Method and system to co-optimize utilization of demand response and energy storage resources

• US 9,209,625 B2
• Filed: 04/20/2012
• Issued: 12/08/2015
• Est. Priority Date: 04/20/2012
• Status: Active Grant

• Current Assignee: GE Digital Holdings LLC (GE Aerospace)
• Original Assignee: General Electric Company
• Inventors: Tyagi, Rajesh, Fisher, Rayette Ann, Black, Jason Wayne
• Primary Examiner(s): Ali, Mohammad
• Assistant Examiner(s): Pan, Yuhui R
• Application Number:
  US13/451,851
• Publication Number:
  US 20130282193A1
• Time in Patent Office: 1,327 Days
• Field of Search: 700/291
• US Class Current: 1/1
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: H02J 3/28 Arrangements for balancing of the load in a network by storage of energy
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

Method and system to provide co-optimized utilization of demand response and energy storage resources in an electrical grid system. The system may include a module to evaluate a marginal savings relative to a dispatch cost, if a demand response event is performed. The system may further include a module to evaluate a marginal savings relative to the dispatch cost, if an energy storage event is performed, and a controller including circuitry may be configured to determine a control strategy to perform a dispatch including a demand response event and/or an energy storage event, based at least in part on the respective marginal savings of the demand response event and/or the energy storage event, which may be selected to co-optimize an integrated utilization of the demand response and energy storage resources to meet a given objective.

Claims

1. A method to provide co-optimized utilization of demand response and energy storage resources in an electrical grid system, comprising:

obtaining a grid system load;

estimating a dispatch cost in connection with the grid system load from energy supply cost curves stored in a database;

evaluating a marginal savings relative to the dispatch cost if a demand response event is performed, wherein the evaluating of marginal savings regarding a demand response event comprises estimating at least one aggregate demand response profile for each potential group of demand response participants, wherein the evaluating of marginal savings regarding a demand response event for each potential group of demand response participants comprises

based on a respective aggregate profile of a respective demand response group being evaluated, adjusting an original load forecast;

revising a dispatch cost based on the adjusted load forecast;

calculating a savings in the dispatch cost relative to the original load forecast;

subtracting an option or threshold cost of the demand response event from the calculated savings to determine a net savings; and

selecting a demand response group with a highest normalized savings, which meets each load-reduction constraint to which the given objective may be subject;

evaluating a marginal savings relative to the dispatch cost if an energy storage event is performed;

determining a control strategy to perform a dispatch comprising a demand response event and/or an energy storage event, which is selected to co-optimize an integrated utilization of the demand response and energy storage resources to meet a given objective based at least in part on the respective marginal savings of the demand response event and/or the energy storage event, wherein said control strategy is further based on parameters indicative of an aggregate of hybrid operational capabilities resulting from the integrated utilization of the demand response and energy storage resources relative to the given objective; and

performing a dispatch consistent with the determined control strategy.

2. The method of claim 1, wherein the given objective comprises a maximization of total savings in connection with the performed dispatch.

3. The method of claim 1, wherein the given objective comprises a maximization of total savings in connection with the performed dispatch subject to at least one or more load-reduction constraints.

4. The method of claim 3, wherein the load-reduction constraint is selected from the group consisting of a ramping rate, a defined load shape, a defined load limit, and a combination of the foregoing constraints.

5. The method of claim 1, further comprising, evaluating parameters indicative of the aggregate of hybrid operational capabilities, which remain subsequent to the performed dispatch.

6. The method of claim 1, wherein the evaluating of marginal savings regarding an energy storage event comprises estimating at least one profile of increments of electrical energy, which can be extracted during a dispatch period from each energy storage resource.

7. The method of claim 6, wherein the evaluating of marginal savings regarding an energy storage event for each energy storage resource comprises:

based on an estimated increment of electrical energy from a respective energy storage resource being evaluated, adjusting a load forecast relative to an original load forecast;

revising a dispatch cost based on the adjusted load forecast;

calculating a savings in the dispatch cost relative to the original load forecast;

subtracting a cost of the energy storage event from the calculated savings to determine a net savings;

selecting an energy storage resource with a highest normalized savings.

8. The method of claim 7, wherein the selecting further comprises selecting an energy storage resource, which meets each load-reduction constraint to which the given objective may be subject.

9. The method of claim 7, wherein the control strategy is further configured to determine a charging schedule for a selected energy resource.

