摘要
提出了一种锅炉运行优化的系统框架,并着重对建模方法和优化算法进行了讨论。采用一种改进的在线支持向量机方法对学习样本进行处理,并与常规支持向量机模型相结合,形成了一种自适应建模方法,以适应煤质与锅炉实际运行工况的变化。对多目标优化算法进行讨论,并介绍了NSGA II遗传算法在锅炉优化中的应用。以某大型电站锅炉为对象,对本文方法进行了应用研究,所建模型的趋势分析和测试结果均表明了本文算法的正确性,所提出的优化模型以NOx为目标函数,综合考虑了锅炉运行经济性和安全性等约束条件,优化结果表明通过运行参数的优化调整可有效降低锅炉污染物的排放。
A new boiler operation optimization system,based on a new adaptive modeling method and genetic algorithm,was proposed in this paper.Based on an improved support vector regression method with modified criterion for selection of the unwanted trained sample while continuously training of prediction model,a new modeling method was given for adaptively prediction,such that the deviation caused from the variation of coal quality and different operating points can be effectively compensated.The multi-objective optimization algorithm,NAGA II,is included in the proposed optimization scheme.The scheme is further illustrated in a real process of a coal-fired boiler.The analysis and test results of the parametric models were presented.An optimization model,including objective function and constraints,was also given in this paper,and the optimization results revealed the validity of the proposed method.
出处
《锅炉技术》
北大核心
2011年第4期18-22,共5页
Boiler Technology
关键词
燃煤锅炉
优化
模型
算法
coal-fired boiler
optimization
model
algorithm
