Design of main steam temperature control system of sub-critical 600MW power unit and its application

Author(s):  
Feng Jian ◽  
Kao Zhi-qiang ◽  
Han Zhong-xu ◽  
Dang Zeng-kui ◽  
Liang Zhen-wu ◽  
...  
Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoli Li ◽  
Jian Liu ◽  
Kang Wang ◽  
Fuqiang Wang ◽  
Yang Li

The reheat steam temperature control system of thermal power unit is a complex control object with time-varying parameters and large delay. In order to achieve precise control of reheat steam temperature, the performance of the reheat temperature control system is analyzed according to the data that are obtained based on the constrained predictive control algorithm. Firstly, the process and mathematical model of reheat steam temperature control system are introduced. Then the principle of constrained predictive control algorithm is analyzed. Finally, the steady-state values of control quantities of reheat steam temperature control system under different conditions are given by MATLAB simulation, and, by analyzing the steady-state values and steady-state time of the input and output of the system, the reference values and the regulating law of the control quantities and the specific constraint range of the control quantities of the system are given, which can provide reference data and theoretical basis for the field adjustment of the reheat steam temperature control system in power plant and improve the safety and effectiveness of the system.


2018 ◽  
Vol 5 (1) ◽  
pp. 63
Author(s):  
Fengzhi Dai ◽  
Yujie Yan ◽  
Baochang Wei ◽  
Yuxing Ouyang ◽  
Lingran An

Author(s):  
Ruicai Si ◽  
Zhi Xia ◽  
Zhongyan Wang ◽  
Jia Li ◽  
Fuxin Ma ◽  
...  

2012 ◽  
Vol 591-593 ◽  
pp. 1204-1207
Author(s):  
Yan Min Nie ◽  
Tao Wang ◽  
Ying Bo An

The main steam temperature is always an important indicator of the boiler operation quality, high or low will affect the quality of boiler operation. At first, introduce a algorithm PSO, which can used to optimize the PID parameters of a main steam temperature control system. Then, improved the PSO, and studied a kind of improved particle swarm algorithm—quantum apply quantum-behaved particle swarm optimization (QPSO). And this algorithm is used to optimize the PID parameters of a main steam temperature control system, got the best parameters. In the end, simulation result shows that, compared with basic particle swarm optimization (PSO),QPSO can make main steam temperature control system has a better control of quality, and improves the system of static and dynamic characteristics.


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