Boiler Combustion Control Model of Large-scale Coal-fired Power Plant with Asymmetric Artificial Neural Networks

被引：0

作者：

Chen, Xiaowen ^{[1
]}

Gao, Lin ^{[2
]}

Zhou, Junbo ^{[2
]}

Gao, Haidong ^{[2
]}

Wang, Lin ^{[2
]}

Wang, Xingwu ^{[1
]}

Chen, Baixu ^{[3
]}

机构：

[1] Yellow River Upstream Hydropower Dev Ltd Liabil C, Xining, Qinghai, Peoples R China

[2] Xian Thermal Power Res Inst Co Ltd, Xian, Shaanxi, Peoples R China

[3] North China Elect Power Univ, Beijing, Peoples R China

来源：

PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC) | 2017年

关键词：

boiler; ANN; asymmetric ANN; combustion control;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Key problems in coal-fired boiler combustion modeling were discussed in large-scale power plants. An asymmetric artificial neural network (ANN) model is proposed, where general forward multilayer ANN model structure is transformed to the domestic problems. Which greatly reduces the demands for the number of modeling samples. The comparison results show that the proposed model is more effective than the classical ones. It was applied on optimization of the combustion control in a 660MW supercritical boiler and good performances had been observed.

引用

页码：980 / 983

页数：4

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