摘要
基于效率和低NOx排放目标的锅炉燃烧整体优化是指实时地提出同时优化效率和低NOx排放目标的操作,而其中锅炉效率和NOx排放模型的精度以及优化算法的效率尤为重要。该文基于改进MRAN算法的锅炉燃烧效率和NOx排放模型以及基于实数编码的遗传优化算法,对电站锅炉的燃烧过程进行优化仿真。结果表明,改进的MRAN算法和基于实数编码的遗传算法应用在电站锅炉的效率和低NOx排放目标燃烧优化上是有效的,可以得到按一定目标函数的锅炉效率和低NOx排放目标的实时整体优化效果。
Boilers combustion global optimization on efficiency and low NOx emissions object is proposing operations on line for considering efficiency and low NOx emissions object simultaneously. According to this problem, Boilers efficiency and NOx emissions model precision and optimization algorithm efficiency are very important. Simulation studies on boilers efficiency and low NOx emissions object combustion global optimization are carried out by improved MRAN algorithm on combustion efficiency and low NOx emissions object and genetic algorithm on real coding. The results show improved MRAN algorithm and genetic algorithm on real coding are effective on efficiency and low NOx emissions object combustion optimization for the power station boilers. The proposed algorithms can get global optimum conditions of boilers efficiency and low NOx emissions object online for a certain object function.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2006年第4期46-50,共5页
Proceedings of the CSEE
关键词
热能动力工程
最小资源分配网络
氮氧化物
遗传算法
Thermal power engineering
Miminal resource allocating networks （MRAN）
NOx
Genetic algorithm
