Boiler Performance Improvement Due to Intelligent Sootblowing Utilizing Real-Time Boiler Modeling

Boiler Performance Improvement Due to Intelligent Sootblowing Utilizing Real-Time Boiler Modeling

Presented to: Power-Gen International
November 30 – December 2, 2004
Orlando, Florida, USA

G. J. Nakoneczny - Babcock & Wilcox - Barberton, Ohio, USA

R. S. Conrad - Babcock & Wilcox - Barberton, Ohio, USA

I. Vulicevic - Babcock & Wilcox - Barberton, Ohio, USA

K. A. Larson - Babcock & Wilcox - Barberton, Ohio, USA

K. L. Noel - MidAmerican Energy Company - Muscatine, Iowa, USA

M. W. Carlisle - Alabama Power Company - Quinton, Alabama, USA


To achieve optimum boiler operation and performance it is necessary to control the cleanliness and limit the fouling of the heat transfer surfaces. Historically, the heating surfaces were cleaned by air-blowing, steam-blowing, or water-blowing sootblowers on a scheduled timebased interval. With the advent of fuel switching strategies such as changing from bituminous to Powder River Basin coals to reduce emissions, the control of heating surface cleanliness has become more problematic for many steam generator owners. A scheduled cleaning approach does not easily address changes in operation. Also, as power plant operators push to achieve greater efficiency and performance from their boilers, the ability to more effectively optimize cleaning cycles has become increasingly important. Sootblowing, only when and where it is required to maintain unit performance, can reduce unnecessary blowing, save on steam utilization, and reduce tube erosion and wear.

B&W's core technology for boiler design is based on modeling of boiler heating surfaces to establish heating surface requirements and performance. The modeling process also must consider fuel types and the combustion requirements. This same technology is used to model the expected performance of existing units. By establishing the boiler model it is possible to accurately determine when and where heating surfaces are experiencing diminished performance due to ash buildup and fouling.

The ability to model the heating surface and determine real-time cleanliness indexes is important in developing a system that can more accurately initiate the cleaning cycle of the boiler heating surfaces. The performance of the individual convection pass banks is interrelated; consequently, determining the best sootblowing program must not only rely on the cleanliness of the specific bank to initiate or trigger blowing. By coupling the real-time cleanliness index data with the measured operating parameters of the boiler it is possible to establish rule-based logic to drive sootblower operation.

Presented in this paper is the approach taken by The Babcock & Wilcox Company in developing the Powerclean™ system, a sootblowing optimization system. Also presented are the performance improvements made with the Powerclean™ system at two utilities in the USA – MidAmerican Energy’s Louisa Generating Station and Alabama Power’s Plant Miller.

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