MANAGING COMPUTATIONAL WORKLOADS OF COMPUTING APPARATUSES POWERED BY RENEWABLE RESOURCES

• US 20160247085A1
• Filed: 05/02/2016
• Published: 08/25/2016
• Est. Priority Date: 09/14/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Harper, David Tennyson III, Peterson, Eric C., Harris, Shaun L., Belady, Christian L.
• Granted Patent: US 10,719,773 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09
• CPC Class Codes: G06F 1/3206 Monitoring of events, devices or parameters that trigger a change in power modality
• CPC Class Codes: G06F 1/329 by task scheduling
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

A method described herein includes an act of receiving data that is indicative of predicted weather conditions for a particular geographic region, wherein the particular geographic region has an energy generation system therein, and wherein the energy generation system utilizes at least one renewable energy resource to generate electrical power. The method also includes the act of scheduling a computational workload for at least one computer in a data center based at least in part upon the data that is indicative of the predicted weather conditions for the particular geographic region.

Claims

1. A method executed by a computing system, the method comprising:

predicting an amount of electrical power that is to be generated by a power system at a point in time between four hours and eight hours in the future, the power system generates electrical power based upon a renewable resource, the power system provides electrical power to a data center; and

scheduling a computational workload for at least one computing device in the data center based upon the predicted amount of electrical power that is to be generated by the power system at the point in time in the future.

2. The method of claim 1, further comprising:

predicting a weather condition at a location of the power system, the weather condition predicted for the point in time in the future, wherein the amount of electrical power that is to be generated by the power system at the point in time in the future is predicted based upon the weather condition.

3. The method of claim 2, wherein the power system comprises a wind turbine, and wherein the amount of electrical power that is to be generated by the power system at the point in time in the future is predicted based upon velocity of wind predicted for the point in time in the future.

4. The method of claim 3, wherein the amount of electrical power that is to be generated by the power system at the point in time in the future is predicted based upon data that is indicative of current angular velocity of a blade of the wind turbine.

5. The method of claim 2, wherein the power system comprises a solar panel, and wherein the amount of electrical power that is to be generated by the power system at the point in time in the future is predicted based upon an amount of sunlight that is predicted to incident upon the solar panel at the point in time in the future.

6. The method of claim 1, wherein scheduling the computational workload for the at least one computing device in the data center comprises scheduling the at least one computing device for maintenance at the point in time in the future.

7. The method of claim 1, wherein scheduling the computational workload for the at least one computing device in the data center comprises transferring the computational workload from the at least one computing device to another computing device in a different data center.

8. The method of claim 1, further comprising:

predicting a second amount of electrical power that is to be generated by the power system at a second point in time between one day and two days in the future; and

scheduling the computational workload for the at least one computing device in the data center based upon the predicted second amount of electrical power that is to be generated by the power system at the second point in time in the future.

9. The method of claim 1, wherein scheduling of the computational workload for the at least one computing device in the data center is further based upon a current amount of electrical power being generated by the power system.

10. The method of claim 1, wherein scheduling of the computational workload for the at least one computing device in the data center is further based upon a current workload of the at least one computing device.

11. A computing system comprising:

at least one processor; and

memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform acts comprising;

predicting a weather condition at a geographic location at a point in time that is between four hours and eight hours in the future;

predicting an amount of electrical power that is to be generated by a power system at the point in time in the future, the amount of electrical power predicted based upon the weather condition, the power system configured to generate electrical power through use of a renewable resource, the power system configured to supply electrical power to at least one computing device in a data center; and

scheduling a computational workload for the at least one computing device in the data center based upon the amount of electrical power that is to be generated by the power system at the point in time in the future.

12. The computing system of claim 11, the weather condition being wind velocity at the geographic location at the point in time in the future.

13. The computing system of claim 11, the weather condition being an amount of solar radiation that is expected to be incident upon a solar panel that is located at the geographic location.

14. The computing system of claim 11, wherein scheduling the computational workload for the at least one computing device in the data center comprises scheduling maintenance for the at least one computing device in the data center at the point in time in the future.

15. The computing system of claim 11, wherein scheduling the computational workload for the at least one computing device in the data center comprises shifting a computational task from the at least one computing device in the data center to another computing device in another data center.

16. The computing system of claim 11, wherein predicting the amount of electrical power that is to be generated by the power system at the point in time in the future is further based upon a current sensed condition of the power system.

17. The computing system of claim 16, the power system comprising a wind turbine, the current sensed condition being angular velocity of a blade of the wind turbine.

18. The computing system of claim 11, the acts further comprising:

updating the predicted amount of electrical power that is to be generated at the point in time in the future; and

updating the schedule of the computational workload responsive to updating the predicted amount of electrical power that is to be generated at the point in time in the future.

19. A system comprising:

a power system that generates electrical power based upon a renewable resource;

a data center that comprises a plurality of computing devices, wherein the power system provides the data center with electrical energy;

at least one computing device that is configured to;

generate a prediction as to an amount of electrical power that is to be output by the power system at a point in time in the future, the point in time in the future being between four and eight hours into the future; and

schedule a computational workload for at least one computing device in the data center based upon the prediction as to the amount of electrical power that is to be output by the power system at the point in time in the future.

20. The system of claim 19, wherein the power system comprises at least one of a wind turbine or a solar panel.