摘要
提出一基于智能计算技术的锅炉燃烧优化实时指导系统,该系统根据电科院现场燃烧调整试验数据以及锅炉运行历史数据,采用人工智能神经网络建立了锅炉燃烧特性的NSGA-Ⅱ数学模型,将现场燃烧调整试验数据结果和日常司炉的运行经验模型化,并采用多目标遗传算法优化技术从模型中提取专家级燃烧运行知识和经验,通过计算机在线指导锅炉配风、配煤等燃烧运行调整,达到同时提高锅炉运行效率和减小NOx排放的目的。
In this paper,a real-time guiding system for boiler combustion optimization based on artificial intelligence technology is proposed,in which the NSGA-Ⅱ mathematical model is established by adopting neural artificial intelligence network in combination with the data of coal-fired boiler combustion adjustment test and historical operation.By using this approach,the modeling of the field combustion adjustment test data and the operator＇s daily experience is realized,and the expert knowledge and experience are obtained with the multi-objective genetic algorithm.Consequently,through the online computational guidance for the adjustment of combustion air and fuel,the goal of improving the boiler efficiency and reducing the NOx emissions are also reached simultaneously.
出处
《中国电力》
CSCD
北大核心
2014年第7期1-5,共5页
Electric Power
基金
国家自然科学基金项目(61262048)
江西省节能减排科技创新示范科技项目(20123BBG71023)~~
关键词
电站锅炉
燃烧
指导系统
人工智能
神经网络
锅炉效率
utility boiler
combustion
guiding system
artificial intelligence
neural network
boiler efficiency
