USING PLANNING TO CONTROL DEMAND RESPONSE AND SUPPLY CHOICES IN A MANAGED ELECTRICAL SYSTEM

• US 20130123994A1
• Filed: 11/15/2011
• Published: 05/16/2013
• Est. Priority Date: 11/15/2011
• Status: Active Grant

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Palo Alto Research Center, Inc. (Xerox Holdings Corp.)
• Inventors: Greene, Daniel H., Hindi, Haitham A.S., Price, Robert R., Preas, Bryan T., Hanley, John
• Granted Patent: US 8,924,035 B2
• Time in Patent Office: Days
• US Class Current: 700/291
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: H02J 1/14 Balancing the load in a network
• CPC Class Codes: H02J 2310/44 for aircrafts
• CPC Class Codes: H02J 4/00 Circuit arrangements for mains or distribution networks not specified as ac or dc
• CPC Class Codes: Y02T 50/50 On board measures aiming to increase energy efficiency
• CPC Class Codes: Y04S 20/221 General power management systems

Abstract

One embodiment of the present invention provides an energy-management system for managing energy within a predominantly closed power system. The system includes an identifying mechanism configured to identify a number of components coupled to the energy-management system, a receiving mechanism configured to receive current status information of the components, an evaluating mechanism configured to evaluate future energy need, a planning mechanism configured to plan future energy activities based on the energy need and the current status information, and a controlling mechanism configured to control operations of the components based on the planned energy activities.

Claims

1. A method for managing energy within a predominantly closed power system, comprising:

identifying a number of components coupled to an energy-management system;

receiving current status information of the components;

evaluating future energy need;

planning future energy activities based on the energy need and the current status information; and

controlling operations of the components based on the planned energy activities.

2. The method of claim 1, wherein the components include at least one energy supply and one load.

3. The method of claim 1, wherein the energy activities include modifications of energy generation and/or energy consumption.

4. The method of claim 3, wherein the modifications include one or more of:

starting or stopping of energy sources;

charging or discharging of energy storage devices; and

demand response.

5. The method of claim 1, wherein evaluating the future energy need involves computing a performance model for a component.

6. The method of claim 5, wherein the performance model is computed by a driver associated with the component.

7. The method of claim 5, wherein the performance model includes one or more variables corresponding to:

power, cost, and/or deficit.

8. The method of claim 1, wherein planning future energy activities involves implementing a model predictive control (MPC) scheme.

9. The method of claim 8, wherein implementing the MPC scheme involves:

determining a finite time horizon;

defining an optimization problem the goal of which is to minimize the cost subject to the deficit being zero at the end of the finite time horizon; and

solving the optimization problem.

10. The method of claim 9, wherein solving the optimization problem involves using an A* search algorithm or a mixed integer program (MIP) solver.

11. The method of claim 9, wherein solving the optimization problem involves using an “

anytime”

algorithm, thereby allowing the optimization problem to be solved within a predetermined amount of time.

12. The method of claim 1, wherein the predominantly closed power system is one of:

a power system of an aircraft;

a power system of a ship;

a power system for a remote base; and

a micro grid.

13. An energy-management system for managing energy within a predominantly closed power system, comprising

an identifying mechanism configured to identify a number of components coupled to the energy-management system;

a receiving mechanism configured to receive current status information of the components;

an evaluating mechanism configured to evaluate future energy need;

a planning mechanism configured to plan future energy activities based on the energy need and the current status information; and

a controlling mechanism configured to control operations of the components based on the planned energy activities.

14. The energy-management system of claim 13, wherein the components include at least one energy supply and one load.

15. The energy-management system of claim 13, wherein the energy activities include modifications of energy generation and/or energy consumption.

16. The energy-management system of claim 15, wherein the modifications include one or more of:

starting or stopping of energy sources;

charging or discharging of energy storage devices; and

demand response.

17. The energy-management system of claim 13, wherein the evaluating mechanism is configured to compute a performance model for a component.

18. The energy-management system of claim 17, wherein the evaluating mechanism comprises a driver associated with the component configured to compute the performance model.

19. The energy-management system of claim 17, wherein the performance model includes one or more variables corresponding to:

power, cost, and/or deficit.

20. The energy-management system of claim 13, wherein the planning mechanism is further configured to

implement a model predictive control (MPC) scheme.

21. The energy-management system of claim 20, wherein while implementing the MPC scheme the planning mechanism is further configured to:

determine a finite time horizon;

define an optimization problem the goal of which is to minimize the cost subject to the deficit being zero at the end of the finite time horizon; and

solve the optimization problem.

22. The energy-management system of claim 21, wherein while solving the optimization problem, the planning mechanism is further configured to use an A* search algorithm or a mixed integer program (MIP) solver.

23. The energy-management system of claim 21, wherein while solving the optimization problem, the planning mechanism is further configured to use an “

anytime”

algorithm, thereby allowing the optimization problem to be solved within a predetermined amount of time.

24. The energy-management system of claim 13, wherein the predominantly closed power system is one of:

a power system of an aircraft;

a power system of a ship;

a power system for a remote base; and

a micro grid.

25. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for managing energy within a predominantly closed power system, the method comprising:

identifying a number of components coupled to an energy-management system;

receiving current status information of the components;

evaluating future energy need;

planning future energy activities based on the energy need and the current status information; and

controlling operations of the components based on the planned energy activities.