Valuing and optimizing scheduling of generation assets for a group of facilities

• US 20040006502A1
• Filed: 01/02/2003
• Published: 01/08/2004
• Est. Priority Date: 05/03/2002
• Status: Active Grant

• Current Assignee: Fidelity Information Services, LLC (Fidelity National Information Services Incorporated)
• Original Assignee: FIS Energy Systems, Inc. (Fidelity National Information Services Incorporated)
• Inventors: Manoliu, Mihaela, Skantze, Petter, Masiello, Ralph D.
• Granted Patent: US 7,389,209 B2
• Time in Patent Office: Days
• US Class Current: 705/8
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: H02J 3/004 Generation forecast, e.g. methods or systems for forecasting future energy generation
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid
• CPC Class Codes: Y10S 706/927 Education or instruction

Abstract

The present invention provides methods and systems for determining anticipated profit from facilities such as electrical power generation facilities, for determining values for assets based on profitability of facilities, and for determining optimal operational scheduling options for facilities. Methods and systems are provided which utilize a dynamic programming algorithm and a decision tree based model in which one or more operating constraints are implicitly modeled, facilitating computational tractability. Additionally, methods and systems are provided that utilize a dynamic programming algorithm and a decision tree based model that accounts for a combined effect of price paths with specified uncertainty as well as operational constraints. Furthermore, methods and systems are provided that address profitability, valuation, and scheduling in relation to a group, or portfolio, of facilities, accounting for liquidity factors as well as group, or global, constraints.

Claims

1. A computerized method for facilitating joint scheduling of operation of each of a plurality of facilities for at least a first time interval of a period of time, the method comprising:

determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

,

applying a dynamic optimization algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities;

determining an optimal scheduling option for each of the plurality of facilities based on anticipated optimal set of schedules; and

,

storing in a memory optimal scheduling information associated with the optimal scheduling option for each of the plurality of facilities.

2. The method of claim 1, wherein one or more constraints of the at least one specified constraint are implicitly modeled.

3. The method of claim 1, wherein each of the optimal scheduling options is selected from the group consisting of ramping down a generation rate, ramping up a generation rate, and maintaining a generation rate at a steady level.

4. The method of claim 1, wherein generating a decision tree based model comprises generating a decision tree based model including one or more implicitly modeled constraints.

5. The method of claim 4, wherein generating a decision tree based model comprises generating a decision tree based model utilizing parameters consisting of a time parameter, a price parameter, generation parameter, a runtime parameter.

6. A computerized method for determining an anticipated profitability of operation of a plurality of facilities for a period of time, the method comprising:

determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one specified control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

applying a dynamic programming algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities;

determining the anticipated profitability of the plurality of facilities based on the anticipated optimal set of schedules; and

,

storing in a memory the anticipated profitability information associated with the anticipated profitability.

7. The method of claim 6, wherein one or more constraints of the at least one specified constraint are implicitly modeled.

8. The method of claim 6, comprising determining a value of an asset based on the anticipated profitability.

9. The method of claim 6, wherein applying the dynamic programming algorithm comprises determining an optimal decision rule, for one or more of the plurality of facilities, at each of one or more nodes of each of the decision tree based models, each node representing a time in the period, and each optimal decision rule specifying an optimal dispatch option at each of the times.

10. The method of claim 6, comprising generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the one or more at least one specified control price path, the set of preliminary schedules, load obligations, and a specified liquidity function, wherein the specified liquidity function is specified in accordance with the formula:

S_h=ƒ

(I_h)

wherein S_h is a spot price for the at least one commodity at time, and I_h is a net long-short position of a participant in a market for the at least one commodity, and comprising determining I_h in accordance with the equation;

11. The method of claim 10, comprising generating the plurality of possible price paths utilizing Monte Carlo simulation.

12. The method of claim 6, wherein generating a decision tree based model comprises generating a decision tree based model including one or more implicitly modeled constraints.

13. The method of claim 12, wherein generating a decision tree based model comprises generating a decision tree based model utilizing parameters consisting of a time parameter, a price parameter, generation parameter, a runtime parameter.

14. A computer usable medium storing program code which, when executed by a computer, causes the computer to execute a computerized method for facilitating joint scheduling of operation of each of a plurality of facilities for at least a first time interval of a period of time, the method comprising:

determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one specified control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

,

applying a dynamic optimization algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities;

determining an optimal scheduling option for each of the plurality of facilities based on anticipated optimal set of schedules; and

,

storing in a memory optimal scheduling information associated with the optimal scheduling option for each of the plurality of facilities.

15. The computer usable medium of claim 14, wherein one or more constraints of the at least one specified constraint are implicitly modeled.

