RESOURCE COST OPTIMIZATION SYSTEM, METHOD, AND PROGRAM

• US 20130346345A1
• Filed: 08/28/2013
• Published: 12/26/2013
• 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 9,092,832 B2
• Time in Patent Office: Days
• US Class Current: 705/412
• 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 optimizing a cost of a resource under a cost structure, the method comprising:

retaining a policy generated based on a Markov decision process and the cost structure, the policy indicating when to store the resource in a storage device and when to release the resource from the storage device;

deciding an action of storing or releasing the resource based on the policy and a state of the Markov decision process, the state including a usage amount error, an amount of resource available in the storage device, a specification of a current section among a plurality of sections during which the policy applies, and a target value.

2. The method according to claim 1, wherein the resource comprises electric power, and the storage device is a 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 the target value is a target charge or discharge amount for a next section when the current section is a target section and the target value is null otherwise.

5. The method according to claim 4, further comprising determining a next target charge or discharge amount when the current section is the target section.

6. The method according to claim 5, wherein the next target charge or discharge amount is based on a usage amount and a predicted value of usage.

7. A non-transitory computer executed program product for optimizing a cost of a resource under a cost structure, the program product causing the computer to execute:

a step of retaining a policy generated based on a Markov decision process and the cost structure, the policy indicating when to store the resource in a storage device and when to release the resource from the storage device;

a step of deciding an action of storing or releasing the resource based on the policy and a state of the Markov decision process, the state including a usage amount error, an amount of resource available in the storage device, a specification of a current section among a plurality of sections during which the policy applies, and a target value.

8. The program product according to claim 7, wherein the resource comprises electric power and the storage device is a 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 target value is a target charge or discharge amount for a next section when the current section is a target section and the target value is null otherwise.

11. The program product according to claim 10, wherein the computer further executes a step of determining a next target charge or discharge amount when the current section is the target section.

12. The program product according to claim 11, wherein the next target charge or discharge amount is based on a usage amount and a predicted value of usage.

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

a storage device configured to store the resource and release the resource;

means for retaining a policy generated based on a Markov decision process and the cost structure, the policy indicating when to store the resource in the storage device and when to release the resource from the storage device;

means for deciding an action of storing or releasing the resource by the storage device based on the policy and a state of the Markov decision process, the state including a usage amount error, an amount of resource available in the storage device, a specification of a current section among a plurality of sections during which the policy applies, and a target value.

14. The system according to claim 13, wherein the resource comprises electric power, and the storage device is a battery.

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

16. The system according to claim 13, wherein the target value is a target charge or discharge amount for a next section when the current section is a target section and the target value is null otherwise.

17. The system according to claim 16, wherein the means for deciding the action determines a next target charge or discharge amount when the current section is the target section.

18. The system according to claim 17, wherein the next target charge or discharge amount is based on a usage amount and a predicted value of usage.