Computing architecture for autonomous microgrids

• US 9,148,019 B2
• Filed: 09/22/2011
• Issued: 09/29/2015
• Est. Priority Date: 12/06/2010
• Status: Active Grant

• Current Assignee: National Technology & Engineering Solutions Of Sandia LLC (Honeywell International Inc.)
• Original Assignee: Sandia Corporation (Martin Marietta Corporation)
• Inventors: Goldsmith, Steven Y.
• Primary Examiner(s): Fennema, Robert
• Assistant Examiner(s): WHITTINGTON, ANTHONY T
• Application Number:
  US13/241,054
• Publication Number:
  US 20120143385A1
• Time in Patent Office: 1,468 Days
• Field of Search: 700/297, 703/2, 703/18
• US Class Current: 1/1
• CPC Class Codes: H02J 2300/10 The dispersed energy generation being of fossil origin, e.g. diesel generators
• CPC Class Codes: H02J 2300/20 The dispersed energy generation being of renewable origin
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 2300/28 The renewable source being wind energy
• CPC Class Codes: H02J 2300/40 wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
• CPC Class Codes: H02J 3/38 Arrangements for parallely feeding a single network by two or more generators, converters or transformers
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: H02J 3/466 Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers
• CPC Class Codes: Y02E 10/76 Power conversion electric or electronic aspects

Abstract

A computing architecture that facilitates autonomously controlling operations of a microgrid is described herein. A microgrid network includes numerous computing devices that execute intelligent agents, each of which is assigned to a particular entity (load, source, storage device, or switch) in the microgrid. The intelligent agents can execute in accordance with predefined protocols to collectively perform computations that facilitate uninterrupted control of the microgrid.

Claims

1. A method configured for execution in a computing device in a microgrid, the computing device assigned to a particular power source in the microgrid, the method comprising:

computing, for the particular power source in the microgrid, an amount of power predicted to be output by the particular power source at a future point in time;

receiving data from computing devices assigned to a plurality of other power sources in the microgrid, the data pertaining to amounts of power predicted to be output by the plurality of other power sources in the microgrid, respectively, at the future point in time;

causing a processor to compute and output a value that is indicative of a total amount of power predicted to be output collectively by the particular power source and the plurality of other power sources in the microgrid at the future point in time; and

causing the processor to output a signal to a switch that controls current flow from the microgrid using a transmission line to another microgrid, the signal comprising data that is indicative of a difference between the total amount of power predicted to be output collectively by the particular power source and the plurality of other power sources in the microgrid at the future point in time and a total amount of power predicted to be consumed by loads in the microgrid.

2. The method of claim 1, wherein a power electronics device comprises the computing device in the microgrid.

3. The method of claim 2, wherein the power electronics device is one of a transformer, a DC-DC converter, a DC-AC inverter, an AC-DC converter, a thyristor, IGBT, or switch contactor.

4. The method of claim 1, wherein the particular power source is a power source that utilizes at least one renewable energy resource to generate power.

5. The method of claim 4, wherein the particular power source is one of a solar panel or a wind turbine.

6. The method of claim 1, further comprising causing the processor to compute data that is indicative of a mean of the total amount of power predicted to be output collectively by the particular power source and the plurality of other power sources in the microgrid at the future point in time and a variance of the total amount of power predicted to be output collectively by the particular power source and the plurality of other power sources in the microgrid at the future point in time.

7. The method of claim 1, further comprising:

computing amounts of power predicted to be output by the particular power source at a plurality of different future points in time; and

causing at least one other power source in the microgrid to alter at least one operating condition based at least in part upon the amounts of power predicted to be output by the particular power source at the plurality of different future points in time.

8. The method of claim 7, wherein the at least one other power source in the microgrid is one of a battery, a capacitor bank, or a gas turbine.

9. The method of claim 1, the microgrid comprising less than five thousand different power sources and less than one hundred thousand different loads.

10. The method of claim 1, the microgrid encompassing a geographic range of less than 300 square miles.

11. The method of claim 1, the computing device being a portion of a decentralized, distributed network, wherein computing devices in the decentralized, distributed network perform computations using multi-agent systems (MAS) technologies.

12. A system that facilitates autonomously controlling operation of a microgrid, the system comprising:

a computing device that is assigned to a source of power in the microgrid, the computing device comprising;

a processor; and

a memory that comprises a plurality of components that are executed by the processor, the plurality of components comprising;

a source predictor component that computes predictions of amounts of electrical power that will be output by the source of power in the microgrid across multiple points in time in the future;

a source communicator component that communicates the amounts of power that will be output by the source of power in the microgrid across the multiple points in time in the future that are predicted by the source predictor component to at least one other computing device that is assigned to at least one other source of power in the microgrid;

an aggregate power computer component that is configured to perform at least a portion of a distributed computation for an aggregate amount of power predicted to be output by sources of power in the microgrid, the sources of power in the microgrid comprising at least one power source that outputs a varying amount of electrical power over time; and

a transmission agent that outputs a signal to a switch that controls current flow from the microgrid using a transmission line to another microgrid, the signal comprising data that is indicative of a difference between the aggregate amount of power predicted to be output collectively by the particular power source and the plurality of other power sources in the microgrid at the future point in time and a total amount of power predicted to be consumed by loads in the microgrid.

13. The system of claim 12, the at least one power source that outputs a varying amount of electrical power over time being one of a solar panel or a micro wind turbine.

14. The system of claim 12, the computing device comprised by one of a DC-DC converter, a DC-AC converter, an AC-DC converter, an AC-AC converter, or a transformer.

15. The system of claim 12, the source predictor component computes the predictions of the amounts of electrical power that will be output by the source of power in the microgrid across multiple points in time in the future based at least in part upon position of the sun at the points in time in the future, expected cloud coverage at the points in time in the future, or expected wind speeds at the points in time in the future.

16. The system of claim 12, the computing device being a portion of a distributed computing system that autonomously controls operation of the microgrid.

17. The system of claim 12, wherein the source of power is a gas turbine, and wherein the plurality of components further comprises a source scheduler component that schedules an amount of power to be generated by the gas turbine at at least one point in time in the future based at least in part upon the collective amount of power predicted to be output by sources of power in the microgrid.

18. The system of claim 12, wherein the computing device operates in harmony with another computing device to generate a virtual power bus that is accessible to loads in the microgrid.

19. A non-transitory computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform acts comprising:

accessing data pertaining to at least one weather condition at various future points in time;

predicting amounts of electric power that are to be generated by a source of electric power in a microgrid at the various future points in time based at least in part outputting the amounts of electric power to a plurality of other computing devices that are assigned to other sources of power in the microgrid;

receiving from the plurality of other computing devices that are assigned to the other sources of power data that pertains to a total amount of power to be generated by sources of electric power in the microgrid;

performing at least one computation based upon the data received from the plurality of other computing devices, the at least one computation pertaining to a collective amount of power predicted to be available to loads in the microgrid at the various points in time; and

outputting a signal to a switch that controls current flow from the microgrid using a transmission line to another microgrid, the signal comprising data that is indicative of a difference between the total amount of power predicted to be output collectively by the particular power source and the plurality of other sources of power in the microgrid at one of the various future points in time and a total amount of power predicted to be consumed by loads in the microgrid.