RESOURCE COST OPTIMIZATION SYSTEM, METHOD, AND PROGRAM

• US 20120239453A1
• Filed: 03/09/2012
• Published: 09/20/2012
• Est. Priority Date: 03/18/2011
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Osogami, Takayuki
• Granted Patent: US 9,196,010 B2
• Time in Patent Office: Days
• US Class Current: 705/7.25
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 50/06 Energy or water supply

Abstract

Apparatus and method use a Markov decision process (MDP) to reduce the cost of variations in electric power usage. The user notifies a power company of a predicted value for a period. The period is divided into subsections. For each subsection, on the basis of a MDP including a state that depends on an electric power usage amount error, charge amount, and set target, the amount of charging and discharging of a storage battery as an action at any given time is optimally decided depending on the electric power usage amount error, charge amount, time, and set target at that time. A predetermined time in a subsection is a target setting time, at which a future target is further set as the action. The action includes deciding the charging and discharging amount in that subsection and deciding a future target in a subsection whose target should be set.

Claims

1. A computer implemented method for generating a policy for optimizing a cost of a resource under a predetermined cost structure, the method comprising:

preparing an error distribution that indicates a deviation of an amount of usage from a predicted value, a characteristic of a storing means for storing or releasing the resource, and the cost structure in a computer-readable form;

calculating an expected cost in a Markov decision process and a parameter that includes a transition probability on the basis of the error distribution, the characteristic of the storing means, and the cost structure, the Markov decision process including a state that includes a usage amount error, an amount of the resource in the storing means, a specification of a section, and a set target; and

deciding an optimal policy that includes an action of storing or releasing the resource of the storing means for the state using the expected cost in the Markov decision process and the parameter including the transition probability.

2. The method according to claim 1, wherein the resource comprises electric power, and the storing means comprises a storage battery.

3. The method according to claim 1, wherein the cost structure comprises a piecewise linear function.

4. The method according to claim 1, wherein said deciding an optimal policy includes solving using linear programming.

5. The method according to claim 1, wherein said deciding an optimal policy includes solving using value iteration.

6. The method according to claim 1, wherein said deciding an optimal policy includes solving using policy iteration.

13. A computer implemented method for optimizing a cost of a resource under a predetermined cost structure, the method comprising:

retaining a policy generated by a method of claim 1 in a computer-readable manner on the basis of the cost structure;

deciding an action of storing or releasing of storing means by calculating a Markov decision process that includes a state including a usage amount error, an amount of resource in the storing means, a specification of a section, and a set target on the basis of the policy for each of a plurality of subsections into which the section is divided; and

deciding an objective resource usage amount in a next section on the basis of the policy in a specific subsection of the plurality of subsections.

14. The method according to claim 13, wherein the resource comprises electric power, and the storing means comprises a storage battery.

15. The method according to claim 13, wherein the cost structure comprises a piecewise linear function.

7. A computer executed program product for generating a policy for optimizing a cost of a resource under a predetermined cost structure, the program product causing the computer to execute:

a step of preparing an error distribution that indicates a deviation of an amount of usage from a predicted value, a characteristic of a storing means for storing or releasing the resource, and the cost structure in a computer-readable form;

a step of calculating an expected cost in a Markov decision process and a parameter that includes a transition probability on the basis of the error distribution, the characteristic of the storing means, and the cost structure, the Markov decision process including a state that includes a usage amount error, an amount of resource in the storing means, a specification of a section, and a set target; and

a step of deciding an optimal policy that includes an action of storing or releasing the resource of the storing means for the state using the expected cost in the Markov decision process and the parameter including the transition probability.

8. The program product according to claim 7, wherein the resource comprises electric power, and the storing means comprises a storage battery.

9. The program product according to claim 7, wherein the cost structure comprises a piecewise linear function.

10. The program product according to claim 7, wherein the step of deciding the optimal policy is solved using linear programming.

11. The program product according to claim 7, wherein the step of deciding the optimal policy is solved using value iteration.

12. The program product according to claim 7, wherein the step of deciding the optimal policy is solved using policy iteration.

16. A computer executed program product for optimizing a cost of a resource under a predetermined cost structure, the program product causing the computer to execute:

a step of retaining a policy generated by a program product of claim 7 in a computer-readable manner on the basis of the cost structure;

a step of deciding an action of storing or releasing of storing means by calculating a Markov decision process that includes a state including a usage amount error, an amount of resource in the storing means, a specification of a section, and a set target on the basis of the policy for each of a plurality of subsections into which the section is divided; and

a step of deciding an objective resource usage amount in a next section on the basis of the policy in a specific subsection of the plurality of subsections.

17. The program product according to claim 16, wherein the resource comprises electric power and the storing means comprises a storage battery.

18. The program product according to claim 16, wherein the cost structure comprises a piecewise linear function.

19. A computer implemented system for optimizing a cost of a resource under a predetermined cost structure, the system comprising:

memory means;

storing means for storing or releasing the resource;

means for retaining a policy generated using a program product of claim 7 in the memory means in a computer-readable manner on the basis of the cost structure;

means for deciding an action of storing or releasing of storing means by calculating a Markov decision process that includes a state including a usage amount error, an amount of resource in the storing means, a specification of a section, and a set target on the basis of the policy for each of a plurality of subsections into which the section is divided; and

means for deciding an objective resource usage amount in a next section on the basis of the policy in a specific subsection of the plurality of subsections.

20. The system according to claim 19, wherein the resource comprises electric power, and the storing means comprises a storage battery.

21. The system according to claim 19, wherein the cost structure comprises a piecewise linear function.