Using planning to control demand response and supply choices in a managed electrical system

• US 8,924,035 B2
• Filed: 11/15/2011
• Issued: 12/30/2014
• 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
• Primary Examiner(s): Masinick, Michael D
• Application Number:
  US13/297,068
• Publication Number:
  US 20130123994A1
• Time in Patent Office: 1,141 Days
• Field of Search: 700/286, 700295-297
• US Class Current: 700/295
• 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 closed power system, comprising:

identifying a number of components within the closed power system coupled to an energy-management system, wherein the components include at least an energy supply and a load;

receiving current status information of the components;

evaluating a future energy need over a finite time horizon;

computing, for the finite time horizon, a cost function which includes an energy-generation cost associated with the energy supply and a disutility associated with the load;

calculating, for the finite time horizon, a deficit accumulated by the load during one or more demand response processes;

planning future energy activities based on the energy need and the current status information to minimize the cost function, over the finite time horizon, subject to a constraint for reducing the deficit to zero by end of the time horizon; and

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

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

3. The method of claim 2, wherein the modifications include one or more of:

starting or stopping of energy sources;

charging or discharging of energy storage devices; and

demand response.

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

5. The method of claim 4, wherein the performance model is computed by a driver associated with the component.

6. The method of claim 4, wherein the performance model includes one or more variables corresponding to:

power, cost, and/or deficit.

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

8. The method of claim 7, wherein implementing the MPC scheme involves using an A* search algorithm or a mixed integer program (MIP) solver.

9. The method of claim 7, wherein implementing the MPC scheme involves using an “

anytime”

algorithm, thereby allowing an optimization problem defined by the MPC scheme to be solved within a predetermined amount of time.

10. The method of claim 1, wherein the 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.

11. 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, wherein the components include at least an energy supply and a load;

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

an evaluating mechanism configured to evaluate future energy need over a finite time horizon;

a cost-function-computation mechanism configured to compute, for the finite time horizon, a cost function which includes an energy-generation cost associated with the energy supply and a disutility associated with the load;

a calculation mechanism configured to calculate, for the finite time horizon, a deficit accumulated by the load during one or more demand response processes;

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

wherein while planning the future energy activities, the planning mechanism is further configured to minimize the cost function, over the finite time horizon, subject to a constraint for reducing the deficit to zero by end of the time horizon; and

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

12. The energy-management system of claim 11, wherein the energy activities include modifications of energy generation and/or energy consumption.

13. The energy-management system of claim 12, wherein the modifications include one or more of:

starting or stopping of energy sources;

charging or discharging of energy storage devices; and

demand response.

14. The energy-management system of claim 11, wherein the evaluating mechanism is configured to compute a performance model for a component.

15. The energy-management system of claim 14, wherein the evaluating mechanism comprises a driver associated with the component configured to compute the performance model.

16. The energy-management system of claim 14, wherein the performance model includes one or more variables corresponding to:

power, cost, and/or deficit.

17. The energy-management system of claim 11, wherein the planning mechanism is further configured to

implement a model predictive control (MPC) scheme.

18. The energy-management system of claim 17, wherein while implementing the MPC scheme, the planning mechanism is further configured to use an A* search algorithm or a mixed integer program (MIP) solver.

19. The energy-management system of claim 17, wherein while implementing the MPC scheme, the planning mechanism is further configured to use an “

anytime”

algorithm, thereby allowing an optimization problem defined by the MPC scheme to be solved within a predetermined amount of time.

20. The energy-management system of claim 11, wherein the 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.

21. 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, wherein the components include at least an energy supply and a load;

receiving current status information of the components;

evaluating a future energy need over a finite time horizon;

computing, for the finite time horizon, a cost function which includes an energy-generation cost associated with the energy supply and a disutility associated with the load;

calculating, for the finite time horizon, a deficit accumulated by the load during one or more demand response processes;

planning future energy activities based on the energy need and the current status information to minimize the cost function, over the finite time horizon, subject to a constraint for reducing the deficit to zero by end of the time horizon; and

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