Method for integrating individual load forecasts into a composite load forecast to present a comprehensive synchronized and harmonized load forecast

• US 20110029141A1
• Filed: 07/02/2010
• Published: 02/03/2011
• Est. Priority Date: 07/02/2010
• Status: Active Grant

• Current Assignee: Alstom Technology Ltd. (Alstom SA)
• Original Assignee: Alstom Grid Incorporated (Alstom SA)
• Inventors: Chung, Kenneth, McKeag, Tory, Sun, David, Cheung, Kwok
• Granted Patent: US 8,538,593 B2
• Time in Patent Office: Days
• US Class Current: 700/291
• CPC Class Codes: G05B 13/02 electric
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• 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

Abstract

A method is provided for merging different load forecasts for power grid centers. Area load forecasts are accepted from load forecast engines. A relational database saves load forecast engine data. A comprehensive operating plan integrates individual load forecasts into a composite load forecast to present a comprehensive, synchronized and harmonized load forecast.

Claims

1. A method for merging different load forecasts for power grid centers, comprising:

accepting area load forecasts from load forecast engines;

saving load forecast data in a relational data base; and

integrating individual load forecasts into a composite load forecast to present a comprehensive, synchronized and harmonized load forecast.

2. The method of claim 1, further comprising,

using a programmatic interface that accepts the area load forecasts from load forecast engines.

3. The method of claim 1, further comprising,

providing a user interface that allows an operator to review input load forecasts and to modify load forecasts with an override capability.

4. The method of claim 1, further comprising:

merging multiple load forecasts that cover a same time range to form a composite load forecast.

5. The method of claim 1, further comprising:

providing a programmatic interface that allows consuming applications to query for load forecasts covering at least one of a range of areas, intervals, and time ranges.

6. The method of claim 1, further comprising:

providing a persistence store to hold load forecast data.

7. A method for merging different load forecasts for power grid centers, comprising:

accepting area load forecasts from load forecast engines within a common service framework;

saving load forecast engine data in a relational database; and

integrating individual load forecasts into a composite load forecast to present a comprehensive, synchronized and harmonized load forecast.

8. The method of claim 7, further comprising:

integrating an operator interface to support flexible manual override.

9. A method for merging different load forecasts for power grid centers, comprising:

accepting area load forecasts from load forecast engines; and

serving load forecast requests from different clients with consistent load forecast data; and

integrating individual load forecasts into a composite load forecast to present a comprehensive, synchronized and harmonized load forecast.

10. The method of claim 9, wherein improved load forecasts are provided over different time horizons

11. The method of claim 9, wherein operator interface to load forecast is streamlined with reduction of repetitive manual entries.

12. The method of claim 9, further comprising:

providing an operator user interface to support manual override capability

13. A method for merging different load forecasts for power grid centers, comprising:

accepting area load forecasts from load forecast engines;

saving load forecast engine data in a relational database;

integrating individual load forecasts into a composite load forecast to present a comprehensive, synchronized and harmonized load forecast; and

performing at least one of scaling, adding, setting and linear transformation.

14. The method of claim 13, further comprising:

synthesizing a composite load profile for any given scheduling study period.

15. The method of claim 14, further comprising:

using a weighting factor model to synthesize the composite load profile.

16. The method of claim 15, further comprising:

using a set of front end programmings for inputting and retrieving load forecasts along with boundary processing.

17. The method of claim 16, wherein boundary processing includes at least one of priority and averaging.

18. The method of claim 13, further comprising:

providing a middle-tier architecture.

19. The method of claim 18, wherein the middle-tier architecture includes an service layer for web services, and exposes services to client applications.

20. The method of claim 19, wherein the middle-tier architecture includes an internal service layer.