基于子空间方法的超超临界机组
过热蒸汽系统模型辨识

上海交通大学学报（自然版） ›› 2017, Vol. 51 ›› Issue (6): 672-678.

基于子空间方法的超超临界机组
过热蒸汽系统模型辨识

孟庆阳1,阎威武1,胡勇1，程建林1，陈世和2,张曦2

1. 上海交通大学自动化系，上海 200240； 2. 广东电网电力科学研究院，广州 510080

出版日期:2017-06-30 发布日期:2017-06-30
基金资助:

Model Identification Based on Subspace Model Identification of
Superheated Steam System in UltraSupercritical CoalFired Power Unit

MENG Qingyang1,YAN Weiwu1,HU Yong1,CHENG Jianlin1,CHEN Shihe2,ZHANG Xi2

1. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China;
2. Guangdong Electric Power Research Institute, Guangzhou 510080, China

Online:2017-06-30 Published:2017-06-30
Supported by:

摘要/Abstract

摘要： 针对超超临界机组过热蒸汽系统模型辨识，采用基于数据驱动的闭环子空间辨识方法直接得到系统的阶跃响应系数，结合传统的SISO(Single Input Single Output)辨识方法，并利用最小二乘算法回归出系统的低阶传递函数模型.通过对某电厂超超临界机组过热蒸汽系统进行闭环辨识，结果表明，该策略很好地融合了子空间方法的简便性以及传统SISO辨识方法的最优性，并成功用于超超临界机组过热蒸汽系统模型辨识.

关键词: , 超超临界机组, 过热蒸汽系统, 子空间辨识, 闭环辨识方法

Abstract: The superheated steam system ultrasupercritical unit is a multiinput and multioutput system. In this paper, a datadriven subspace approach is introduced for the model identification of the superheated steam system. In the approach, the unit step response coefficients are drawn directly, then the loworder transfer function of the system is obtained by leastsquare regression. Finally, closed loop identification based on datadriven subspace approach is applied to the superheated steam system of ultrasupercritical coalfired power unit. Real application shows that proposed identification strategy has a small computational cost and can meet the accuracy requirements in industrial sites.

Key words: , ultrasupercritical unit； superheated steam system； datadriven subspace approach； closed loop identification

中图分类号:

TP 271

孟庆阳1,阎威武1,胡勇1，程建林1，陈世和2,张曦2. 基于子空间方法的超超临界机组
过热蒸汽系统模型辨识[J]. 上海交通大学学报（自然版）, 2017, 51(6): 672-678.

MENG Qingyang1,YAN Weiwu1,HU Yong1,CHENG Jianlin1,CHEN Shihe2,ZHANG Xi2. Model Identification Based on Subspace Model Identification of
Superheated Steam System in UltraSupercritical CoalFired Power Unit[J]. Journal of Shanghai Jiaotong University, 2017, 51(6): 672-678.

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