摘要
随着新能源电力规模的不断扩大及用电需求的持续变化,火电机组常运行于深度、快速变负荷的状态,对汽轮机阀门的流量特性要求也越来越高,而常用的通过现场流量特性试验进行线性化校正的方式存在精度低、无法直观监测校正结果等问题。为此,通过开发组态式数据处理分析算子、参数寻优算法及可视化技术对历史数据进行分析处理、对阀门流量特性进行线性化校正及监测。将该方法应用于某600 MW直流炉机组,结果表明汽机阀门的流量特性线性得到了极大改善,同时也实现了阀门流量特性的在线监测。
As the scale of new energy generation and the demand for electricity continue to change,thermal power units are often operated under deep and rapidly varying loads,which places increasingly high demands on the flow characteristics of turbine valves.In this paper,we develop a configurable data processing analysis algorithm,a parameter finding algorithm and a visualisation technique to analyse and process historical data,and to linearise and monitor the valve flow characteristics.The method was applied to a 600 MW DC furnace unit and the results showed that the linearity of the flow characteristics of the steam engine valves was greatly improved and online monitoring of the valve flow characteristics was also achieved.
作者
田彬
朱子凡
TIAN Bin;ZHU Zifan(CHN Energy ZhiShen Control Technology Co.,Ltd.,Beijing 102211,China;Beijing Engineering Research Center of Power Station Automation,Beijing 102211,China)
出处
《电工技术》
2022年第15期235-239,共5页
Electric Engineering
关键词
历史数据挖掘
流量特性曲线优化
可视化
组态式算子
historical data mining
optimisation of flow characteristic curves
visualisation
grouping arithmetic