Distributed forecasting and pricing system

• US 10,366,403 B2
• Filed: 10/15/2012
• Issued: 07/30/2019
• Est. Priority Date: 10/15/2012
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Yu, Jia Yuan
• Primary Examiner(s): Miller, Alan S
• Application Number:
  US13/651,850
• Publication Number:
  US 20140108093A1
• Time in Patent Office: 2,479 Days
• Field of Search: 705 711- 742
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors

Abstract

A method, system and computer program product for distributed forecasting and pricing for a commodity supplied by a provider to a user. In one embodiment, the provider announces a pricing plan, and the provider receives a forecast of an estimated amount of the commodity from the provider that the user will use over a given period of time. The provider provides the user with an actual amount of the commodity over the given period; and the provider charges the user for the actual amount of the commodity provided to the user based on the pricing policy, the actual amount of the commodity provided to the user, and the accuracy of the forecast. In an embodiment, the forecast is received by the provider after the provider announces the pricing plan and before the given period begins. The forecast may be received from the user or from a third-party forecaster.

Claims

1. A method of supplying a commodity from a provider to a plurality of users, and pricing the commodity, based on collecting distributed forecasting of use of the commodity, the method comprising:

providing, by the provider, a pricing plan for the commodity;

providing remote access over a distributed computer network to a plurality of users via a mobile communication device application;

receiving, by the provider, a forecast from each of the plurality of users, at a computer processing system, via the distributed computer network, of an estimated amount of the commodity from the provider that each of the plurality of users will use over a given period of time;

determining, by the provider, at the computer processing system, an amount of the commodity to be produced based on all the forecasts received from the plurality of users over the distributed computer network;

producing, by the provider, the determined amount of the commodity based on all the forecasts received from the plurality of users over the distributed computer network;

providing, by the provider, each of the plurality of users with an actual amount of the commodity over the given period of time;

determining, by the provider, at the computer processing system, a price for each respective user of the plurality of users for the commodity, in retrospect, after the given period of time, and charging each respective user said determined price, for the actual amount of the commodity provided to each respective user by the provider over the given period of time, based on said pricing plan, said actual amount of the commodity provided to each respective user, and an accuracy of the forecast of the estimated amount of the commodity that each respective user will use, said accuracy determined by a difference between said forecast and the actual amount of the commodity provided to each respective user by the provider; and

monitoring information from a smart meter indicating the actual amount of the commodity provided to one or more respective users and adjusting the forecast based on the monitored information in determining the price for the commodity for each of the one or more respective users.

2. The method according to claim 1, further comprising monitoring the actual amount of the commodity provided to a respective user and increasing the price for the respective user in response to the actual amount of the provided commodity being greater than the forecast.

3. The method according to claim 2, further comprising monitoring the actual amount of the commodity provided to a respective user and decreasing the price for the respective user in response to the actual amount of the provided commodity being less than the forecast.

4. The method according to claim 1, further comprising receiving a forecast for the estimated amount of the commodity that the plurality of users will use over the given period of time from a forecaster, different from the plurality of users and the provider.

5. The method according to claim 1, further comprising repeating the provider receiving a forecast, and the provider providing each of the plurality of users with an actual amount of the commodity, a multitude of times over a defined length of time.

6. The method according to claim 1, wherein the forecast from one or more of the plurality of users includes an estimated upper limit and an estimated lower limit of the commodity from the provider that the one or more of the plurality of users will use over said given period of time.

7. The method according to claim 1, wherein:

the given time period includes a multitude of time intervals; and

the forecast from one or more of the plurality of users includes a mean of a multitude of partial amounts, each of said partial amounts being an amount of the commodity from the provider that the one or more of the plurality of users will use in a respective one of said multitude of time intervals.

8. The method according to claim 7, wherein the forecast includes a variance from a defined value.

9. The method according to claim 1, further comprising:

determining uncertainty in the forecast based on forecast errors; and

increasing the price based on the uncertainty.

10. The method according to claim 1, further comprising:

receiving, by the provider, information from one or more users indicating a quantity of the commodity produced by the one or more users; and

adjusting the amount of the commodity to be produced based on the quantity of the commodity produced by the one or more users.

11. The method according to claim 1, further comprising:

the provider consuming a quantity of the commodity; and

;

adjusting the amount of the commodity to be produced based on the quantity of the commodity consumed by the provider.

12. A computer program product, comprising:

at least one tangible computer readable hardware device having computer readable program code logic tangibly embodied therein to price a commodity supplied to a user from a supplier based on collecting distributed forecasting of use of the commodity from a plurality of users, said computer readable program code, when executing in a computer, implementing the method comprising;

providing a pricing policy specified by the provider for the commodity;

providing remote access over a distributed computer network to a plurality of users via a mobile communication device application;

receiving a forecast from each of the plurality of users, at a computer processing system, via a distributed computer network, to the provider of an estimated amount of the commodity from the provider that each of the plurality of users will use over a given period of time;

determining, at the computer processing system, an amount of the commodity to be produced based on all the forecasts received from the plurality of users over the distributed computer network;

determining, at the computer processing system, a price for each respective user of the plurality of users for the commodity, in retrospect, after the given period of time, and charging each respective user said determined price, for an actual amount of the commodity provided to each respective user by the provider over the given period of time, based on the pricing policy specified by the provider, the produced amount of the commodity based on all the forecasts, said actual amount of the commodity provided to each respective user, and an accuracy of the forecast of the estimated amount of the commodity that each respective user will use, said accuracy determined by a difference between said forecast and the actual amount of the commodity provided to each respective user by the supplier; and

monitoring information from a smart meter indicating the actual amount of the commodity provided to one or more respective users and adjusting the forecast based on the monitored information in determining the price for the commodity for each of the one or more respective users.

13. The computer program product according to claim 12, further comprising monitoring the actual amount of the commodity provided to a respective user and increasing the price for the respective user in response to the actual amount of the provided commodity being greater than the forecast.

14. The computer program product according to claim 13, further comprising monitoring the actual amount of the commodity provided to a respective user and decreasing the price for the respective user in response to the actual amount of the provided commodity being less than the forecast.

15. The computer program product according to claim 12, further comprising receiving a forecast for the an estimated amount of the commodity that the plurality of users will use over the given period of time from a forecaster, different from the plurality of users and the provider.

16. The computer program product according to claim 12, further comprising repeating the provider receiving a forecast, and the provider providing each of the plurality of users with an actual amount of the commodity, a multitude of times over a defined length of time.

17. The computer program product according to claim 12, wherein the forecast from one or more of the plurality of users includes an estimated upper limit and an estimated lower limit of the commodity from the provider that the one or more of the plurality of users will use over said given period of time.

18. The computer program product according to claim 12, wherein:

the given time period includes a multitude of time intervals; and

the forecast from one or more of the plurality of users includes a mean of a multitude of partial amounts, each of said partial amounts being an amount of the commodity from the provider that the one or more of the plurality of users will use in a respective one of said multitude of time intervals.

19. The computer program product according to claim 12, wherein the forecast includes a variance from a defined value.

20. The computer program product according to claim 12, further comprising:

determining uncertainty in the forecast based on forecast errors; and

increasing the price based on the uncertainty.

21. The computer program product according to claim 12, further comprising:

receiving, by the provider, information from one or more users indicating a quantity of the commodity produced by the one or more users; and

adjusting the amount of the commodity to be produced based on the quantity of the commodity produced by the one or more users.

22. The computer program product according to claim 12, further comprising:

the provider consuming a quantity of the commodity; and

adjusting the amount of the commodity to be produced based on the quantity of the commodity consumed by the provider.