Dynamic modeling and model predictive control for printed-circuit heat exchanger in supercritical CO2 power cycle

被引:0
|
作者
Zhang, Fan [1 ]
Hu, Hemin [1 ]
Wang, Tao [1 ]
Zhang, Bing [1 ]
机构
[1] Beijing Univ Chem Technol, Coll Mech & Elect Engn, Beijing 100029, Peoples R China
关键词
Supercritical carbon dioxide power cycle; Printed-circuit heat exchanger; Dynamic modeling; Machine learning; Model predictive control; WASTE HEAT; DESIGN; RECUPERATORS; OPTIMIZATION;
D O I
10.1016/j.jclepro.2024.143495
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The supercritical carbon dioxide (sCO(2)) Brayton cycle, known for its superior thermal efficiency and compact turbomachinery size, can utilize various heat sources. The printed-circuit heat exchangers (PCHE) used in the power cycle, particularly the recuperators and cooler, significantly influence the thermal efficiency of the cycle. However, they exhibit intricate characteristics attributed to large thermal inertia and nonlinear heat transfer. This paper explores the one-dimensional dynamic modeling and control issues for PCHE. The established dynamic PCHE models are verified through different scenarios. Then, a novel control strategy is proposed for fast temperature reference tracking and disturbance rejection. The composite controller includes three parts: the main control is based on the principle of model predictive control (MPC); Gaussian process (GP) regression modeling is incorporated as the feedforward; and the disturbance observer (DOB) is introduced for unexpected disturbance estimation and compensation. Compared with traditional controllers, simulations demonstrate that for reference tracking the settling time of the proposed method can be saved by more than 50%, and for disturbance rejection the recovery time can be reduced by more than 30%. The results indicate the presented strategy can ensure the safe and effective operation of the sCO(2) power cycle.
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页数:11
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