Transactive control and coordination framework and associated toolkit functions

• US 10,740,775 B2
• Filed: 12/16/2013
• Issued: 08/11/2020
• Est. Priority Date: 12/14/2012
• Status: Active Grant

• Current Assignee: Battelle Memorial Institute
• Original Assignee: Battelle Memorial Institute
• Inventors: Hammerstrom, Donald J., Melton, Ron, Esram, Trishan, Hathaway, John E.
• Primary Examiner(s): Pan, Yuhui R
• Application Number:
  US14/108,078
• Publication Number:
  US 20140172503A1
• Time in Patent Office: 2,430 Days
• Field of Search: 700291, 705412
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: Y04S 50/14 Marketing, i.e. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards

Abstract

Disclosed herein are representative embodiments of methods, apparatus, and systems for facilitating operation and control of a resource distribution system (such as a power grid). For example, embodiments of the disclosed technology can be used to improve the resiliency of a power grid and to allow for improved consumption of renewable resources. Further, certain implementations facilitate a degree of decentralized operations not available elsewhere.

Claims

1. A method for operating a transactive node in a market-based electrical-energy-allocation system, comprising:

by computing hardware configured to operate the transactive node;

computing incentive signal data, the incentive signal data comprising data indicative of a cost of electric energy at the transactive node at a current time interval and data indicative of a forecasted cost of electric energy at the transactive node at one or more future time intervals, wherein the incentive signal data further comprises data indicative of a confidence level that the data indicative of the cost of electric energy at the transactive node at the current time interval is accurate or data indicating a confidence level that the data indicative of the forecasted cost of electric energy at the transactive node at the one or more future time intervals is accurate;

computing feedback signal data, the feedback signal data comprising data indicative of an electric load at the transactive node at the current time interval and data indicative of a forecasted load for electric energy at the transactive node at the one or more future time intervals; and

transmitting the incentive signal data and the feedback signal data to a neighboring transactive node.

2. The method of claim 1) wherein the data indicative of the cost of electric energy comprises data indicative of a cost of real electrical energy, reactive electrical energy, or a combination of both real and reactive electrical energies at the transactive node at the current time interval, and wherein the data indicative of the forecasted cost of electric energy comprises data indicative of a forecasted cost of real electrical energy, reactive electrical energy, or a combination of both real and reactive electrical energies at the transactive node at the one or more future time intervals.

3. The method of claim 1), wherein the data indicative of the electric load comprises data indicative of a real electrical load, reactive electrical load, or a combination of both real and reactive electrical loads at the transactive node at the current time interval, and wherein the data indicative of the forecasted load for electric energy comprises data indicative of a forecasted load of real electrical load, reactive electrical load, or a combination of both real and reactive electrical loads at the transactive node at the one or more future time intervals.

4. The method of claim 1), wherein the incentive signal data further comprises data indicating a confidence level that the data indicative of the cost of electric energy at the transactive node at the current time interval is accurate, and data indicating a confidence level that the data indicative of the forecasted cost of electric energy at the transactive node at the one or more future time intervals is accurate.

5. The method of claim 1), wherein the feedback signal data further comprises data indicating a confidence level that the data indicative of the electric load at the transactive node at the current time interval is accurate, and data indicating a confidence level that the data indicative of the forecasted load for electric energy at the transactive node at the one or more future time intervals is accurate.

6. The method of claim 1), wherein the method further comprises receiving incentive signal data and feedback signal data from one or more neighboring transactive nodes, wherein the computing the incentive signal data is based at least in part on the received incentive signal data, and wherein the computing the feedback signal data is based at least in part on the received feedback signal data.

7. One or more non-transitory computer-readable media storing computer-readable instructions for causing computer to perform the method of claim 1).

8. A transactive node comprising computing hardware configured to perform the method of claim 1).

9. A method for operating a transactive node in a market-based electrical-energy-allocation system, comprising:

by computing hardware;

receiving incentive signal data at the transactive node from two or more neighboring transactive nodes, the incentive signal data from the two or more neighboring transactive nodes comprising data indicative of at least a cost of electric energy at a current time interval;

computing aggregated incentive signal data based at least in part on the incentive signal data from the two or more neighboring transactive nodes; and

transmitting the aggregated incentive signal data to a further transactive node,

wherein the received incentive signal data further includes data indicating a confidence level of the received incentive signal data, or wherein the transmitted incentive signal data further includes data indicating a confidence level of the transmitted incentive signal data.

