The Study of Optimized Combustion Tuning for Fossil Power Plant

발전보일러의 최적연소조정에 대한 실험적 연구

  • Jung, Jae-Jin (Doosan Heavy Industries & Construction) ;
  • Song, Jung-Il (Dept. of Mechanical Engineering, Changwon National University)
  • Published : 2009.04.10

Abstract

Fossil power plants firing lower grade coals or equipped with modified system for NOx controls are challenged with maintaining good combustion conditions while maximizing generation and minimizing emissions. In many cases significant derate, availability losses and increase in unburned carbon levels can be attributed to poor combustion conditions as a result of poorly controlled local fuel and air distribution within the boiler furnace. In order to develop a on-line combustion tuning system, field test was conducted at operating power boiler. During the field test the exhaust gases' $O_2$, NOx and CO was monitored by using a spatially distributed monitoring grid located in the boiler's high temperature vestibule and upper convective back-pass region. At these locations, the flue gas flow is still significantly stratified, and air in-leakage is minimal which enables tracing of poor combustion zones to specific burners and over-fire air ports. using these monitored information we can improving combustion at every point within the furnace, therefore the boiler can operate at reduced excess $O_2$ and gas temperature deviation, reduced furnace exit gas temperature levels while also reducing localized hot spots, corrosive gas conditions, slag or clinker formation and UBC. Benefits include improving efficiency, reducing NOx emissions, increasing output and maximizing availability. Discussion concerning the reduction of greenhouse gases is prevalent in the world. When taking a practical approach to addressing this problem, the best way and short-term solution to reduce greenhouse gases on coal-fired power plants is to improve efficiency. From this point of view the real time optimized combustion tuning approach is the most effective and implemented with minimal cost.

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