基于智能计算的锅炉燃烧优化指导系统及其应用

doi:10.11930/j.issn.1004-9649.2014.7.1.4

中国电力 ›› 2014, Vol. 47 ›› Issue (7): 1-5.DOI: 10.11930/j.issn.1004-9649.2014.7.1.4

• 发电 • 下一篇

基于智能计算的锅炉燃烧优化指导系统及其应用

李海山¹, 雎刚², 毛晓飞¹, 余廷芳³

1. 国网江西省电力科学研究院,江西南昌 330096;
2. 东南大学能源与环境学院,江苏南京 210096;
3. 南昌大学机电学院 ,江西南昌 330031

收稿日期:2014-03-13 出版日期:2014-07-18 发布日期:2015-12-10
作者简介:李海山（1974—）,男,江西萍乡人,高级工程师,从事电站低碳节能技术研究。E-mail: lihais@139.com
基金资助:
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）

Guiding System for Boiler Combustion Optimization Based on Artificial Neural Network and Its Application

LI Hai-shan¹, JU GANG², MAO Xiao-fei¹, YU Ting-fang³

1. Jiangxi Province Electric Power Test Research Institute, Nanchang 330096, China;
2. School of Energy and Environmental Engineering, Southeast University, Nanjing 210096, China;
3. School of Mechanical and Electronic Engineering, Nanchang University, Nanchang 330031, China

Received:2014-03-13 Online:2014-07-18 Published:2015-12-10
Supported by:
This work is supported by National Natural Science Foundation of China(61262048) and Energy Saving & Innovation Technology Demonstration Project of Jiangxi Province (20123BBG71023)

摘要/Abstract

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NO_x排放的目的。

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

Abstract: 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 NO_x emissions are also reached simultaneously.

Key words: utility boiler, combustion, guiding system, artificial intelligence, neural network, boiler efficiency

中图分类号:

TK227.1

李海山, 雎刚, 毛晓飞, 余廷芳. 基于智能计算的锅炉燃烧优化指导系统及其应用[J]. 中国电力, 2014, 47(7): 1-5.

LI Hai-shan, JU GANG, MAO Xiao-fei, YU Ting-fang. Guiding System for Boiler Combustion Optimization Based on Artificial Neural Network and Its Application[J]. Electric Power, 2014, 47(7): 1-5.

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https://www.electricpower.com.cn/CN/Y2014/V47/I7/1

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基于智能计算的锅炉燃烧优化指导系统及其应用

Guiding System for Boiler Combustion Optimization Based on Artificial Neural Network and Its Application

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基于智能计算的锅炉燃烧优化指导系统及其应用

Guiding System for Boiler Combustion Optimization Based on Artificial Neural Network and Its Application

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