Page 7

Update Item Information
Title GNOCIS a Tool for Continuous Combustion Optimization of Utility Boilers
Creator Menzies, Bill; Sorge, John; Stallings, Jeff
Publisher Digitized by J. Willard Marriott Library, University of Utah
Date 1996
Spatial Coverage presented at Baltimore, Maryland
Abstract GNOCIS (Generic NOx Control lntelligent System) is a methodology that can result in improved boiler efficiency and reduced NOx emissions from fossil fuel fired boilers. Using a numerical model of the combustion process, GNOCIS applies an optimizing procedure to identify the best set points for the plant on a continuous basis. The optimization occurs over a wide range of operating conditions. Once determined, the recommended setpoints can be implemented automatically without operator intervention (closed-loop), or, at the plant's discretion, conveyed to the plant operators for implementation (open-loop). GNOCIS is designed to run on a stand-alone workstation networked to the digital control system, or internally on some digital control systems. The developmental sites for GNOCIS are Alabama Power Company's Gaston Unit 4, a 270 MW wallfired unit, and PowerGen's Kingsnorth Unit 1, a 500 MW tangentially-fired unit. This paper provides a general overview of the technology and results from testing at these two locations. In addition, GNOCIS is also being installed on other utility boilers and results will be presented from these sites as available. The development of GNOCIS was funded by a consortium consisting of the Electric Power Research Institute, PowerGen, Southern Company, Radian International, U.K. Department of Trade and Industry, and U.S. Department of Energy.
Type Text
Format application/pdf
Language eng
Rights This material may be protected by copyright. Permission required for use in any form. For further information please contact the American Flame Research Committee.
Conversion Specifications Original scanned with Canon EOS-1Ds Mark II, 16.7 megapixel digital camera and saved as 400 ppi uncompressed TIFF, 16 bit depth.
Scanning Technician Cliodhna Davis
ARK ark:/87278/s61c20h3
Setname uu_afrc
ID 12701
Reference URL https://collections.lib.utah.edu/ark:/87278/s61c20h3

Page Metadata

Title Page 7
Format application/pdf
OCR Text Show
Setname uu_afrc
ID 12700
Reference URL https://collections.lib.utah.edu/ark:/87278/s61c20h3/12700