Energy Management with Correspondence Based Data Auditing Signoff

• US 20130173322A1
• Filed: 12/30/2011
• Published: 07/04/2013
• Est. Priority Date: 12/30/2011
• Status: Abandoned Application

• Current Assignee: Schneider Electric USA, Inc. (Schneider Electric SE)
• Original Assignee: Schneider Electric USA, Inc. (Schneider Electric SE)
• Inventors: Gray, Anthony R.
• Application Number:
  US13/341,394
• Publication Number:
  US 20130173322A1
• Time in Patent Office: Days
• US Class Current: 705/7.13
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00017 using optical fiber
• CPC Class Codes: H02J 13/00034 the elements or equipment being or involving an electric power substation
• 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: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02P 90/82 Energy audits or management systems therefor
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• CPC Class Codes: Y04S 20/221 General power management systems
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/124 using wired telecommunication networks or data transmission busses

Abstract

Systems and methods for monitoring energy management (EM) data from at least one energy data source; detecting a data anomaly event in the EM data; determining if a resolution for the data anomaly event requires human input; and submitting a request to at least one user for human input to resolve the data anomaly event.

Claims

1. A method implemented by at least one computer upon executing programming code stored on at least one non-transitory computer-readable medium, the method comprising:

monitoring energy management (EM) data from at least one energy data source;

detecting a data anomaly event in the EM data;

determining if a resolution for the data anomaly event requires human input; and

submitting an automated request to at least one user for human input to resolve the data anomaly event; and

recording a record of the request in a database for a resolution response from the at least one user.

2. The method of claim 1, further comprising:

generating an identification for the data anomaly event;

retrieving contact information for at least one user from a contact database;

generating the request including data anomaly event information for the at least one user; and

recording the contact information and the identification in a database for a resolution response from the at least one user.

3. The method of claim 1, further comprising:

generating the request including data anomaly event information, wherein the data anomaly information includes a plurality of resolution decisions.

4. The method of claim 3, where in the request is configured to automatically generate a response that includes the user'"'"'s resolution decision selected from the plurality of resolution decisions and an identification for the data anomaly event.

5. The method of claim 1, further comprising:

classifying the data anomaly into a diagnostic class for resolution.

6. The method of claim 5, wherein the diagnostic class comprises a class selected from:

Known Good, Known Bad, and Need Human Input.

7. The method of claim 1, further comprising:

determining if a resolution response message for an outstanding request has been received.

8. The method of claim 7, further comprising:

if resolution response message has been received, associating the response with the identification in the database;

identifying a resolution response from the resolution response message; and

resolving the data anomaly event in accord with the resolution response.

9. The method of claim 7 wherein the method further comprises:

if it is determined that a resolution response message for an outstanding request has not been received, generating a subsequent correspondence request to at least one other user for human input.

10. The method of claim 2 wherein the method further comprises:

retrieving contact information for a plurality of users from a contact database;

generating the correspondence request for the plurality of users;

submitting the request to the plurality of users for human input to resolve the data anomaly event.

11. The method of claim 1 wherein the method further comprises:

submitting the at least one request to at least one user via a correspondence medium selected from the group of;

email, an SMS message, voicemail, instant messaging, and a posting to social media platform.

12. The method of claim 1 wherein the method further comprises:

acquiring associated EM attribute data related to the data anomaly event; and

submitting the at least one data anomaly event and the EM attribute data to the at least one user.

13. The method of claim 12 wherein associated EM attribute data is selected from the group including:

coincident equipment status information, maintenance management system data, a calendar of events, weather, financial information data, news data, and a history of data anomaly resolutions for a energy source.

14. The method of claim 12 wherein the method further comprises:

recording the resolution information in the resolution response message; and

associating the resolution response with a diagnostic class that does not require human input.

15. The method of claim 1 wherein the method further comprises:

receiving the EM data from a plurality of energy data sources;

detecting a plurality of data anomaly events in the EM data; and

analyzing the data from the plurality of energy data sources to determine if the data anomaly events meet at least one correlation criterion.