16. A computer usable medium storing program code which, when executed by a computer, causes the computer to execute a computerized method for determining an anticipated profitability of operation of a plurality of facilities for a period of time, the method comprising:

determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one specified control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

applying a dynamic programming algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities;

determining the anticipated profitability of the plurality of facilities based on the anticipated optimal set of schedules; and

,

storing in a memory anticipated profitability information associated with the anticipated profitability of the plurality of facilities.

17. The computer usable medium of claim 16, wherein one or more constraints of the at least one specified constraint are implicitly modeled.

18. A system for facilitating joint scheduling of operation of each of a plurality of facilities for at least a first time interval of a period of time, the system comprising:

means for determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

means for generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one specified control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

,

means for applying a dynamic optimization algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

means for generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

means for utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities;

means for determining an optimal scheduling option for each of the plurality of facilities based on anticipated optimal set of schedules; and

means for storing in a memory optimal scheduling option information associated with the optimal scheduling option for each of the plurality of facilities.

19. The system of claim 18, wherein one or more constraints of the at least one specified constraint are implicitly modeled.

20. A system for determining an anticipated profitability of operation of a plurality of facilities for a period of time, the system comprising:

means for determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

means for generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one specified control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

means for applying a dynamic programming algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

means for generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

means for utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities;

means for determining the anticipated profitability of the plurality of facilities based on the anticipated optimal set of schedules; and

,

means for storing in a memory anticipated profitability information associated with the anticipated profitability of the plurality of facilities

21. The system of claim 20, wherein one or more constraints of the at least one specified constraint are implicitly modeled.

22. A system for facilitating joint scheduling of operation of each of a plurality of facilities for at least a first time interval of a period of time, the system comprising:

a processor; and

memory accessible by the processor;

wherein the processor is programmed for;

determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one specified control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

,

applying a dynamic optimization algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities; and

,

determining an optimal scheduling option for each of the plurality of facilities based on anticipated optimal set of schedules.

23. The system of claim 22, wherein one or more constraints of the at least one specified constraint are implicitly modeled.

24. A computational method for facilitating joint scheduling of operation of each of a plurality of facilities for at least a first time interval of a period of time, the method comprising:

determining a set of preliminary anticipated optimal schedules for each of the plurality of facilities, comprising;

generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one control price path; and

,

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

,

applying a dynamic optimization algorithm to the decision tree based models to determine a set of preliminary anticipated optimal schedules, the set of preliminary anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time;

generating a set of liquidity adjusted price paths for the at least on commodity over the period of time, the set of liquidity adjusted price paths being generated based at least on the at least one specified control price path, the set of preliminary anticipated optimal schedules, and a specified liquidity function;

utilizing an optimal control price path search algorithm that utilizes iterative performance of the determining step and the generating step with updating of the at least one control price paths according to the liquidity adjusted price paths, determining an optimal control price path and an anticipated optimal set of schedules, the anticipated optimal set of schedules including a schedule for each of the plurality of facilities; and

determining an optimal scheduling option for each of the plurality of facilities based on anticipated optimal set of schedules.

25. A computerized method for facilitating joint scheduling of operation of each of a plurality of facilities for at least a first time interval of a period of time, the method comprising:

determining a set of anticipated optimal schedules for each of the plurality of facilities, comprising;

generating a decision tree based model for each of the plurality of facilities, each of the decision tree based models accounting for a combined effect, on the optimization of the scheduling of the operation of the respective facility, of;

at least one specified control price path including at least one price, over the period of time, of at least one commodity associated with the operation of each of the plurality of facilities, the at least one price of the at least one commodity being affected by the operation of each of the facilities over the period of time;

at least one specified level of uncertainty with regard to the at least one control price path; and

at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of each of the plurality of facilities; and

iteratively applying a dynamic optimization algorithm to the decision tree based models to determine a set of anticipated optimal schedules including a schedule for each of the plurality of facilities over the period of time, comprising, at each iteration;

updating the at least one specified control price path; and

applying the dynamic optimization algorithm utilizing the updated at least one specified control price path;

determining an optimal scheduling option for each of the plurality of facilities based on the set of anticipated optimal schedules; and

storing in a memory optimal scheduling information associated with the optimal scheduling option for each of the plurality of facilities.

26. The method of claim 25, wherein generating a decision tree based model comprises generating an asset model and a market model.

27. The method of claim 25, wherein iteratively applying a dynamic optimization algorithm comprises applying a dynamic optimization algorithm comprising logic for updating the at least one specified control price path based on results from a previous iteration.