江苏科技信息 ›› 2016, Vol. 33 ›› Issue (3): 61-62.doi: 10.3969/j.issn.1004-7530.2016.03.023

• 论文 • 上一篇    下一篇

基于数据特征量挖掘技术的锅炉吹灰优化系统研究

丁勇, 蒋欢春, 李相龙   

  1. 江苏阚山发电有限公司,江苏徐州,221134;上海明华电力技术工程有限公司,上海,200090
  • 出版日期:2016-01-25 发布日期:2016-01-25

Research on the Optimization System of Boiler Soot Blowing Based on Data Features Mining Technology

Ding Yong, Jiang Huanchun, Li Xianglong   

  • Online:2016-01-25 Published:2016-01-25

摘要: 随着国内大型火电厂越来越重视“节能减排”工作,各厂不仅对锅炉吹灰优化运行优化的认识与重视程度不断提高,还开发出了部分应用于生产现场的吹灰优化系统,但由于锅炉实际运行情况的复杂多变、运行参数多具有相互耦合特性使其真正的实际应用效果比较有限,因此此类系统并未被大规模广泛地使用。文章研究的阚山发电厂通过和上海明华公司共同开发基于数据特征量挖掘技术的燃煤锅炉受热面实时灰污监测与吹灰优化系统,研究了计算基础数据的预处理方法、燃煤特性对锅炉受热面灰污程度的影响因子、运行参数变化特征量的软测量方法、最终开发了以最小运行成本为目标的吹灰优化系统,该系统目前运行稳定,取得了不错的指导效果。

关键词: 数据特征量, 软测量方法, 锅炉受热面, 清洁系数, 吹灰优化

Abstract: With the development of large-scale thermal power plants, the understanding and emphasis of the optimization operation of boiler soot blowing is increasing, but the actual application effect is limited due to the complicated and changeable operation parameters, so the system has not been widely used. Kanshan power plant and Shanghai Minghua Company jointly developed a coal-fired boiler heating surface of real-time fouling monitoring and soot blowing optimization system based on data features mining technology. The system is currently running steadily in the plant and it has achieved a good guiding effect.