GNOCIS an update of the generic NO{sub x} control intelligent system
Technical Report
·
OSTI ID:269437
GNOCIS is an on-line enhancement to existing power plant Digital Control Systems (DCS) designed to reduce NO{sub x} emissions while meeting other operational constraints, such as heat rate and CO emissions. It can also be used to minimize unburned carbon while meeting a specified NO{sub x} limit, or any combination of emissions/performance variables that can be quantified by a common metric and are affected by DCS - adjustable parameters. The core of the system is an adaptive neural network model of the NO{sub x} generation characteristics of the boiler. The software applies an optimizing procedure to identify the best setpoints for the plant. The recommended setpoints can be either conveyed to the operator via the DCS in an advisory mode, or implemented automatically in a closed-loop mode. GNOCIS is designed to run on a stand-alone workstation connected to the DCS via the data highway. Sensor validation techniques have been incorporated. The goal for GNOSIS is to deliver 10-35% reductions in NO{sub x} from baseline conditions while maintaining or improving other operational constraints. Preliminary results are presented for demonstrations at two power plants: (1) 500-MW T-fired boiler at PowerGen`s Kingsnorth Station, (2) 250-MW Opposed-fired boiler at Alabama Power Company`s Gaston Station.
- Research Organization:
- Electric Power Research Inst., Palo Alto, CA (United States)
- OSTI ID:
- 269437
- Report Number(s):
- EPRI-TR--105978-V2; CONF-9505150--Vol.2
- Country of Publication:
- United States
- Language:
- English
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