scholarly journals Undisturbed Switching Control Method of Superheated Steam Temperature Systems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Lei Yu
Keyword(s):  
Control System ◽  
Power Plants ◽  
Superheated Steam ◽  
Control Method ◽  
Thermal Power ◽  
Switching Control ◽  
System Control ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Predictive Controller

In this paper, a new type of superheated steam temperature switching control system for thermal power plants is presented. A single neuron adaptive PSD (Proportional Sum Differential) predictive controller is designed. The DCS (Distributed Control System) control system platform is used for configuration design. At the same time, the feedforward compensation technology and anti-integration saturation technology are employed to improve the characteristics of large hysteresis and multi-interference in the superheated steam temperature system. Undisturbed switching performance can be well obtained between the new controller and its own PID controller. This proposed method has been well applied in a thermal power plant (600MW) and achieved better control quality.

scholarly journals SUPERHEATED STEAM TEMPERATURE CONTROL FOR BOILER USING ADAPTIVE DYNAMIC FEEDFORWARD COMPENSATORS

2018 ◽  
Vol 56 (3) ◽  
pp. 347
Author(s):  
Nguyen Trong Ha ◽  
Nguyen Le Hoa ◽  
Doan Quang Vinh
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Power Plants ◽  
Superheated Steam ◽  
Thermal Power ◽  
Steam Temperature ◽  
Boiler Load ◽  
Adaptive Dynamic ◽  
Superheated Steam Temperature ◽  
Feedforward Compensators

This paper proposes a new control strategy for improving the performance of the superheated steam temperature control system in thermal power plants. Based on the analysis of the limitations of the static feedforward compensators (SFC) for temperature and boiler load disturbances in the existing control system of the auxiliary boiler in Dung Quat refinery, two adaptive dynamic feedforward compensators (ADFC) for temperature and boiler load disturbances were proposed to replace the SFCs.  In addition, a method for predicting the tube wall temperature of the superheater using an autoregressive moving average (ARMA) model was also proposed. The simulation results for the two typical cases of the boiler load change indicate that the control system incorporated with the proposed ADFCs improves significantly the performance of the control system

Adaptive PID Cascade Control for Superheated Steam Temperature Based on Inverse Model

2011 ◽  
Vol 133 (11) ◽  
Author(s):  
Zhijie Wang ◽  
Guangjun Wang ◽  
Hong Chen
Keyword(s):  
Control System ◽  
Power Plant ◽  
Superheated Steam ◽  
Thermal Power ◽  
Control Process ◽  
Inverse Model ◽  
Cascade Control ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Cascade Control System

Since the superheated steam temperature system of boiler in thermal power plant is characterized as time varying and nonlinear, it is hard to achieve a satisfactory performance by the conventional proportional-integral-derivative (PID) cascade control scheme. This paper presents a design method of adaptive PID cascade control system for superheated steam temperature based on inverse model: First, the inner loop and the outer process in the cascade control system are equivalent to a generalized plant. A simplified Takagi–Sugeno (STS) fuzzy model is adopted to identify the inverse model of the generalized plant. By choosing the appropriate structure and optimizing with constrains for the parameters of the inverse model, the organic combination of the PID primary controller with the inverse model is realized. To maintain the structure of the existing conventional PID cascade control system in power plant without change, in the control process, the parameters of the primary controller are adjusted on-line according to the identification result of the inverse model of the generalized plant; thus an adaptive PID cascade control system is formed, which matches with the characteristics of the controlled plant. Through the simulation experiments of controlling superheated steam temperature, it is illustrated that the proposed scheme has good adaptability and anti-interference ability.

Superheated Steam Temperature Control Based on Improved Recurrent Neural Network and Simplified PSO Algorithm

2011 ◽  
Vol 128-129 ◽  
pp. 1065-1069 ◽  
Author(s):  
Liang Yu Ma ◽  
Yin Ping Ge ◽  
Xing Cao
Keyword(s):  
Neural Network ◽  
Temperature Control ◽  
Recurrent Neural Network ◽  
Power Plants ◽  
Superheated Steam ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Control Scheme ◽  
Wide Range ◽  
Optimization Control

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.

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