METHOD FOR PREDICTING POWER USAGE EFFECTIVENESS AND DATA CENTER INFRASTRUCTURE EFFICIENCY WITHIN A REAL-TIME MONITORING SYSTEM

• US 20100049494A1
• Filed: 08/17/2009
• Published: 02/25/2010
• Est. Priority Date: 08/15/2008
• Status: Active Grant

• Current Assignee: Bentley Systems Incorporated
• Original Assignee: EDSA Corporation
• Inventors: Needle, Barry, Meagher, Kevin, Radibratovic, Branislav
• Granted Patent: US 8,401,833 B2
• Time in Patent Office: Days
• US Class Current: 703/13
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202

Abstract

A system for making real-time predictions about power usage efficiency (PUE) and/or data center infrastructure efficiency (DCiE) of an electrical system comprises a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the electrical system; an analytics server communicatively connected to the data acquisition component and comprising a virtual system modeling engine configured to generate predicted data output for the electrical system using a virtual system model of the electrical system, an analytics engine configured to monitor the real-time data output and the predicted data output of the electrical system, and a PUE/DCiE simulation engine configured to use the virtual system model updated based in the real-time data to forecast the PUE/DCiE.

Claims

1. A system for making real-time predictions about power usage efficiency (PUE) of an electrical system, comprising:

a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the electrical system;

an analytics server communicatively connected to the data acquisition component, comprising;

a virtual system modeling engine configured to generate predicted data output for the electrical system using a virtual system model of the electrical system,

an analytics engine configured to monitor the real-time data output and the predicted data output of the electrical system, and

a PUE simulation engine configured to use the virtual system model updated based on the real-time data to forecast the PUE.

2. The system for making real-time predictions about PUE of an electrical system, as recited in claim 1, further comprising a client terminal communicatively connected to the analytics server and configured to communicate the forecasted PUE.

3. The system for making real-time predictions about PUE of an electrical system, as recited in claim 1, wherein the forecasted PUE is communicated by way of graphics on a display interfaced with the client terminal.

4. The system for making real-time predictions about PUE of an electrical system, as recited in claim 1, wherein the forecasted PUE is communicated by way of text on a display interfaced with the client terminal.

5. The system for making real-time predictions about PUE of an electrical system, as recited in claim 1, wherein the forecasted PUE is communicated by way of synthesized speech generated by the client terminal.

6. The system for making real-time predictions about PUE of an electrical system, as recited in claim 1, wherein the forecasted PUE is communicated by way of a paper report generated by a printing device interfaced with the client terminal.

7. The system for making real-time predictions about PUE of an electrical system, as recited in claim 1, wherein the PUE simulation engine is further configured to use the virtual system model updated based on the real-time data to forecast data center infrastructure efficiency (DCiE).

comprising a client terminal communicatively connected to the analytics server and configured to communicate the forecasted PUE

8. The system for making real-time predictions about PUE of an electrical system, as recited in claim 1, wherein the analytics server is configured to:

create a base-line PUE model of the electrical system; and

calculate the PUE of the electrical system using the base-line PUE model.

9. The system for making real-time predictions about PUE of an electrical system, as recited in claim 8, wherein the analytics server is further configured to:

create a calibrated PUE model of the electrical system; and

calculate the PUE of the electrical system using the calibrated PUE model.

10. The system for making real-time predictions about PUE of an electrical system, as recited in claim 9, wherein the analytics server is further configured to:

compare the PUE calculated from the calibrated PUE model with the PUE calculated from the base-line PUE model to validate the base-line model.

11. The system for making real-time predictions about PUE of an electrical system, as recited in claim 10, wherein the PUE values from the calibrated model and base-line model are within a predetermined range.

12. The system for making real-time predictions about PUE of an electrical system, as recited in claim 10, wherein the analytics server is further configured to:

update the calibrated PUE model with a first modification to the electrical system; and

calculate the PUE of the electrical system using the updated calibrated PUE model.

13. The system for making real-time predictions about PUE of an electrical system, as recited in claim 12, wherein the analytics server is further configured to:

update the calibrated PUE model with a second modification to the electrical system; and

calculate the PUE of the electrical system using the updated calibrated PUE model.

14. A system for making real-time predictions about data center infrastructure efficiency (DCiE) of an electrical system, comprising:

a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the electrical system;

an analytics server communicatively connected to the data acquisition component, comprising;

a virtual system modeling engine configured to generate predicted data output for the electrical system using a virtual system model of the electrical system,

an analytics engine configured to monitor the real-time data output and the predicted data output of the electrical system, and

a DCiE simulation engine configured to use the virtual system model updated based on the real-time data to forecast the DCiE.

15. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 14, further comprising a client terminal communicatively connected to the analytics server and configured to communicate the forecasted DCiE.

16. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 14, wherein the forecasted DCiE is communicated by way of graphics on a display interfaced with the client terminal.

17. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 14, wherein the forecasted DCiE is communicated by way of text on a display interfaced with the client terminal.

18. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 14, wherein the analytics server is configured to:

create a base-line DCiE model of the electrical system; and

calculate the DCiE of the electrical system using the base-line DCiE model.

19. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 18, wherein the analytics server is further configured to:

create a calibrated DCiE model of the electrical system; and

calculate the DCiE of the electrical system using the calibrated DCiE model.

20. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 19, wherein the analytics server is further configured to:

compare the DCiE calculated from the calibrated DCiE model with the DCiE calculated from the base-line DCiE model to validate the base-line model.

21. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 20, wherein the DCiE values from the calibrated model and base-line model are within a predetermined range.

22. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 20, wherein the analytics server is further configured to:

update the calibrated DCiE model with a first modification to the electrical system; and

calculate the DCiE of the electrical system using the updated calibrated DCiE model.

23. The system for making real-time predictions about DCiE of an electrical system, as recited in claim 22, wherein the analytics server is further configured to:

update the calibrated DCiE model with a second modification to the electrical system; and

calculate the DCiE of the electrical system using the updated calibrated DCiE model.

24. A computer-readable medium having instructions thereon, that when executed, cause a computer to perform a method comprising:

creating a base-line PUE model of the electrical system; and

calculating the PUE of the electrical system using the base-line PUE model.

25. The computer-readable medium of claim 24, wherein the instructions further cause a computer to perform the method comprising:

creating a calibrated PULE model of the electrical system; and

calculating the PUE of the electrical system using the calibrated PUE model.

26. The computer-readable medium of claim 25, wherein the instructions further cause a computer to perform the method comprising:

validating the base-line PUE model;

updating the calibrated PUE model with a modification to the electrical system; and

calculating the PUE of the electrical system using the updated calibrated PUE model.