摘要
锅炉燃烧调整试验获得的优化工况不能满足电厂煤质和机组负荷变化的要求,因此开发了在线燃烧优化技术.它以连续监测烟气成分为基础,实时确定炉膛高温腐蚀速率,同时利用支持向量机对锅炉效率和NOx排放浓度建模和遗传算法寻优,在线获得安全、经济和环保的锅炉运行工况.实际应用表明,该技术确定的优化工况实现了煤质及机组负荷的耦合,提高了锅炉效率,降低了NOx排放浓度.
Since the optimal setpoint of boiler obtained by combustion adjusting test could not meet the requirement of the variation of coal quality and unit load, an on-line combustion optimization technology is developed. Based on continuous monitoring of flue gas components, the real-time high temperature erosion rate of furnace can be confirmed. With support vector machine, boiler efficiency and NOx emission models are build. Then by use of genetic algorithms, the safe, economical and clean operating parameters can be obtained. The application results show that the optimal setpoint obtained by this technology can adapt the variation of coal quality and unit load, improve boiler efficiency and decrease the NOx emission concentration.
出处
《动力工程》
EI
CSCD
北大核心
2008年第1期33-35,53,共4页
Power Engineering
关键词
能源与动力工程
锅炉
燃烧优化
烟气成份
连续监测
遗传算法
支持向量机
energy and power engineering
boiler
combustion optimization
flue gas components
continuous monitoring
genetic algorithms
support vector machine
