IP Library Granted Patent US 7,315,769
Granted Patent B2
US 7,315,769 · App. 11/263,420 · Granted Jan 1, 2008

Multi-tier benefit optimization for operating the power systems including renewable and traditional generation, energy storage, and controllable loads

Assignee: General Electric Company
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Quick Facts
Patent No.
US 7,315,769
App. No.
11/263,420
Granted
Jan 1, 2008
Kind
B2
Abstract

A plurality of power generating assets are connected to a power grid. The grid may, if desired, be a local grid or a utility grid. The power grid is connected to a plurality of loads. The loads may, if desired, be controllable and non-controllable. Distribution of the power to the loads is via a controller that has a program stored therein that optimizes the controllable loads and the power generating assets. The optimization process is via multi-tier benefit construct.

Claims (43)

1. An intelligent renewable based system comprising:

a controller with a memory said memory having stored therein a program;

a plurality of data structures forming said program;

said program data structures controlling a multi-tier benefit optimization of a power grid;

said power grid having renewable power generating assets, fossil fueled generating assets and controllable loads connectively disposed thereto; and

said multi-tier benefit optimization program maximizes the sum of weighted direct and indirect benefits or penalties generated by said renewable power generating assets, fossil fueled generating assets and said controllable loads, such that economics of system operation and benefits or penalties of system operation unrelated to the reasons for which the system is primarily operational are quantified and together are optimized to achieve a desired multi-tier benefit.

2. An intelligent renewable based system as recited in claim 1 , further comprising forecasted power demand from said renewable power generating assets being passed to said controller for benefit optimization by said program.

3. An intelligent renewable based system as recited in claim 1 , further comprising forecasted water demand from said renewable power generating assets being passed to said controller for benefit optimization by said program.

4. An intelligent renewable based system as recited in claim 1 , wherein said renewable power generating assets passing forecasted resource availably to said controller.

5. An intelligent renewable based system as recited in claim 1 , wherein said renewable power generating asset is a hydrogen engine deriving its fuel from hydrogen storage via a desalination plant and an electrolyser.

6. An intelligent renewable based system as recited in claim 1 , wherein said controllable loads are selected from a group consisting of hydrogen storage, electrolyser plant and desalination plant.

7. An intelligent renewable based system as recited in claim 1 , wherein said renewable power generating assets are selected from a group consisting of wind power, hydroelectic power, solar, geothermal and hydrogen engine-generators.

8. An intelligent renewable based system comprising:

a controller with a memory said memory having stored therein a program;

a plurality of data structures forming said program;

said program data structures controlling a multi-tier benefit optimization of a power grid;

said power grid having power generating assets and controllable loads connectively disposed thereto; and

said multi-tier benefit optimization maximizes the sum of weighted multi-tier direct and indirect benefits or penalties generated by said power generating assets and produced by said controllable loads, such that economics of system operation and benefits or penalties of system operation unrelated to the reasons for which the system is primarily operational are quantified and together are optimized to achieve a desired multi-tier benefit.

9. An intelligent renewable based system as recited in claim 8 , wherein said power grid is an electric ship.

10. An intelligent renewable based system as recited in claim 8 , wherein each multi-tier benefit is associated with a respective power generating asset or controllable load and comprises a sum of weighted benefits as a function of power.

11. A method for an intelligent renewable based system comprising:

providing renewable power generating assets connectively disposed to a power grid;

providing power loads connectively disposed to said power grid;

optimizing said provided renewable power generating assets and said provided power loads via maximizing a sum of weighted multi-tier benefits or penalties associated with said provided renewable power generating assets and said provided power loads;

generating power from said optimized renewable power generating assets; and

distributing said generated power to said optimized power loads, such that economics of system operation and benefits or penalties of system operation unrelated to the reasons for which the system is primarily operational are quantified and together are optimized to achieve a desired multi-tier benefit.

12. A method for an intelligent renewable based system as recited in claim 11 , wherein providing renewable power generating assets comprises:

providing water generating assets;

providing water loads;

providing storage assets;

generating water from said provided water generating assets;

storing water via said storage assets;

generating power from said stored water; and

distributing said generated power to said provided water loads.

13. A method for an intelligent renewable based system in claim 11 , wherein said power loads are controllable.

14. A method for an intelligent renewable based system as recited in claim 11 , wherein maximizing a sum of weighted multi-tier benefits or penalties associated with said provided renewable power generating assets and said provided power loads comprises maximizing a sum of weighted multi-tier benefits or penalties as a function of power.

15. A method for an intelligent renewable based system as recited in claim 11 , wherein said renewable power-generating assets are selected from a group consisting of wind power, hydroelectric power, and energy storage.

16. A method for an intelligent renewable based system as recited in claim 11 , further comprising maximizing extraction of power from renewable power generating assets based on adjustable droop characteristics.

17. A method for an intelligent renewable based system as recited in claim 12 , wherein said water-generating assets are selected from a group consisting of desalination of seawater and water storage.

18. A method for an intelligent renewable based system as recited in claim 13 , wherein said controllable loads are desalination plants.

19. A method for an intelligent renewable based system as recited in claim 15 , wherein said energy storage units are compressed hydrogen fueling tanks in communication with said hydrogen engine-generators.

20. A method for an intelligent renewable based system as recited in claim 11 , further comprising providing fossil fueled power generating assets connectively disposed to the power grid.

21. A method for an intelligent renewable based system as recited in claim 20 , wherein said fossil fueled asset is a diesel engine-generator.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 31, 2006
From: BALAN, CHELLAPPA; BOSE, SUMIT; YE, ZHIHONG; BEBIC, JOVAN; BEDOUT, JUAN DE; LIU, YAN; GARCES, LUIS
To: GENERAL ELECTRIC COMPANY
Reel/Frame 017420/0527 →
Continuity (1)
Related Publication 20070100503A1 · May 3, 2007