文档介绍：第 24 卷第 4 期中国电机工程学报
2004 年 4 月 Proceedings of the CSEE ©2004 .
文章编号:0258-8013 (2004) 04-0184-05 中图分类号:TK31 文献标识码:A 学科分类号:470⋅2040
人工智能技术在电站锅炉燃烧优化中的应用研究
王培红, 李磊磊, 陈强, 董益华
(东南大学动力系,江苏南京 210096)
RESEARCH ON APPLICATIONS OF ARTIFICIAL INTELLIGENCE TO
COMBUSTION OPTIMIZATION IN A COAL-FIRED BOILER
WANG Pei-hong, LI Lei-lei, CHEN Qiang, DONG Yi-hua
(Southeast University, Nanjing 210096,China)
ABSTRACT: Coal-fired boiler operation is confronted with two 1 引言
requirements to reduce its operation cost and to lower its emission.
In order to improve the efficiency and to reduce the emission in 锅炉燃烧过程中锅炉热效率与 NOx 排放的影响
combustion, a model of a coal-fired boiler for NOx emission and 因素大部分相同,但具有矛盾的要求。确定兼顾锅炉
efficiency response characteristics is needed. Such a modeling is 热效率和 NOx 排放两个目标的运行优化方案是本文
quite difficult, due to the huge boiler architecture, complicated
的研究目标。本文在电站锅炉热效率与 NOx 排放的
operating conditions, coal sort variation and etc. Based on the data
响应特性模型研究的基础上,进行了锅炉高效低污染
of bustion experiment, a new approach bine
work with function-type mode is developed, which 燃烧优化问题的数学描述。针对本文所述优化问题的
results in a mixed model of NOx emission and boiler efficiency 数学模型特点,采用改进的十进制实数编码的遗传算
response characteristics model. Based on the model, we apply 法作为优化算法。数值实验与优化试验结果的一致
decimal ic algorithm to solve the control pr