10. The method of claim 1, wherein the control strategy is configured to determine a quantitative proportion of demand response and energy storage resources and a temporal schedule for the demand response event and/or the energy storage event.

11. The method of claim 5, further comprising iteratively performing the evaluating of marginal savings to respectively determine a next demand response event and/or a next energy storage event to perform, and dynamically adjusting the control strategy based on the respective marginal savings of the next demand response and/or the next energy storage event, wherein said control strategy is further dynamically adjusted based on the parameters indicative of the aggregate of hybrid operational capabilities, which remain available.

12. The method of claim 1, wherein the control strategy comprises determining a sequence of dispatches to be performed over a time horizon comprising a corresponding sequence of events comprising at least one of a demand response event and an energy storage event.

13. A system to provide co-optimized utilization of demand response and energy storage resources in an electrical grid system, the system comprising:

a module to obtain a grid system load;

a module to estimate a dispatch cost in connection with the grid system load from energy supply cost curves stored in a database;

a module to evaluate a marginal savings relative to the dispatch cost if a demand response event is performed, wherein the module to evaluate marginal savings regarding a demand response event comprises a module configured to estimate at least one aggregate demand response profile for each potential group of demand response participants, wherein the module to evaluate marginal savings regarding a demand response event for each potential group of demand response participants comprises;

a module to adjust an original load forecast based on a respective aggregate profile of a respective demand response group being evaluated;

a module to revise a dispatch cost based on the adjusted load forecast;

a module to calculate a savings in the dispatch cost relative to the original load forecast;

a module to subtract an option or threshold cost of the demand response event from the calculated savings to determine a net savings; and

a module to select a demand response group with a highest normalized savings, which meets each load-reduction constraint to which the given objective may be subject;

a module to evaluate a marginal savings relative to the dispatch cost if an energy storage event is performed;

a controller comprising circuitry configured to determine a control strategy to perform a dispatch comprising a demand response event and/or an energy storage event, which is selected to co-optimize an integrated utilization of the demand response and energy storage resources to meet a given objective based at least in part on the respective marginal savings of the demand response event and/or the energy storage event, wherein said control strategy is further based on parameters indicative of an aggregate of hybrid operational capabilities resulting from the integrated utilization of the demand response and energy storage resources relative to the given objective; and

a module to perform a dispatch consistent with the determined control strategy.

14. The system of claim 13, wherein the given objective comprises a maximization of total savings in connection with the performed dispatch.

15. The system of claim 13, wherein the given objective comprises a maximization of total savings in connection with the performed dispatch subject to at least one or more load-reduction constraints.

16. The system of claim 15, wherein the load-reduction constraint is selected from the group consisting of a ramping rate, a defined load shape, a defined load limit, and a combination of the foregoing constraints.

17. The system of claim 13, further comprising a module to evaluate parameters indicative of the aggregate of hybrid operational capabilities, which remain subsequent to the performed dispatch.

18. The system of claim 13, wherein the module to evaluate marginal savings regarding an energy storage event comprises a module to estimate at least one profile of increments of electrical energy, which can be extracted during a dispatch period from each energy storage resource.

19. The system of claim 18, wherein the module to evaluate marginal savings regarding an energy storage event for each energy storage resource comprises:

a module to adjust a load forecast relative to an original load forecast, based on an estimated increment of electrical energy from a respective energy storage resource being evaluated;

a module to revise a dispatch cost based on the adjusted load forecast;

a module to calculate a savings in the dispatch cost relative to the original load forecast;

a module to subtract a cost of the energy storage event from the calculated savings to determine a net savings; and

a module to select an energy storage resource with a highest normalized savings.

20. The system of claim 19, wherein the module to select the energy storage resource is configured to select an energy storage resource, which meets each load-reduction constraint to which the given objective may be subject.

21. The system of claim 18, wherein the control strategy is further configured to determine a charging schedule for a selected energy resource.

22. The system of claim 13, wherein the control strategy is configured to determine a quantitative proportion of demand response and energy storage resources and a temporal schedule for the demand response event and/or the energy storage event.

23. The system of claim 13, wherein the controller is configured to iteratively perform a respective evaluation of marginal savings to determine a next demand response event and/or a next energy storage event to perform, and dynamically adjust the control strategy based on the respective marginal savings of the next demand response and/or the next energy storage event, wherein said control strategy is further dynamically adjusted based on the parameters indicative of the aggregate of hybrid operational capabilities, which remain available.