摘要
建立精确的热工对象动态模型是提升系统控制性能的重要基础。针对某1000MW超超临界火电机组减温喷水量扰动下主汽温对象的动态特性,利用现场运行数据和混合粒子群优化算法对主汽温系统进行辨识,建立了过热器喷水量扰动下主汽温的动态数学模型。对所建立的模型进行验证,结果表明模型能够有效地反映主汽温系统的实际运行状况。
Accurate dynamic model of thermal objects is an important foundation for improving the controlling per- formance of system. According to the main steam temperature dynamics under the disturbances of spray water in a 1000MW Ultra Supereritical （USC） boiler,we used online data and hybrid particle swarm optimization algorithm to i- dentify the main steam temperature system, and established the dynamic mathematical models of the main steam tem- perature under the disturbances of spray water. Simulations show that the models can reflect the facts of main steam temperature.
出处
《计算机仿真》
CSCD
北大核心
2014年第12期133-136,共4页
Computer Simulation
基金
中央高校基本科研业务费专项资金资助项目(13ZD13)
关键词
主汽温
喷水流量
粒子群优化
现场数据
动态模型
Main steam temperature
Spray water flow
Particle swarm optimization （PSO）
Online data
Dynamic model
