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浙江大学学报(工学版)
J4  2010, Vol. 44 Issue (6): 1127-1132    DOI: 10.3785/j.issn.1008-973X.2010.06.014
能源工程     
基于变尺度混沌蚁群算法的飞灰中的碳质量分数优化
吴锋, 周昊, 郑立刚, 岑可法
浙江大学 能源清洁利用国家重点实验室,热能工程研究所,浙江 杭州 310027
Application of scaleable chaotic ant colony algorithm in control of
unburned carbon in fly ash
WU Feng, ZHOU Hao, ZHENG Li-gang, CEN Ke-fa
State Key Laboratory of Clean Energy Utilization, Institute for Thermal Power Engineering, Zhejiang University, Hangzhou 310027, China
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摘要：

为了降低燃煤锅炉飞灰中的碳质量分数,利用支持向回归（SVR）建立了大型四角切圆燃烧锅炉的碳质量分数模型.利用大样本量的热态实炉碳质量分数实验数据对模型进行了训练和验证,利用变尺度混沌蚁群算法结合该模型对锅炉的运行参数进行优化.计算结果表明：SVR模型具有很好的泛化性和预测精度;变尺度蚁群算法能实现全局寻优,降低飞灰中的碳质量分数,而且具有很高的稳定性和鲁棒性,其快速的收敛寻优能力也非常适于在线应用；支持向量机与变尺度蚁群算法的结合使用可以有效地实现燃烧优化,降低飞灰中的碳质量分数是控制锅炉飞灰中碳质量分数的有效工具.
Abstract:

 In order to control the unburned carbon in fly ash of the coalfired boiler, support vector regression (SVR) was employed to establish a mathematic model to predict the characteristics of unburned carbon in fly ash in large capacity cornerfired boilers. A large number of field test data from a fullscale operating boiler was used to train and validate the SVR model. A scaleable chaotic ant colony optimization (SCACO) was combined with carbon content of fly ash model to optimize the operating parameters of the boiler. The computational results show that the generalization and accuracy of SVR are very good. SCACO reduces carbon content of fly ash with high stability and robustness. Its fast convergence suits for online applications. The hybrid algorithm combining SVR and SCACO provides a effective way to control the unburned carbon in fly ash.
出版日期: 2010-07-16
:  TK 223  
基金资助:

浙江省自然科学基金资助项目（R107532）；全国优秀博士学位论文作者专项资金资助项目（200747）；新世纪优秀人才支持计划资助项目（NCET070761）；浙江大学曹光彪高科技发展基金资助项目（2008RC001）；国家重点基础研究发展计划资助项目（2009CB219802）；中央高等学校基本科研经费专项资金资助项目（2009QNA4042；2）.
通讯作者: 周昊,男,教授.     E-mail: zhouhao@cmee.zju.edu.cn
作者简介: 吴锋(1983—）,男,河北邯郸人,博士生,从事低污染燃烧与燃烧优化的研究.E-mail:wufeng0314@gmail.com
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引用本文:

吴锋, 周昊, 郑立刚, 岑可法. 基于变尺度混沌蚁群算法的飞灰中的碳质量分数优化[J]. J4, 2010, 44(6): 1127-1132.

TUN Feng, ZHOU Hao, ZHENG Li-Gang, CEN Ge-Fa. Application of scaleable chaotic ant colony algorithm in control of
unburned carbon in fly ash. J4, 2010, 44(6): 1127-1132.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2010.06.014    或    http://www.zjujournals.com/eng/CN/Y2010/V44/I6/1127

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