摘要
对某 6 0 0MW燃煤电站锅炉进行了多工况热态NOx 排放特性测量 ,在利用多层前向神经网络对该锅炉的NOx 排放特性进行建模的基础上 ,将神经网络模型与模拟退火全局优化算法相结合 ,实现了锅炉的低NOx 燃烧的优化 ,计算得到可获得低NOx 排放浓度的具体燃烧配风方案 .文中对 2种不同退火参数的模拟退火算法进行了比较 ,结果说明采用T0 =5 0K ,α=0 .6的参数可以获得较好的寻优效果 .本文研究结果为实现大型电站锅炉低NOx 燃烧控制的在线优化技术打下了基础 .
With the developing restrict environmental protection demand, more attention was paid on the low NO x combustion optimizing technology for its cheap and easy property. In this work, field experiments on the NO x emissions characteristics of a 600MW coal-fired boiler were carried out, on the base of the artificial neural network (ANN) modeling, the simulated annealing (SA) algorithm was employed to optimize the boiler combustion to achieve a low NO x emissions concentration, and the combustion scheme was obtained. Two sets of SA parameters were adopted to find a better SA scheme, the result show that the parameters of T 0=50K,α=0.6 can lead to a better optimizing process. This work can give the foundation of the boiler low NO x combustion on-line control technology.
出处
《环境科学》
EI
CAS
CSCD
北大核心
2003年第6期63-67,共5页
Environmental Science
基金
国家自然科学基金资助项目 (5 0 2 0 6 0 18)
国家重点基础研究发展规划项目 (G2 0 0 1CB40 96 0 0
G19990 2 2 2 0 4)
