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| 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 3 |
| Format | application/pdf |
| OCR Text | Figure 2 shows the informational flow for the GNOCIS implementation at Gaston. All process data is collected through the DCS and passed on to the GNOCIS host (a PC running WindowsNT) for calculation of the recommendations. These recommendations are then conveyed to the operator via the DCS operator displays. If acceptable, the operator can then implement these changes through the DCS operator displays. Also, th,e operator has the option of running GNOCIS closedloop in which the recommendations are automatically implemented. The primary operator display, which resides on the DCS, is shown in Figure 3. Open-Loop Operator Displays n Advise Current Operating Conditions Model Development A pprove d Setpoints .. - L&N MAX 1000 -- A~ ~ctuator Demands Closed-Loop GNOCIS ~ L&N MAX 1000 , . Data AcqUistlon Figure 2. Gaston I GNOCIS Installation Figure 3. Gaston/GNOCIS Operator Interface Plant --- Process Data Recommendation Based on Current Mill Configuration Recommendation Based on Best Mill Configuration Remove/Add Parameter from Optimization Consideration Data collected through the DCS was used to create the combustion models. Although in excess of 1000 pOints are being archived in the DCS, early in the project, a subset of approximately 100 parameters were identified as being possibly important for combustion modeling purposes. Modeling efforts have concentrated on the most recent three to four months of long-term data. Short-term tests were run periodically during which the unit was run at off-design conditions to augment data available from normal operation and thereby expand the range over which the combustion model could make estimates. Also, results from testing GNOCIS were generally included in the training data for future models. The collected data was preprocessed to remove invalid data and to some extent, data collected during transients. In general, the existing control system and instrumentation provided an excellent platform for the collection of real-time process data in a format usable by GNOCIS. 3 |
| Setname | uu_afrc |
| ID | 12696 |
| Reference URL | https://collections.lib.utah.edu/ark:/87278/s61c20h3/12696 |