基于数据挖掘的火电机组主要参数基准值获取方法  

Data mining based determination method of main parameter benchmark values for power plants

作　　者：梁俊宇[1,2,3] 赵明 李鹏飞[2,3,5] 王洋[5] 丁常富[5] 

机构地区：[1]华北电力大学动力工程及工程热物理博士后科研流动站,北京102206 [2]华北电力大学 [3]云南电网公司工作站,云南昆明650217 [4]云南电力试验研究院(集团)有限公司电力研究院,云南昆明650217 [5]华北电力大学能源动力与机械工程学院,河北保定071003

出　　处：《热力发电》2015年第1期73-76,81,共5页Thermal Power Generation

摘　　要：采集火电机组重要参数的历史运行数据,基于数据挖掘的方法对参数进行数据清理和数据规约,根据关联规则挖掘历史运行参数的基准值并给定相应的偏差范围。以某300MW机组为例,结合系统中的多重数据验证模块,对获取的基准值和偏差范围进行了试验验证。结果表明,采用数据挖掘手段获取的基准值和偏差带的准确性较高,保障了煤耗在线监测系统的准确性与可靠性,有利于电力调度的合理实施。The historical operation data of important parameters in a thermal power unit were collected and data mining methods were used to carry out data cleaning and data reduction.Then the reference values of operation parameters were obtained based on association rule,and the deviation ranges were given.Combined with multiple data validation module,the reference values and deviation ranges were verified.The results show that the accuracy of the reference values and deviation ranges obtained by data mining is high enough to meet the requirements of engineering calculations,thus to ensure the accuracy and reliability of the coal-line monitoring system,which is conducive to a fair and impartial implementation of energy-saving generation dispatching.

关 键 词：火电机组 主要运行参数 基准值 数据挖掘 煤耗在线监测 电力调度 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]