Simultaneous boiler optimization of efficiency, emission, and reliability utilizing neural network modeling
Boiler performance optimization includes the preservation of efficiency, emission, capacity, and reliability. Competitive pressures require cost reduction and environmental compliance. It is a challenge for utility personnel to balance these requirements and to achieve specific company goals. Unfortunately, these requirements often demand tradeoffs. The Clean Air Act Amendment requires Utilities to reduce NO{sub x} emission. NO{sub x} emission reduction has often been accomplished by installation of new low NO{sub x} burners. Boiler tuning for NO{sub x} control can be used as an alternative to low NO{sub x} burner installation. A PC-based computer software program was developed to assist the tuning process. This software, System Optimization Analysis Program (SOAP), is a neural network based code which uses the self-adaptation learning process, with an adaptive filter added for data noise control. SOAP can use historical data as the knowledge base and it provides a fast optimal solution to adaptive control problems. SOAP was tested at several fossil plants. The tests were primarily for NO{sub x} reduction, but the performance parameters were optimized simultaneously.
- Research Organization:
- Electric Power Research Inst. (EPRI), Palo Alto, CA (United States); Baltimore Gas and Electric Co., MD (United States)
- OSTI ID:
- 401957
- Report Number(s):
- EPRI-TR-106753; CONF-960719-; TRN: 96:005874-0041
- Resource Relation:
- Conference: Fossil plant maintenance conference, Baltimore, MD (United States), 29 Jul - 1 Aug 1996; Other Information: PBD: Jul 1996; Related Information: Is Part Of Proceedings: 1996 EPRI fossil plant maintenance conference; PB: 677 p.
- Country of Publication:
- United States
- Language:
- English
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