scholarly journals Research of IGPC Control Strategy Based-on Hybrid Optimization for Power Station Boiler Superheated Steam Temperature

2014 ◽  
Vol 6 (2) ◽  
pp. 36-43
Author(s):  
Benxian Xiao ◽  
Rongbao Chen ◽  
Jun Xiao
Keyword(s):  
Control Strategy ◽  
Superheated Steam ◽  
Hybrid Optimization ◽  
Steam Temperature ◽  
Power Station ◽  
Superheated Steam Temperature ◽  
Power Station Boiler

scholarly journals Multi-Objective Intelligent Optimization of Superheated Steam Temperature Control Based on Cascaded Disturbance Observer

2020 ◽  
Vol 12 (19) ◽  
pp. 8235
Author(s):  
Yong-Sheng Hao ◽  
Zhuo Chen ◽  
Li Sun ◽  
Junyu Liang ◽  
Hongxia Zhu
Keyword(s):  
Control Strategy ◽  
Disturbance Observer ◽  
Power Plants ◽  
Superheated Steam ◽  
Critical Parameters ◽  
Pi Control ◽  
Control Performance ◽  
Steam Temperature ◽  
Multi Objective ◽  
Superheated Steam Temperature

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.

scholarly journals Superheated Steam Temperature Control Based on a Hybrid Active Disturbance Rejection Control

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1757 ◽  
Author(s):  
Gengjin Shi ◽  
Zhenlong Wu ◽  
Jian Guo ◽  
Donghai Li ◽  
Yanjun Ding
Keyword(s):  
Control Strategy ◽  
Disturbance Rejection ◽  
Superheated Steam ◽  
Active Disturbance Rejection Control ◽  
Control Performance ◽  
Steam Temperature ◽  
Loop Control ◽  
Superheated Steam Temperature ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

Superheated steam temperature (SST) is a significant index for a coal-fired power plant. Its control is becoming more and more challenging for the reason that the control requirements are stricter and the load command changes extensively and frequently. To deal with the aforementioned challenges, previously the cascade control strategy was usually applied to the control of SST. However, its structure and tuning procedure are complex. To solve this problem, this paper proposes a single-loop control strategy for SST based on a hybrid active disturbance rejection control (ADRC). The stability and ability to reject the secondary disturbance are analyzed theoretically in order to perfect the theory of the hybrid ADRC. Then a tuning procedure is summarized for the hybrid ADRC by analyzing the influences of all parameters on control performance. Using the proposed tuning method, a simulation is carried out illustrating that the hybrid ADRC is able to improve the dynamic performance of SST with good robustness. Eventually, the hybrid ADRC is applied to the SST system of a power plant simulator. Experimental results indicate that the single-loop control strategy based on the hybrid ADRC has better control performance and simpler structure than cascade control strategies. The successful application of the proposed hybrid ADRC shows its promising prospect of field tests in future power industry with the increasing demand on integrating more renewables into the grid.

scholarly journals Superheated steam temperature system of thermal power control engineering based on neural network local multi-model prediction

2021 ◽  
Vol 25 (4 Part B) ◽  
pp. 2949-2956
Author(s):  
Jinsong Zhan ◽  
Jing Du ◽  
Shaofeng Dong ◽  
Wei Hu
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Superheated Steam ◽  
Thermal Power ◽  
Time Lag ◽  
Operating Conditions ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Smooth Switching ◽  
Switching Method

The superheated steam temperature object of thermal power plant has the characteristics of time lag, inertia and time-varying parameters. The control quality of the conventional proportional integral derivate controller with fixed parameters will decrease after the object characteristics change. The generalized predictive control strategy of superheated steam temperature based on neural network local multi-model switching can achieve the goal of designing sub-controllers for fixed models under several typical operating conditions. When the system operating conditions change, the effective switching strategy is timely and accurate. Switch to the most suitable controller. The paper proposes a new smooth switching method, which can effectively suppress the large disturbance phenomenon of the object when switching. The simulation results verify the effectiveness of the control strategy.

Multiple Model Based Robust PID Control for Superheated Steam Temperature System

2014 ◽  
Vol 494-495 ◽  
pp. 1266-1269
Author(s):  
Li Hua Liu ◽  
Xiu Kun Wei
Keyword(s):  
Control Strategy ◽  
Pid Control ◽  
Superheated Steam ◽  
Operating Conditions ◽  
Pid Controllers ◽  
Multiple Model ◽  
Steam Temperature ◽  
Switching Strategy ◽  
Superheated Steam Temperature ◽  
The Given

Temperature of superheated steam in power generation units is essentially important for the safe and economic running of boilers and turbines. In this paper, a robust PID control strategy based on multiple models is proposed. Robust PID controllers associated with each model are designed with parameters tuned based on the H performance. For different operating conditions, the appropriate controller is selected by the given switching strategy. Simulations are done to prove the effectiveness of the control strategy.

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