Cloud-level analytics for boiler networks

• US 10,208,947 B2
• Filed: 12/05/2014
• Issued: 02/19/2019
• Est. Priority Date: 03/26/2014
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Maturana, Francisco, Asenjo, Juan L.
• Primary Examiner(s): Sasaki, Shogo
• Application Number:
  US14/562,233
• Publication Number:
  US 20150276208A1
• Time in Patent Office: 1,537 Days
• CPC Class Codes: F22B 35/18 Applications of computers to steam boiler control
• CPC Class Codes: G05B 13/04 involving the use of models or simulators
• CPC Class Codes: G06F 9/5072 Grid computing

Abstract

A boiler control system executing on a cloud platform facilitates remote control system analysis and generation of suitable set point parameters for a given boiler application. The system includes a system interface component, a modeling component and a correlation analytics component. The system interface component collects industrial data associated with a set of boilers and demand data associated with a set of loads. The system interface component also stores the industrial data and the demand data on a cloud platform. The modeling component generates a boiler behavioral model for storage on the cloud platform based on analysis of the industrial data and the demand data. The boiler behavioral model defines at least one correlation between efficiency and capacity associated with the set of boilers. The correlation analytics component determines at least one set point parameter for the set of boilers based on analysis of the boiler behavioral model.

Claims

1. A cloud system communicatively coupled over a public network to a manufacturing system comprising a set of boilers, the cloud system comprising:

a memory having stored thereon computer-executable components;

a processor, operatively coupled to the memory, that executes the computer-executable components, the computer-executable components comprising;

a system interface component configured to collect, over the public network, industrial data associated with an executing process of the set of boilers associated with a set of loads and demand data associated with the set of loads associated with the set of boilers, and store the industrial data and the demand data on the cloud system;

a modeling component configured to generate a boiler behavioral model based on an analysis of the industrial data and the demand data, wherein the boiler behavioral model comprises at least one-efficiency curve between efficiency and capacity associated with the set of boilers, and store the boiler behavioral model on the cloud system; and

a correlation analytics component configured to determine a respective value for each of at least one set point parameter for the set of boilers based on an iterative analysis of the boiler behavioral model and a defined optimization criterion; and

wherein the system interface component further configured to issue a control command over the public network to at least one controller associated with the set of boilers, wherein the control command is configured to control the controller to employ the respective values of the at least one set point parameter during execution of the executing process of the set of boilers.

2. The cloud system of claim 1, further comprising a client interface component that sends the respective values of the at least one set point parameter to a client device communicatively connected to the cloud system.

3. The cloud system of claim 1, wherein the correlation analytics component is further configured to simulate an operating scenario for the set of boilers represented by initial conditions based on the boiler behavioral model.

4. The cloud system of claim 3, wherein the correlation analytics component is further configured to determine whether the operating scenario for the set of boilers is associated with a maximum efficiency.

5. The cloud system of claim 4, wherein the correlation analytics component is further configured to modify the initial conditions in response to a determination that the operating scenario for the set of boilers is not associated with the maximum efficiency.

6. The cloud system of claim 4, wherein the correlation analytics component is further configured to generate the respective values of the at least one set point parameter in response to a determination that the operating scenario for the set of boilers is associated with the maximum efficiency.

7. The cloud system of claim 3, wherein the correlation analytics component is further configured to apply a set of operational rules for the operating scenario.

8. The cloud system of claim 1, wherein the system interface component is further configured to generate one or more data sets based on the industrial data and the demand data.

9. The cloud system of claim 1, wherein the system interface component is further configured to receive at least a portion of the industrial data as a data packet from a cloud agent device associated with one or more of the set of boilers.

10. A method executed by a cloud system comprising at least one processor and communicatively coupled over a public network to an industrial boiler system comprising one or more boilers, the method comprising:

receiving, over a public network by the cloud system comprising at least one processor, industrial data from the one or more boilers associated with a currently executing process of the industrial boiler system associated with one or more loads and demand data from the one or more loads of the industrial boiler system;

creating, by the cloud system, a boiler behavioral model based on analysis of the industrial data and the demand data, wherein the boiler behavioral model comprises at least one-efficiency curve between efficiency and capacity associated with the one or more boilers;

storing, by the cloud system, the boiler behavioral model on the cloud-based system;

determining, by the cloud system, a respective value for each of at least one set point parameter for the one or more boilers based on an iterative analysis of the boiler behavioral model and a defined optimization criterion; and

issuing, by the cloud system over the public network, a control command to at least one controller associated with the one or more boilers, wherein the control command initiates the controller to employ the respective values of the at least one set point parameter during execution of the executing process of the industrial boiler system.

11. The method of claim 10, further comprising sending, by the cloud system, the respective values of the at least one set point parameter to a client device that has authorization to access the cloud system.

12. The method of claim 10, further comprising simulating, by the cloud system, an operating scenario for the one or more boilers represented by initial conditions based on the boiler behavioral model.

13. The method of claim 12, further comprising determining, by the cloud system, whether the operating scenario for the one or more boilers is associated with a maximum efficiency.

14. The method of claim 13, further comprising modifying, by the cloud system, the initial conditions in response to a determination that the operating scenario for the one or more boilers is not associated with the maximum efficiency.

15. The method of claim 13, further comprising generating, by the cloud system, the respective values of the at least one set point parameter in response to a determination that the operating scenario for the one or more boilers is associated with the maximum efficiency.

16. The method of claim 12, further comprising applying, by the cloud system, a set of operational rules for the operating scenario.

17. The method of claim 10, wherein the receiving comprises:

receiving at least a portion of the industrial data as a data packet from a cloud agent device associated with the one or more boilers; and

processing the data packet in accordance with header information included in the data packet.

18. A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause a cloud system comprising a processor and communicatively coupled over a public network to an industrial boiler system comprising one or more boilers to perform operations comprising:

receiving, over the public network, industrial data from the one or more boilers associated with a currently executing process of the industrial boiler system associated with one or more loads and demand data from the one or more loads of the industrial boiler system;

generating a boiler behavioral model based on analysis of the industrial data and the demand data, wherein the boiler behavioral model comprises at least one efficiency curve between efficiency and capacity associated with the one or more boilers;

storing the boiler behavioral model;

generating a respective value for each of at least one set point parameter for the one or more boilers based on an iterative analysis of the boiler behavioral model and a defined optimization criterion;

transmitting, over the public network, a control command to at least one controller associated with the one or more boilers, wherein the control command controls the controller to employ the respective values of the at least one set point parameter during execution of the executing process of the industrial boiler system.

19. The non-transitory computer-readable medium of claim 18, the operations further comprising initiating a sending of the respective values of the at least one set point parameter to a client device.

20. The non-transitory computer-readable medium of claim 18, the operations further comprising simulating an operating scenario for the one or more boilers represented by initial conditions based on the boiler behavioral model.