摘要
以某电厂锅炉壁温优化运行为例,根据数据聚类特征对参数进行分组,结合Apriori算法,找出与热偏差关联的控制参数项,发掘出敏感参数项。数据挖掘结果与优化调整结果相符,通过规则约束使壁温优化效果提升17%,可为同类电厂运行调整提供借鉴。
Taking the wall temperature optimization of a power plant boiler as an example, the combined method of feature grouping and Apriori algorithm was used to find out the control parameters associated with the thermal deviation among pipe panels and to excavate the items of sensitive parameters. The results of excavation were in good agreement with actual measurements, and the optimization effectiveness on the wall temperature could be improved by 17% based on the association rules. This may serve as a reference for operation adjustment of similar power plants.
作者
张磊
丁士发
杨凯镟
Zhang Lei;Ding Shifa;Yang Kaixuan(Shanghai Power Equipment Research Institute Co.,Ltd.,Shanghai 200240,China)
出处
《发电设备》
2019年第2期122-126,共5页
Power Equipment
关键词
电厂
优化运行
屏间热偏差
特征分组
关联规则算法
power plant
optimized operation
thermal deviation among pipe panels
feature grouping
algorithm based on association rules
