominal metric for the estimator, the detected deviation due to at least one corrupt signal; and

responsive to detecting the deviation, generating an alert that indicates the deviation and at least one of the first digital device or the second digital device connected to the utility grid that provided the at least one of the first sampled time series or the second sampled time series that form the pair of signals that deviate from the nominal metric due to the at least one corrupt signal.

2. The method of claim 1, comprising:

correcting, prior to determining the metric for the pair of signals, sampling voids in at least one of the first sampled time series of the first signal or the second sampled time series of the second signal.

3. The method of claim 1, comprising:

determining, based on a number of void samples, whether to void at least one of the first sampled time series of the first signal or the second sampled time series of the second signal.

4. The method of claim 1, comprising:

processing, prior to determining the metric for the pair of signals, at least one of the first sampled time series of the first signal or the second sampled time series of the second signal by performing at least one of;

linear trend removal, removal of spectral components with periods greater than a sample record, or spectral filtering.

5. The method of claim 1, comprising:

determining the physical co-dependence between the first signal and the second signal based on the first digital device and the second digital device positioned on a same branch of a distribution circuit of the utility grid.

6. The method of claim 1, comprising:

determining the physical co-dependence between the first signal and the second signal based on the first digital device positioned ahead of a branch point on a distribution circuit of the utility grid, and the second digital device positioned after the branch point.

7. The method of claim 1, wherein the estimator is based on at least one of a statistical cross-moment, a joint density approximation, a dependency quantification by entropic divergence measures, or a causality quantification and prediction by directed dependence measures.

8. The method of claim 1, comprising:

identifying, prior to detecting the deviation, the nominal metric using a learning process.

9. The method of claim 1, comprising:

providing a command to at least one of the first digital device or the second digital device responsive to detecting the deviation.

10. The method of claim 1, comprising at least one of:

disabling at least one of the first digital device or the second digital device responsive to detecting the deviation;

resetting at least one of the first digital device or the second digital device responsive to detecting the deviation;

or

updating at least one of the first digital device or the second digital device responsive to detecting the deviation.

11. The method of claim 1, comprising:

preventing, responsive to detecting the deviation, a sampled time series of a signal measured by at least one of the first digital device or the second digital device from being used to adjust a tap setting at a voltage regulator of the utility grid.

12. A system for detection of signal deviations in a utility grid, comprising:

a non-conforming signal detector comprising one or more processors that execute a metric estimator component to;

receive a first sampled time series of a first signal of a first process or a first operational characteristic of electricity in the utility grid, the first sampled time series of the first signal measured by a first digital device connected to the utility grid;

receive a second sampled time series of a second signal of a second process or a second operational characteristic of electricity in the utility grid, the second sampled time series of the second signal measured by a second digital device connected to the utility grid;

identify a pair of signals formed from the first sampled time series of the first signal and the second sampled time series of the second signal responsive to identifying a physical co-dependence between the first signal and the second signal, the physical co-dependence between the first signal and the second signal identified based on at least one of a dependence as indicated by one or more physical factors between the first digital device and the second digital device or a common phase between the first signal and the second signal, wherein the one or more physical factors includes at least one of connectivity between the first digital device and the second digital device or a connection topology of an electric circuit of the utility grid;

select, based on the pair of signals identified based on the physical co-dependence, an estimator from a predetermined list of estimators configured for the pair of signals;

determine, based on the estimator configured for the pair of signals identified based on the physical co-dependence, a metric for the pair of signals;

compare the metric for the pair of signals with a nominal metric for the estimator configured for the pair of signals;

detect, responsive to the comparison, a deviation between the metric for the pair of signals and the nominal metric for the estimator, the detected deviation due to at least one corrupt signal; and

responsive to detection of the deviation, generate an alert that indicates the deviation and at least one of the first digital device or the second digital device connected to the utility grid that provided the at least one of the first sampled time series or the second sampled time series that form the pair of signals that deviate from the nominal metric due to the at least one corrupt signal.

13. The system of claim 12, wherein the non-conforming signal detector is further configured to:

correct, prior to determination of the metric for the pair of signals, sampling voids in at least one of the first sampled time series of the first signal or the second sampled time series of the second signal.

14. The system of claim 12, wherein the non-conforming signal detector is further configured to:

determine, based on a number of void samples, whether to void at least one of the first sampled time series of the first signal or the second sampled time series of the second signal.

15. The system of claim 12, wherein the non-conforming signal detector is further configured to:

process, prior to determining the metric for the pair of signals, at least one of the first sampled time series of the first signal or the second sampled time series of the second signal by performing at least one of;

linear trend removal, removal of spectral components with periods greater than a sample record, or spectral filtering.

16. The system of claim 12, wherein the non-conforming signal detector is further configured to:

determine the physical co-dependence between the first signal and the second signal based on the first digital device and the second digital device positioned on a same branch of a distribution circuit of the utility grid.

17. The system of claim 12, wherein the non-conforming signal detector is further configured to:

determine the physical co-dependence between the first signal and the second signal based on the first digital device positioned ahead of a branch point on a distribution circuit of the utility grid, and the second digital device positioned after the branch point.

18. The system of claim 12, wherein the estimator is based on at least one of a statistical cross-moment, a joint density approximation, a dependency quantification by entropic divergence measures, or a causality quantification and prediction by directed dependence measures.

19. The system of claim 12, wherein the non-conforming signal detector is further configured to:

identify, prior to detection of the deviation, the nominal metric using a learning process.

20. The system of claim 12, wherein the non-conforming signal detector is further configured to:

provide a command to at least one of the first digital device or the second digital device responsive to detecting the deviation.

21. The system of claim 12, wherein the non-conforming signal detector is further configured to at least one:

disable at least one of the first digital device or the second digital device responsive to detecting the deviation;

reset at least one of the first digital device or the second digital device responsive to detecting the deviation;

or

update at least one of the first digital device or the second digital device responsive to detecting the deviation.

22. The system of claim 12, wherein the non-conforming signal detector is further configured to:

prevent, responsive to detecting the deviation, a sampled time series of a signal measured by at least one of the first digital device or the second digital device from being used to adjust a tap setting at a voltage regulator of the utility grid.