16. The method of claim 15 wherein the method further comprises:

aggregating the EM data from the plurality of energy data sources;

presenting at least one of the EM anomaly data events to a plurality of users for a resolution decision.

17. The method of claim 16 wherein the method further comprises:

allowing the users to see the resolution decisions of other users.

18. The method of claim 15 wherein the method further comprises:

allowing the users to see the resolution decisions of other users on a display medium selected from;

a website, via interconnected software;

a data feed, or on a social media platform.

19. A method implemented by at least one computer upon executing programming code stored on at least one non-transitory computer-readable medium comprising:

monitoring energy management (EM) data from a plurality of energy data sources;

detecting a plurality of data anomaly events in the EM data;

analyzing the data from the plurality of energy data sources to determine if the data anomaly events meet at least one correlation criterion; and

if the data anomaly events meet the correlation criterion, processing the data in accord with the correlation criterion to resolve the data anomaly events.

20. The method of claim 19 wherein the method further comprises:

aggregating the EM data from the plurality of energy data sources;

presenting at least one of the EM anomaly data events to a plurality of users for a resolution decision.

21. The method of claim 20 wherein the method further comprises:

allowing the users to see the resolution decisions of other users.

22. The method of claim 21 wherein the method further comprises:

allowing the users to see the resolution decisions of other users on a display medium selected from;

a website, via interconnected software;

a data feed, or on a social media platform.

23. A method comprising:

monitoring energy management (EM) data from an energy data source;

detecting at least one data anomaly event in the EM data;

acquiring associated EM attribute data related to the data anomaly event; and

presenting the at least one data anomaly event and the EM attribute data to a user.

24. The method of claim 23 wherein associated EM attribute data includes:

coincident equipment status information, maintenance management system data, a calendar of events, a history of data anomaly resolution for a energy source.

25. The method of claim 23 wherein the method further comprises:

receiving resolution information from a user'"'"'s resolution response; and

associating the resolution information with a diagnostic class that does not require human input.

26. An EM system for power management, the system comprising at least one computer, at least one storage device in which is stored EM data, and at least one non-transitory computer readable medium storing thereon computer code which when executed by the at least one computer causes the at least one computer to at least:

monitor energy management (EM) data from at least one energy data source;

detect a data anomaly event in the EM data;

determine if a resolution for the data anomaly event requires human input; and

submit an automated request to at least one user for human input to resolve the data anomaly event; and

record a record of the request in a database for a resolution response from the at least one user.

27. At least one non-transitory computer-readable medium that stores programming code that when executed by at least one computer, instructs the at least one computer to execute a method comprising:

monitoring energy management (EM) data from at least one energy data source;

detecting a data anomaly event in the EM data;

determining if a resolution for the data anomaly event requires human input; and

submitting an automated request to at least one user for human input to resolve the data anomaly event; and

recording a record of the request in a database for a resolution response from the at least one user.

28. An EM system for power management, the system comprising at least one computer, at least one storage device in which is stored EM data, and at least one non-transitory computer readable medium storing thereon computer code which when executed by the at least one computer causes the at least one computer to at least:

monitor energy management (EM) data from a plurality of energy data sources;

detect a plurality of data anomaly events in the EM data;

analyze the data from the plurality of energy data sources to determine if the data anomaly events meet at least one correlation criterion; and

if the data anomaly events meet the correlation criterion, processing the data in accord with the correlation criterion to resolve the data anomaly events.

29. At least one non-transitory computer-readable medium that stores programming code that when executed by at least one computer, instructs the at least one computer to execute a method comprising:

monitoring energy management (EM) data from a plurality of energy data sources;

detecting a plurality of data anomaly events in the EM data;

analyzing the data from the plurality of energy data sources to determine if the data anomaly events meet at least one correlation criterion; and

if the data anomaly events meet the correlation criterion, processing the data in accord with the correlation criterion to resolve the data anomaly events.