Neural Network-Based Combustion Optimization Reduces NO_x Emissions While Improving Performance

摘要

This paper presents the benefits of applyign an on-line, real-time neural network to several bituminous coal fired utility boilers. The system helps reduce NOx emissions up to 60percent, meeting compliance while it improves heat rate up to 2percent overal (5percent at low load) and reduces LOI as much as 30percent through combustion optimization alone. The system can avoid or postpone large capital expenditures for low NOx burners, overfire air boiler modifications, SCRs, and SNCRs.