Autotuning PID Controller for Superheated Steam Temperature in Power Plants

1995 ◽  
Vol 28 (26) ◽  
pp. 7-12
Author(s):  
Guadalupe Madrigal-Espinosa ◽  
J. Alfredo de la Gana-Barrientos
2011 ◽  
Vol 128-129 ◽  
pp. 1065-1069 ◽  
Author(s):  
Liang Yu Ma ◽  
Yin Ping Ge ◽  
Xing Cao

Coal-fired power plants are facing a rapid developing tide toward supercritical and ultra-supercritical boiler units with higher parameters and bigger capacity. Due to the large inertia, large time delay and nonlinear characteristics of a boiler’s superheater system, the widely-used conventional cascade PID control scheme is often difficult to obtain satisfactory steam temperature control effect under wide-range operating condition. In this paper, a predictive optimization control method based on improved mixed-structure recurrent neural network model and a simpler Particle Swarm Optimization (sPSO) algorithm is presented for superheated steam temperature control. Control simulation tests on the full-scope simulator of a 600 MW supercritical power unit showed that the proposed predictive optimization control scheme can greatly improve the superheated steam temperature control quality with good application prospect.


2020 ◽  
Vol 12 (19) ◽  
pp. 8235
Author(s):  
Yong-Sheng Hao ◽  
Zhuo Chen ◽  
Li Sun ◽  
Junyu Liang ◽  
Hongxia Zhu

Superheated steam temperature (SST) is one of the most critical parameters for the process safety, overall efficiency and pollution reduction of coal-fired power plants. However, SST control is challenging due to various disturbances and model uncertainties, especially in the face of the growing penetration of intermittent renewable energy into the power grid. To this end, a cascaded Disturbance Observer-PI (DOB-PI) control strategy is proposed to enhance control performance. The observer design and parameter tuning are carried out through mechanism analysis on the proposed structure. Furthermore, a robust loop shaping method is introduced as a hard constraint to balance the control performance and robustness. The controller parameters are optimized based on the multi-objective artificial bee colony optimization (MOABC) algorithm. Simulation results show that the proposed cascaded DOB-PI control strategy can significantly improve the disturbance rejection performance of both the inner- and outer-loops of the SST control system. This paper indicates promising prospects for the proposed method in future applications.


2012 ◽  
Vol 51 (6) ◽  
pp. 778-785 ◽  
Author(s):  
Jianhua Zhang ◽  
Fenfang Zhang ◽  
Mifeng Ren ◽  
Guolian Hou ◽  
Fang Fang

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