Method and system for SNCR optimization

• US 20060052902A1
• Filed: 08/25/2005
• Published: 03/09/2006
• Est. Priority Date: 08/27/2004
• Status: Abandoned Application

• Current Assignee: NeuCo Incorporated (General Electric Company)
• Original Assignee: NeuCo Incorporated (General Electric Company)
• Inventors: Kohn, Daniel W., Lefebvre, Curt W.
• Application Number:
  US11/211,418
• Publication Number:
  US 20060052902A1
• Time in Patent Office: Days
• US Class Current: 700/266
• CPC Class Codes: B01D 2251/206 Ammonium compounds
• CPC Class Codes: B01D 53/346 Controlling the process
• CPC Class Codes: B01D 53/56 Nitrogen oxides B01D53/60 takes precedence
• CPC Class Codes: F23J 15/003 for supplying chemicals to fumes, e.g. using injection devices
• CPC Class Codes: F23J 2215/10 Nitrogen; Compounds thereof
• CPC Class Codes: F23J 2219/20 Non-catalytic reduction devices
• CPC Class Codes: F23J 7/00 Arrangement of devices for supplying chemicals to fire
• CPC Class Codes: G05B 13/027 using neural networks only

Abstract

A method and system are provided for controlling SNCR performance in a fossil fuel boiler. A performance goal for the boiler and data on current boiler performance is obtained. A determination is made as to whether the performance goal is satisfied by the current boiler performance. When the performance goal is not satisfied, the generally closest operating region in which the performance goal would be satisfied is identified. The operating region is associated with desired operating parameters of one or more devices affecting SNCR performance. One or more control moves are determined using the desired operating parameters of the one or more devices for directing the boiler to the operating region. The one or more control moves are communicated to the one or more devices.

Claims

1. A method for controlling SNCR performance in a fossil fuel boiler, comprising the steps of:

(a) obtaining a performance goal for the boiler;

(b) obtaining data on current boiler performance;

(c) determining whether the performance goal is satisfied by the current boiler performance;

(d) when the performance goal is not satisfied, identifying the generally closest operating region in which the performance goal would be satisfied, the operating region being associated with desired operating parameters of one or more devices affecting SNCR performance;

(e) determining one or more control moves using the desired operating parameters of said one or more devices for directing the boiler to the operating region; and

(f) communicating the one or more control moves to said one or more devices.

2. The method of claim 1 wherein said one or more devices include one or more of:

reagent injectors for controlling reagent profiles in one or more generally cross-sectional areas of said boiler, sootblowers for controlling reaction rate profiles in one or more generally cross-sectional areas of said boiler, and fuel and air injectors for controlling NO_x profiles in one or more generally cross-sectional areas of said boiler.

3. The method of claim 2 wherein said reagent comprises ammonia or urea.

4. The method of claim 1 wherein the performance goal for the boiler comprises maintaining NO_x or reagent output of the plant in a favorable range.

5. The method of claim 1 wherein the performance goal for the boiler comprises maintaining NO_x or reagent variability across a given generally cross-sectional area of the boiler in a favorable range.

6. The method of claim 1 further comprising periodically repeating steps (a) to (f).

7. The method of claim 1 wherein steps (c), (d) and (e) are performed using a direct controller.

8. The method of claim 1 wherein steps (c), (d) and (e) are performed using an indirect controller with a system model that relates operating parameters of the one or more devices to the boiler performance parameters.

9. The method of claim 8 wherein said system model is a neural network.

10. The method of claim 8 wherein said system model is a mass-energy balance model.

11. The method of claim 8 wherein said system model is a genetically programmed model.

12. The method of claim 8 further comprising the step of storing information about the one or more control moves and corresponding measured boiler performance values and retraining the system model using the stored information.

13. A system for controlling SNCR performance in a fossil fuel boiler, comprising:

a controller input for receiving a performance goal for the boiler, and data on current boiler performance;

a controller for determining whether the performance goal is satisfied by the current boiler performance, and when the performance goal is not satisfied, identifying the generally closest operating region in which the performance goal would be satisfied, the operating region being associated with desired operating parameters of one or more devices affecting SNCR performance, said controller also determining one or more control moves using the desired operating parameters of said one or more devices for directing the boiler to the operating region; and

a controller output for communicating the one or more control moves to said one or more devices.

14. The system of claim 13 wherein said one or more devices include one or more of:

reagent injectors for controlling reagent profiles in one or more generally cross-sectional areas of said boiler, sootblowers for controlling reaction rate profiles in one or more generally cross-sectional areas of said boiler, and fuel and air injectors for controlling NO_x profiles in one or more generally cross-sectional areas of said boiler.

15. The method of claim 14 wherein said reagent comprises ammonia or urea.

16. The system of claim 13 wherein the performance goal for the boiler comprises maintaining NO_x or reagent output of the plant in a favorable range.

17. The system of claim 13 wherein the performance goal for the boiler comprises maintaining NO_x or reagent variability across a given generally cross-sectional area of the boiler in a favorable range.

18. The system of claim 13 wherein said controller is a direct controller.

19. The system of claim 13 wherein said controller is an indirect controller with a system model that relates operating parameters of the one or more devices to the boiler performance parameters.

20. The system of claim 19 wherein said system model is a neural network.

21. The system of claim 19 wherein said system model is a mass-energy balance model.

22. The system of claim 19 wherein said system model is a genetically programmed model.

23. The system of claim 19 further comprising a storage for storing information about the one or more control moves and corresponding measured boiler performance values, and wherein the system model is retrained using the stored information.

24. A computer program product, residing on a computer readable medium, for use in controlling SNCR performance in a fossil fuel boiler, the computer program product comprising instructions for causing a computer to:

receive a performance goal for the boiler;

receive data on current boiler performance;

determine whether the performance goal is satisfied by the current boiler performance;

when the performance goal is not satisfied, identify the generally closest operating region in which the performance goal would be satisfied, the operating region being associated with desired operating parameters of one or more devices affecting SNCR performance;

determine one or more control moves using the desired operating parameters of said one or more devices for directing the boiler to the operating region; and

communicate the one or more control moves to said one or more devices.

25. The computer program product of claim 24 wherein said one or more devices include one or more of:

reagent injectors for controlling reagent profiles in one or more generally cross-sectional areas of said boiler, sootblowers for controlling reaction rate profiles in one or more generally cross-sectional areas of said boiler, and fuel and air injectors for controlling NO_x profiles in one or more generally cross-sectional areas of said boiler.

26. The computer program product of claim 25 wherein said reagent comprises ammonia or urea.

27. The computer program product of claim 24 wherein the performance goal for the boiler comprises maintaining NO_x or reagent output of the plant in a favorable range.

28. The computer program product of claim 24 wherein the performance goal for the boiler comprises maintaining NO_x or reagent variability across a given generally cross-sectional area of the boiler in a favorable range.

29. The computer program product of claim 24 wherein the computer program product defines a direct controller.

30. The computer program product of claim 24 wherein the computer program product defines an indirect controller with a system model that relates operating parameters of the one or more devices to the boiler performance parameters.

31. The computer program product of claim 30 wherein said system model is a neural network.

32. The computer program product of claim 30 wherein said system model is a mass-energy balance model.

33. The computer program product of claim 30 wherein said system model is a genetically programmed model.

34. The computer program product of claim 30 further comprising instructions for causing the computer to store information about the one or more control moves and corresponding measured boiler performance values and retrain the system model using the stored information.