CAPITAL ASSET PLANNING SYSTEM

• US 20130138482A1
• Filed: 05/23/2012
• Published: 05/30/2013
• Est. Priority Date: 05/28/2009
• Status: Abandoned Application

• Current Assignee: Trustees Of Columbia University In The City Of New York (Columbia University), Consolidated Edison Incorporated
• Original Assignee: Consolidated Edison Incorporated
• Inventors: Anderson, Roger N., Chow, Maggie, Boulanger, Albert
• Application Number:
  US13/479,198
• Publication Number:
  US 20130138482A1
• Time in Patent Office: Days
• US Class Current: 705/7.37
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A capital asset planning system for selecting assets for improvement within an infrastructure that includes one or more data sources descriptive of the infrastructure, one or more databases, coupled to the one or more data sources, to compile the one or more data sources, one or more processors, each coupled to and having respective communication interfaces to receive data from the one or more databases. The processor includes a predictor to generate a first metric of estimated infrastructure effectiveness based, at least in part, on a current status of the infrastructure, a second metric of estimated infrastructure effectiveness based, at least in part, on a user-selected, proposed changed configuration of the infrastructure, and a net metric of infrastructure effectiveness based, at least in part, on said first metric and said second metric. The system also includes a display, coupled to have the one or more processors, for visually presenting the net metric of infrastructure effectiveness, in which the assets for improvement are selected based, at least in part, on the net metric of infrastructure effectiveness.

Claims

1. A capital asset planning system for selecting assets for improvement within an infrastructure comprising:

(a) one or more data sources descriptive of the infrastructure;

(b) one or more databases, coupled to the one or more data sources, to compile the one or more data sources;

(c) one or more processors, each coupled to and having respective communication interfaces to receive data from the one or more databases, the one or more processors comprising a predictor to generate;

(i) a first metric of estimated infrastructure effectiveness based, at least in part, on a current status of the infrastructure;

(ii) a second metric of estimated infrastructure effectiveness based, at least in part, on a user-selected, proposed changed configuration of the infrastructure; and

(iii) a net metric of infrastructure effectiveness based, at least in part, on said first metric and said second metric; and

(d) a display, coupled to have the one or more processors, for visually presenting the net metric of infrastructure effectiveness;

wherein the assets for improvement are selected based, at least in part, on the net metric of infrastructure effectiveness.

2. The capital asset planning system of claim 1, wherein the first metric of infrastructure effectiveness and the second metric of infrastructure effectiveness are both based, at least in part, on an estimated length of time that the infrastructure produces a commodity.

3. The capital asset planning system of claim 1, wherein the infrastructure is selected from the group consisting of a chemical processing operation, a petroleum refining operation, a product manufacturing operation, a telecommunication grid, a transportation infrastructure, a gas network, a commodity pipeline network, and a water treatment network.

4. The capital asset planning system of claim 1, wherein the infrastructure is an electrical grid.

5. The capital asset planning system of claim 4, wherein the first metric of infrastructure effectiveness and the second metric of infrastructure effectiveness are based, at least in part, on the estimated mean time between failure of one or more components of the electrical grid.

6. The capital asset planning system of claim 4, wherein the one or more data sources descriptive of the infrastructure include data representative of at least one of electrical feeder data, electrical cable data, electrical joint data, electrical transformer data, electrical outage data, electrical test pass or fail data, electrical load data, and past capital improvement cost data.

7. The capital asset planning system of claim 4, wherein the first metric of infrastructure effectiveness and the second metric of infrastructure effectiveness is estimated using a feeder index, said index based, at least in part, on a predicted likelihood of feeder failure.

8. The capital asset planning system of claim 7, wherein the predicted likelihood of feeder failure is obtained using machine learning.

9. The capital asset planning system of claim 7, wherein the feeder index is recalculated based, at least in part, on observed and previously predicted feeder data.

10. The capital asset planning system of claim 5, wherein the estimated mean time between failure is the estimated mean time between failure of an electrical feeder.

11. The capital asset planning system of claim 1, wherein the predictor further generates a cost metric based, at least in part, on the cost of the user-selected, proposed change of the infrastructure.

12. The capital asset planning system of claim 11, wherein the cost metric is generated based, at least in part, on a user-specified cost of one or more specific actions encompassed by the user-selected, proposed change of the infrastructure.

13. The capital asset planning system of claim 11, wherein the one or more data sources include past capital improvement cost data, and the cost metric is based, at least in part, on past capital improvement cost data.

14. The capital asset planning system of claim 1, wherein the predictor further comprises a prioritizer to determine the user-selected, proposed changed configuration of the infrastructure that provides the maximum value based, at least in part, on the net metric of infrastructure effectiveness and the cost metric.

15. A method for selecting assets for improvement within an infrastructure comprising:

(a) accessing one or more data sources descriptive of the infrastructure;

(b) compiling the one or more data sources into one or more databases;

(c) generating a first metric of estimated infrastructure effectiveness based, at least in part, on a current status of the infrastructure;

(d) generating a second metric of estimated infrastructure effectiveness based, at least in part, on a user-selected, proposed changed configuration of the infrastructure; and

(e) generating a net metric of infrastructure effectiveness based, at least in part, on said first metric and said second metric; and

(f) displaying the net metric of infrastructure effectiveness,

wherein the assets for improvement are selected based, at least in part, on the net metric of infrastructure effectiveness.

16. The method for selecting assets for improvement of claim 15 wherein the infrastructure is an electrical grid, and said first metric, said second metric and said net metric is based, at least in part, on the estimated mean time between failure of an electrical feeder within the electrical grid.

17. The method for selecting assets for improvement of claim 15, wherein the first metric of infrastructure effectiveness and the second metric of infrastructure effectiveness is estimated using a feeder index, said index based, at least in part, on a predicted likelihood of feeder failure.

18. The method for selecting assets for improvement of claim 15, further comprising generating a cost metric based on the cost of the user-selected, proposed change of the infrastructure.

19. The method for selecting assets for improvement of claim 15, further comprising determining the user-selected, proposed changed configuration of the infrastructure that provides the maximum value based on the net metric of infrastructure effectiveness and the cost metric.

20. A capital asset planning system for selecting assets for improvement within an electrical grid comprising:

(a) one or more data sources descriptive of the infrastructure selected from electrical feeder data, electrical cable data, electrical joint data, electrical transformer data, electrical outage data, electrical test pass or fail data, electrical load data, and past capital improvement cost data;

(b) one or more databases, coupled to the one or more data sources, to compile the one or more data sources;

(c) one or more processors, each coupled to the one or more databases and having respective communication interfaces to receive data from the one or more databases, the one or more processors comprising a predictor to generate;

(i) an estimated baseline mean time between failure of an electrical feeder;

(ii) an estimated projected mean time between failure of an electrical feeder based, at least in part, on a user-selected, proposed changed configuration of the electrical grid; and

(iii) a net mean time between failure based, at least in part on the estimated baseline mean time between failure and the estimated projected mean time between failure; and

(d) a display, coupled to have the one or more processors, for visually presenting the net metric of infrastructure effectiveness and a cost metric of the proposed changed configuration of the electrical grid,

wherein the capital asset planning system provides the ability to select assets for improvement based, at least in part, on the net mean time between failure and the cost metric.