Predictive Grid Control Methods, Apparatus and Computer Program Products

• US 20190326755A1
• Filed: 04/20/2018
• Published: 10/24/2019
• Est. Priority Date: 04/20/2018
• Status: Active Grant

• Current Assignee: Eaton Intelligent Power Limited (Eaton Corporation PLC.)
• Original Assignee: Eaton Intelligent Power Limited (Eaton Corporation PLC.)
• Inventors: Fu, Qiang, Teleke, Sercan
• Granted Patent: US 11,070,060 B2
• Time in Patent Office: Days
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2300/10 The dispersed energy generation being of fossil origin, e.g. diesel generators
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/18 Arrangements for adjusting, eliminating or compensating reactive power in networks for adjustment of voltage H02J3/16
• CPC Class Codes: H02J 3/32 using batteries with converting means
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/12 Monitoring or controlling equipment for energy generation units, e.g. distributed energy generation [DER] or load-side generation
• CPC Class Codes: Y04S 10/14 Energy storage units
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• 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
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

A prediction of an electric power consumption and/or a generation of at least one of a load and a source coupled to an electric power grid is generated responsive to a forecast of an event. A desired state of an asset on the grid is identified responsive to the prediction. A functional representation of a control scheme for the asset is identified based on a sensitivity of the control parameter to a variance in operation of the electric power grid with respect to the prediction.

Claims

1. A method comprising:

generating a prediction of an electric power consumption and/or a generation of at least one of a load and a source coupled to an electric power grid responsive to a forecast of an event;

determining a desired state of a control parameter of an asset on the grid responsive to the prediction; and

identifying a functional representation of a control scheme for the asset based on a sensitivity of the control parameter to a variance in operation of the electric power grid with respect to the prediction.

2. The method of claim 1, wherein the functional representation includes a first function that relates real power to a voltage frequency and a voltage magnitude and a second function that relates reactive power to the voltage frequency and the voltage magnitude.

3. The method of claim 2, wherein identifying a functional representation comprises generating a set of coefficients for the first and second functions.

4. The method of claim 1, further comprising controlling the asset responsive to the functional representation.

5. The method of claim 4, wherein controlling the asset comprises operating a droop control scheme that uses the functional representation.

6. The method of claim 4, wherein the functional representation relates real power to a voltage frequency and a voltage magnitude and relates reactive power to the voltage frequency and the voltage magnitude.

7. The method of claim 4, wherein the asset comprises at least one of a power source and a load.

8. The method of claim 1:

wherein determining a desired state an asset comprises identifying a set point for a controller of the asset; and

wherein identifying a functional relationship comprises performing a sensitivity analysis on the set point.

9. The method of claim 1, wherein identifying a functional representation comprises generating a set of coefficients that define the functional representation.

10. The method of claim 1, wherein the forecast comprises at least one of a weather forecast, an insolation forecast, and an activity forecast and wherein generating a prediction of an electric power consumption and/or a generation comprises generating a prediction of at least one of an electrical generator output and an electric power load from the at least one of a weather forecast, an insolation forecast, and an activity forecast.

11. A non-transitory computer-readable medium having stored thereon a set of instructions that, when executed by a processor of a computer, causes the computer to perform the operations of claim 1.

12. A system comprising:

a source/load predictor configured to generate a prediction of an electric power consumption and/or a generation of at least one of a load and a source coupled to an electric power grid responsive to a forecast of an event;

a power flow determiner configured to determine a desired state of a control parameter of an asset on the grid responsive to the prediction; and

a sensitivity determiner configured to identify a functional representation of a control scheme for the asset based on a sensitivity of the control parameter to a variance in operation of the electric power grid with respect to the prediction.

13. The system of claim 12, wherein the functional representation represents a first function that relates real power to a voltage frequency and a voltage magnitude and a second function that relates reactive power to the voltage frequency and the voltage magnitude.

14. The system of claim 13, wherein the sensitivity determiner is configured to generate a set of coefficients for the first and second functions.

15. The system of claim 13, further comprising an asset controller, wherein the asset controller is configured to control the asset based on the first and second functions.

16. The system of claim 15, wherein the source/load predictor, the power flow determiner and the sensitivity determiner are positioned in a system controller configured to communicate with the asset controller via a communications channel.

17. A method of controlling an asset on an electric power grid, the method comprising:

determining a set point for a control parameter of the asset from a function that reflects a sensitivity of the control parameter to a variance in operation of the electric power grid with respect to a prediction of operation of the electric power grid; and

controlling the asset responsive to the determined set point.

18. The method of claims 17:

wherein determining a set point comprises;

determining a first set point for the asset from a first function that relates real power to a voltage magnitude and a voltage frequency; and

determining a second set point for the asset from a second function that relates reactive power to the voltage magnitude and a voltage frequency; and

wherein controlling the asset comprises controlling the asset responsive to the first and second set points.

19. The method of claim 18, wherein the first set point comprises a real power set point and wherein the second set point comprises a reactive power set point.

20. The method of claim 18, wherein determining of the first and second set points is preceded by receiving coefficients for the first and second functions from a system controller.

21. A non-transitory computer-readable medium having stored thereon a set of instructions that, when executed by a processor of a computer, causes the computer to perform the operations of claim 17.