火电厂输煤系统节能优化控制方法研究  

Research on energy-saving optimal control methods for coal transmission systems in thermal power plants

作　　者：苗荣霞[1] 李洁馨 张洋 王幸 Miao Rongxia;Li Jiexin;Zhang Yang;Wang Xing(School of Electronic Information Engineering,Xi'an University of Technology,Xi'an 710000,China)

机构地区：[1]西安工业大学电子信息工程学院,西安710000

出　　处：《国外电子测量技术》2023年第5期50-55,共6页Foreign Electronic Measurement Technology

摘　　要：火电厂输煤系统的非线性、时变和大时滞性等复杂特征,使传统控制方法的控制效果不太理想,产生过量输煤和电力生产损耗问题。为了在降低能耗的同时优化系统性能,围绕煤流量、皮带运行速度和系统功率3个变量运用径向基函数(RBF)神经网络建立节能优化模型,并将已建立的节能优化模型用于搭建Smith预估模糊自适应PID控制器。通过MATLAB仿真得出,该方法实现了输煤系统控制参数自动在线调整,皮带输送机的速度能够按照燃煤需求进行较为精准地实时调节,使输煤系统的控制更加高效。The complex characteristics of coal transmission systems in thermal power plants,such as non-linearity,time variation and large time lags,make traditional control methods less effective and create problems of excessive coal transmission and power production losses.In order.to optimise the system performance while reducing energy consumption,an energy saving optimisation model is developed using RBF neural networks around three variables:Coal flow rate,belt running speed and system power,and the established energy saving optimisation model is used to build a Smith predictive fuzzy adaptive PID controller.The method has been simulated by MATLAB to achieve automatic online adjustment of the control parameters of the coal conveying system.The speed of the belt conveyor can be adjusted in real time according to the demand of coal combustion,making the control of the coal conveying system more efficient.

关 键 词：输煤系统 RBF神经网络 节能优化模型 Smith预估模糊自适应PID 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]