中国电机工程学报2024，Vol.44Issue(22)：8957-8967,中插22,12.DOI:10.13334/j.0258-8013.pcsee.232072
基于扩张状态观测器的过热汽温系统建模与参数智能辨识
Modeling and Intelligent Parameter Identification for Superheated Steam Temperature System Based on Extended State Observer
摘要
Abstract
The high penetration of renewable energy presents a serious challenge for the matching between electricity supply and demand in the power grid.Simultaneously,coal-fired units need to undertake extensive tasks related to peak and frequency regulation,which poses a certain threat to the safe and stable operation of the superheated steam temperature system.Therefore,it is necessary to establish a thermal process control-oriented mathematical model for superheated steam temperature.Considering that the total disturbance signal of time-delayed extended state observer(TD-ESO)contains sufficient model information,a method for intelligent parameter optimization and information extraction based on ESO compensation model is proposed,which aims to minimize the amount of unknown information in total disturbance,and uses an improved sand cat swarm optimization algorithm to optimize the model parameters and extract known model information from the total disturbance for compensation to the input of ESO.Simulation results from tests on linear and nonlinear systems indicate that the proposed identification method demonstrates good applicability and high accuracy for both systems with and without input time-delay.In terms of practical application,model identification and validation are carried out by employing operational data from superheated steam temperature system of ultra-supercritical double reheat unit,which also indicates the reasonableness and accuracy of the proposed method.Furthermore,the identified model can provide valuable reference for control strategy design and performance optimization of the superheated steam temperature system.关键词
迟延型扩张状态观测器/数据驱动模型辨识/沙丘猫群优化算法/过热汽温系统Key words
time-delayed extended state observer/data-driven model identification/sand cat swarm optimization algorithm/superheated steam temperature system分类
信息技术与安全科学引用本文复制引用
孙明,王胤开,白阳振,范延增,董泽..基于扩张状态观测器的过热汽温系统建模与参数智能辨识[J].中国电机工程学报,2024,44(22):8957-8967,中插22,12.基金项目
河北省自然科学基金项目(E2018502111) （E2018502111）
河北省省级科技计划项目(22567643H). Natural Science Foundation of Hebei Province(E2018502111) （22567643H）
S&T Program of Hebei Province(22567643H). （22567643H）
