循环流化床锅炉床温与主蒸汽压力的智能辨识  

Intelligent Identification on Bed Temperature and Main Steam Pressure of CFB Boiler based on Salp Swarm Algorithm

作　　者：赵威 钱进[1] 王一桂 黄凤启 ZHAO Wei;QIAN Jin;WANG Yi-gui;无(Guizhou University;Power China Guizhou Engineering Co.,Ltd.;Guotou Panjiang Power Generation Co.,Ltd.)

机构地区：[1]贵州大学,贵州贵阳550025 [2]中国电建集团贵州工程有限公司 [3]国投盘江发电有限公司

出　　处：《电站系统工程》2022年第3期15-17,共3页Power System Engineering

基　　金：贵州省科技支撑计划项目([2020]2Y040)资助。

摘　　要：以循环流化床锅炉的运行数据为基础,建立在50%负荷运行工况下,以给煤量、煤泥量和一次风量为输入,以床温和主蒸汽压力为输出的系统模型。采用樽海鞘群算法(SSA)对模型的参数进行寻优,该算法采用一种新的群体更新模型,控制参数很少。仿真结果表明,相比于传统粒子群算法(PSO),樽海鞘群算法运算速度明显提高,可以得到更优的模型。The field operating data of a 300 MW CFB large proportion coal slime co-firing power plant was used for the identification of model parameter.In order to reflect the relationship of energy balance,the coal-feed quantity,slime quantity and primary air volume were selected as input variables,and the bed temperature and the main steam pressure were selected as the outputs.Intelligent identification of the salp swarm algorithm(SSA)was used to obtain the optimal model parameters to multi-variable system of bed temperature.Finally,compared with the standard particle swarm optimization algorithm(PSO),the effectiveness of built model is obtained.

关 键 词：循环流化床锅炉 床温 主蒸汽压力 樽海鞘群算法 参数辨识 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]