Building energy consumption analysis system

• US 8,756,024 B2
• Filed: 05/07/2010
• Issued: 06/17/2014
• Est. Priority Date: 05/08/2009
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Hedley, Jay, Tsypin, Boris, Raghu, Deepak
• Primary Examiner(s): Kundu, Sujoy
• Assistant Examiner(s): SUAREZ, FELIX E
• Application Number:
  US12/776,159
• Publication Number:
  US 20100286937A1
• Time in Patent Office: 1,502 Days
• Field of Search: None
• US Class Current: 702/60
• CPC Class Codes: F24F 11/46 Improving electric energy efficiency or saving
• CPC Class Codes: F24F 11/58 using Internet communication
• CPC Class Codes: F24F 11/63 Electronic processing
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: G06Q 50/08 Construction
• CPC Class Codes: Y02P 90/84 Greenhouse gas [GHG] management systems
• CPC Class Codes: Y02P 90/845 Inventory and reporting systems for greenhouse gases [GHG]

Abstract

An energy analysis system provides valuable input into building energy expenditures. The system assists with obtaining a detailed view of how energy consumption occurs in a building, what steps may be taken to lower the energy footprint, and executing detailed energy consumption analysis. The analysis may include, as examples, a balance point pair analysis to determine either or both of a heating balance point and a cooling balance point, an exception rank analysis to identify specific data (e.g., energy consumption data) in specific time intervals for further review, or other analysis. The system may display the analysis results on a user interface.

Claims

1. A method for energy analysis comprising:

establishing, by a processor, a data connection from a network operations center through an energy data connectivity interface to an energy data source;

obtaining, by a processor, energy data at the network operations center through the data connection to the energy data source;

performing, by the processor, an energy analysis in the network operations center on the energy data to produce an analysis result, where performing the energy analysis comprises;

determining, by the processor, a balance point set from the energy data as the analysis result, the balance point set comprising a heating balance point and a cooling balance point, wherein the heating balance point is a temperature above which a building is not heated and the cooling balance point is a temperature below which the building is not cooled; and

generating and displaying, by the processor, a user interface on a display, the user interface including the analysis result.

2. The method of claim 1, where determining a balance point set comprises:

determining both of a heating balance point search window into the energy data and a cooling balance point search window into the energy data.

3. The method of claim 2, where determining a balance point set comprises:

executing either or both of a correlation analysis of the energy data within the heating balance point window and a correlation analysis of the energy data within the cooling balance point window.

4. The method of claim 3, where executing the correlation analysis comprises:

executing a correlation analysis between temperature and energy consumption to find a best fit correlation by performing a linear regression using the least squares method, with ‘

n’

independent variables and one dependent variable.

5. The method of claim 3, where executing the correlation analysis comprises:

executing the correlation analysis at each step of a pre-selected temperature delta through both of the heating balance point window and the cooling balance point window.

6. An energy analysis system comprising:

a processor; and

a memory coupled to the processor, the memory comprising;

energy analysis logic that, when executed by the processor, causes an energy analysis system to;

establish a data connection from a network operations center through an energy data connectivity interface to an energy data source;

obtain energy data at the network operations center through the data connection to the energy data source;

perform an energy analysis in the network operations center on the energy data to produce an analysis result, where the energy analysis comprises;

determining a balance point set from the energy data as the analysis result, the balance point set comprising a heating balance point and a cooling balance point, wherein the heating balance point is a temperature above which a building is not heated and the cooling balance point is a temperature below which the building is not cooled; and

generate and display a user interface on a display, the user interface including the analysis result.

7. The system of claim 6, where the energy analysis logic further causes the energy analysis system to obtain either or both of a heating balance point search window and a cooling balance point search window.

8. The system of claim 7, where the energy analysis logic further causes the energy analysis system to:

execute either or both of a correlation analysis of the energy data within the heating balance point window and a correlation analysis of the energy data within the cooling balance point window.

9. The system of claim 8, where the energy analysis logic further causes the energy analysis system to:

execute a correlation analysis between temperature and energy consumption to find a best fit correlation by performing a linear regression using the least squares method, with ‘

n’

independent variables and one dependent variable.

10. The system of claim 8, where the energy analysis logic further causes the energy analysis system to:

execute the correlation analysis at each step of a pre-selected temperature delta through either or both of the heating balance point window and the cooling balance point window.

11. A method for energy analysis comprising:

establishing, by a processor, a data connection from a network operations center through an energy data connectivity interface to an energy data source;

obtaining, by the processor, energy data at the network operations center through the data connection to the energy data source;

performing, by the processor, an energy analysis in the network operations center on the energy data to produce an analysis result, where performing the energy analysis comprises;

determining, by the processor, a heating balance point and a cooling balance point, wherein the heating balance point is a temperature above which a building is not heated and the cooling balance point is a temperature below which the building is not cooled;

determining, by the processor, building comparison baseline data within the energy data;

determining, by the processor, actual consumption data within the energy data;

determining, by the processor, as the analysis result, an exception rank by;

determining, by the processor, a comparison standard deviation of the energy data within a time interval in the building comparison baseline data; and

comparing, by the processor, the comparison standard deviation data and the actual consumption, the exception rank identifying specific data in the actual consumption for further review; and

generating and displaying, by the processor, a user interface on a display, the user interface including the analysis result.

12. The method of claim 11, where determining an exception rank comprises:

determining a comparison average of the energy data within the time interval in the building comparison baseline data.

13. The method of claim 12, where determining an exception rank further comprises:

determining an actual consumption average of the energy data within the time interval in the actual consumption data.

14. The method of claim 13, where determining an exception rank further comprises:

accessing an exception rank definition that comprises a mapping of a statistical parameter to exception ranks; and

assigning the exception rank to the time interval according to the mapping.

15. The method of claim 14, where the statistical parameter comprises a standard deviation window with respect to the comparison average.

16. An energy analysis system comprising:

a processor; and

a memory coupled to the processor, the memory comprising;

energy analysis logic that, when executed by the processor, causes an energy analysis system to;

establish a data connection from a network operations center through an energy data connectivity interface to an energy data source;

obtain energy data at the network operations center through the data connection to the energy data source;

perform an energy analysis in the network operations center on the energy data to produce an analysis result, where the energy analysis comprises;

determining a heating balance point and a cooling balance point, wherein the heating balance point is a temperature above which a building is not heated and the cooling balance point is a temperature below which the building is not cooled;

determining building comparison baseline data within the energy data;

determining actual consumption data within the energy data;

determining, as the analysis result, an exception rank by;

determining a comparison standard deviation of the energy data within a time interval in the building comparison baseline data; and

comparing the comparison standard deviation data and the actual consumption data, the exception rank identifying specific data in the actual consumption data for further review; and

generate and display a user interface on a display, the user interface including the analysis result.

17. The system of claim 16, where the energy analysis logic further causes the energy analysis system to:

determine a comparison average of the energy data within the time interval in the building comparison baseline data.

18. The system of claim 17, where the energy analysis logic further causes the energy analysis system to:

determine an actual consumption average of the energy data within the time interval in the actual consumption data.

19. The system of claim 18, where the energy analysis logic further causes the energy analysis system to:

access an exception rank definition that comprises a mapping of a statistical parameter to exception ranks; and

assign an exception rank to the time interval according to the mapping.

20. The method of claim 19, where the statistical parameter comprises a standard deviation window with respect to the comparison average.