Method and apparatus for customized energy policy based on energy demand estimation for client systems

1. An information handling system comprising:

an application processor executing instructions for an intelligent energy management system to determine energy demand estimation for a group of client information handling systems based on component device utilization data from at least a portion of the group of client information handling systems;

a power policy engine determining, via the application processor, a timeseries power cost estimation for the group of client information handling systems, wherein the timeseries power cost estimation for the group of client information handling systems is based on the energy demand estimation, a day and time of energy usage, and an energy rate for the time and a location of energy usage;

a memory device storing an energy budget limitation for the group of client information handling systems and a component device utilization data record associated with one of a plurality of component devices of a plurality of power policy controlled client information handling systems within the group of information handling systems;

the power policy engine comparing the timeseries power cost estimation for the group of client information handling systems with the energy budget limitation;

the power policy engine determining a power policy to limit utilization of the one of the plurality of component devices within the plurality of power policy controlled client information handling systems based on the component device utilization data record associated with the one of the plurality of component devices when the power cost estimation meets or exceeds the energy budget limitation; and

a network interface device for transmitting the power policy to limit utilization of the one of the plurality of component devices within each of the plurality of power policy controlled client information handling systems to the plurality of power policy controlled client information handling system.

2. The system of claim 1 , wherein the component device utilization data includes power consumption measurements for a plurality of component devices including component devices selected from a group including a CPU/chipset component, a GPU component, a battery charger component, a display component, or a network interface component.

3. The system of claim 1 , wherein the power policy engine determines a power policy to limit utilization of a battery charger component for the power policy controlled client information handling system during a time period when power cost estimation of energy demand for the group of client information handling systems meets or exceeds the energy budget limitation.

4. The system of claim 3 , wherein the power policy to limit utilization of a battery charger component includes limiting battery charging to a battery power level sufficient to accommodate future energy demand estimation levels for the power policy controlled client information handling system for a time period until power cost estimation of energy demand for the group of client information handling systems is projected to fall below the energy budget limitation.

5. The system of claim 1 , wherein the component device utilization data associated with the at least one component device upon which the power policy engine selects the power policy to limit utilization of the at least one component device of the power policy controlled client information handling system includes a productivity index ranking of the at least one component device.

6. The system of claim 1 , wherein the power policy engine determines the power policy to limit utilization of the at least one component device for a plurality of power policy controlled client information handling system.

7. The system of claim 6 , wherein the power policy engine selects the plurality of power policy controlled client information handling systems subject to the power policy based on productivity index ranking classification of the selected plurality of power policy controlled client information handling systems.

8. The system of claim 7 , wherein the power policy engine selects the plurality of power policy controlled client information handling systems subject to the power policy further based on application of a productivity index boundary to productivity index rankings.

9. A computer implemented method comprising:

executing, via an application processor, instructions of an intelligent energy management system to determine energy demand estimation based on a component device utilization data record associated with one of a plurality of component devices of a plurality of power policy controlled client information handling systems within a group of client information handling systems received from at least a portion of the group of client information handling systems;

determining, via a power policy engine operating on the application processor, a power cost estimation for the group of client information handling systems, wherein the power cost estimation for the group of client information handling systems is based on the energy demand estimation, a day and time of energy usage, and an energy rate for the time and a location of energy usage;

comparing the power cost estimation with an energy budget limitation for the group of client information handling systems;

determining a power policy to limit utilization of the one of the plurality of component devices based on the component device utilization data record associated with the one of the plurality of component devices when the power cost estimation meets or exceeds the energy budget limitation; and

transmitting, via a network interface device, the power policy to limit utilization of the one of the plurality of component devices to the plurality of power policy controlled client information handling systems.

10. The method of claim 9 , wherein the component device utilization data includes power consumption measurements for a plurality of component devices including component devices selected from a group including a CPU/chipset component, a GPU component, a battery charger component, a display component, or a network interface component.

11. The method of claim 9 further comprising:

selecting the at least one component device limited under the power policy based on a productivity index ranking for the selected component device.

12. The method of claim 9 , wherein the power policy engine determines the power policy to switch at least one power policy controlled client information handling system to a CPU power state other than the CPU operating state.

13. The method of claim 9 further comprising:

selecting the plurality of power policy controlled client information handling systems limited under the power policy based on a productivity index ranking class for the plurality of power policy controlled client information handling systems.

14. The method of claim 9 , wherein the power cost estimation determined via the power policy engine is a time-series power cost estimation.

15. The method of claim 14 , further comprising:

determining, via the power policy engine, a daily peak need timeframe from the time-series power cost estimation; and

determining a power policy to limit utilization of at least one component device of a plurality of power policy controlled client information handling systems during the daily peak need timeframe.

16. An information handling system comprising:

a network adapter for receiving component device utilization data from a group of client information handling systems in the enterprise including active event times and intervals between active event times for the group of client information handling systems;

a memory device for storing component device utilization data record associated with one of a plurality of component devices received from the group of client information handling systems;

a memory device storing a component device utilization data record associated with one of a plurality of component devices of a plurality of power policy controlled client information handling systems within the group of client information handling systems;

an application processor executing instructions of an intelligent energy management system for determining energy demands for an enterprise, wherein the application processor determines a probability density of active event times for the group of client information handling systems; and

a power policy engine determining, via an application processor, a power policy to switch a system power state based on a recently measured active event time for the power policy controlled client information handling systems, wherein the recently measured active event time is less than or equal to an active event time having a first minimum probability threshold level in the power density of active event times, and wherein switching the system power state includes limiting utilization of the one of the plurality of component devices of each of the power policy controlled client information handling systems based on the component device data record associated with the one of the plurality of component devices.

17. The system of claim 16 , wherein the power policy engine determines the power policy to switch to a first system power state based on a recently measured active event time for the client information handling system, wherein the recently measured active event time is less than or equal to an active event time having a first minimum probability threshold level.

18. The system of claim 16 , wherein the power policy engine further determines the power policy to switch to a second system power state based on the recently measured active event time for the client information handling system, wherein the recently measured active event time is less than or equal to an active event time having a second minimum probability threshold level greater than the first minimum probability threshold, and wherein the second system power state is to turn off a display of the client information handling system.

19. The system of claim 16 , wherein the application processor determines a probability density of intervals between active event times for the client information handling systems, and wherein the power policy engine determines the power policy to switch to a second system power state based on a recently measured interval between active event times for the client information handling system exceeding a threshold level interval between active event times.

20. The system of claim 16 , wherein the second system power state includes a sleep mode.