摘要
大型火力发电厂的实时控制过程中,许多数据之间呈现复杂的非线性关系,而数据挖掘技术能从数据中发现知识或规则,及时分析、调整参数。该文利用数据挖掘方法确定监控参数的目标值,为火电机组耗差分析提供重要依据。介绍了数据挖掘方法的相关理论,研究并应用组织进化算法确定锅炉监控参数的目标值模型。通过分析实时运行数据,挖掘出锅炉运行主要监控参数的目标值,为目标值模型的确定提供了一个新的思路和有效方法。
Complicated nonlinear relationships exist among many data in the real-time control-process of large power plant. And data-mining technology could find knowledge, analyze parameters and regulate them. It ascertained target-value by means of data-mining, which supported energy-loss analysis. It introduced relative theory on data mining, studied and applied target-value model of thermal supervised parameters in the way of Organizational Evolutionary Algorithm. By analyzing real-time operating data of thermal units, and mined the target-value models for main supervised parameters of boiler. The results supply a new idea and effective method for target-value models.
出处
《电站系统工程》
北大核心
2009年第1期8-10,共3页
Power System Engineering
基金
河北省教育厅指导性项目(Z2007414)
关键词
组织进化
目标值
数据挖掘
运行优化
锅炉
organizational evolutionary
target-value
data mining
operation optimization
boiler