10. The method of claim 9), wherein the received incentive signal data and the transmitted aggregated incentive signal data comprise data indicative of a cost of real electrical energy, reactive electrical energy, or a combination of both real and reactive electrical energies.

11. The method of claim 9), wherein the aggregated incentive signal data comprises a weighted sum of the incentive signal data from the two or more neighboring transactive nodes.

12. The method of claim 9), wherein the aggregated incentive signal data is further modified to provide an incentive or disincentive to the further transactive node based on local conditions at the transactive node.

13. The method of claim 9), wherein the received incentive signal data comprises data indicative of the cost of electric energy at the current time interval and data indicative of a forecasted cost of electric energy at one or more future time intervals, and wherein the aggregated incentive signal data comprises data indicative of the aggregated cost of electric energy at the current time interval and data indicative of a forecasted aggregated cost of electric energy at one or more future time intervals.

14. The method of claim 9), wherein the method further comprises:

receiving feedback signal data at the transactive node from the two or more neighboring transactive nodes, the feedback signal data from the two or more neighboring transactive nodes comprising data indicative of at least an electric load for electric energy at a current time interval;

computing aggregated feedback signal data based at least in part on the feedback signal data from the two or more neighboring transactive nodes; and

transmitting the aggregated feedback signal data to the further transactive node.

15. The method of claim 14), wherein the received feedback signal data comprises data indicative of the electric load for electric energy at the current time interval and data indicative of a forecasted load of electric energy at the one or more future time intervals, and wherein the aggregated feedback signal data comprises data indicative of the aggregated load of electric energy at the current time interval and data indicative of a forecasted aggregated load of electric energy at one or more future time intervals.

16. One or more non-transitory computer-readable media storing computer-readable instructions for causing computer to perform the method of claim 9).

17. A transactive node comprising computing hardware configured to perform the method of claim 9).

18. A method for operating a transactive node in a market-based electrical-energy-allocation system, comprising:

by computing hardware;

receiving feedback signal data at a transactive node from two or more neighboring transactive nodes, the feedback signal data from the two or more neighboring transactive nodes comprising data indicative of at least an electric load for electric energy at a current time interval;

computing aggregated feedback signal data based at least in part on the feedback signal data from the two or more neighboring transactive nodes; and

transmitting the aggregated feedback signal data to a further transactive node,

wherein the received feedback signal data further includes data indicating a confidence level of the received feedback signal data, or

wherein the transmitted feedback signal data further includes data indicating a confidence level of the transmitted feedback signal data.

19. The method of claim 18), wherein the received feedback signal data and the transmitted aggregated feedback signal data comprise data indicative of a real electrical load, reactive electrical load, or a combination of both real and reactive electrical loads.

20. The method of claim 18), wherein the received feedback signal data comprises data indicative of the electric load of electric energy at the current time interval and data indicative of a forecasted load of electric energy at one or more future time intervals, and wherein the aggregated feedback signal data comprises data indicative of the aggregated load of electric energy at the current time interval and data indicative of a forecasted aggregated load of electric energy at the one or more future time intervals.

21. The method of claim 18), wherein the method further comprises:

receiving incentive signal data at the transactive node from the two or more neighboring transactive nodes, the incentive signal data from the two or more neighboring transactive nodes comprising data indicative of at least a cost of electric energy at the current time interval;

computing aggregated incentive signal data based at least in part on the incentive signal data from the two or more neighboring transactive nodes; and

transmitting the aggregated incentive signal data to the further transactive node.

22. The method of claim 21), wherein the received incentive signal data comprises data indicative of the cost of electric energy at the current time interval and data indicative of a forecasted cost of electric energy at the one or more future time intervals, and wherein the aggregated incentive signal data comprises data indicative of the aggregated cost of electric energy at the current time interval and data indicative of a forecasted aggregated cost of electric energy at one or more future time intervals.

23. One or more non-transitory computer-readable media storing computer-readable instructions for causing computer to perform the method of claim 18).

24. A transactive node comprising computing hardware configured to perform the method of claim 18).