Deep-learning modeling and control optimization framework for intelligent thermal power plants: A practice on superheated steam temperature

2021 ◽  
Author(s):  
Qianchao Wang ◽  
Lei Pan ◽  
Kwang Y. Lee ◽  
Zizhan Wu
Keyword(s):  
Power Plants ◽  
Superheated Steam ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Steam Temperature ◽  
Modeling And Control ◽  
Optimization Framework ◽  
Control Optimization ◽  
Superheated Steam Temperature ◽  
And Control

A Research on Superheated Steam Temperature Control Optimization of the Thermal Power Plant on the Basis of Steam Temperature Characteristics

2012 ◽  
Vol 516-517 ◽  
pp. 232-238 ◽  
Author(s):  
Jia Fei Yao ◽  
Li Yang Wang
Keyword(s):  
Power Plant ◽  
Temperature Control ◽  
Thermal Power Plant ◽  
Superheated Steam ◽  
Thermal Power ◽  
Steam Temperature ◽  
Simulation Tools ◽  
Control Optimization ◽  
Superheated Steam Temperature ◽  
Steam System

Take the superheated steam system of a 330MW unit as the object, by means of the collection and research on the data of the overheating system of thermal power units and simulation tools in matlab, the results were analyzed, and then presents a construction method of the dynamic compensating function which take the load as the variable, at last, simulate and verify the constructor function.

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

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 Modeling and Control Optimization of Denitrifaction System of 600MW Thermal Power Unit

2018 ◽  
Vol 452 ◽  
pp. 032021
Author(s):  
Jingqiu Kang ◽  
Weihua Li ◽  
Zhenyong Yang ◽  
Aiguo Gao ◽  
Lei Liu ◽  
...  
Keyword(s):  
Power Unit ◽  
Thermal Power ◽  
Modeling And Control ◽  
Control Optimization ◽  
And Control

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.

scholarly journals Simulation and Control of Solar Thermal Power Plants

2010 ◽  
Vol 1 (08) ◽  
pp. 232-236 ◽  
Author(s):  
J. Gall ◽  
D. Abel ◽  
N. Ahlbrink ◽  
R. Pitz-Paal ◽  
J. Andersson ◽  
...  
Keyword(s):  
Power Plants ◽  
Thermal Power ◽  
Solar Thermal ◽  
Thermal Power Plants ◽  
Solar Thermal Power ◽  
Simulation And Control ◽  
And Control

scholarly journals State variable-fuzzy prediction control strategy for superheated steam temperature of thermal power units

2021 ◽  
Vol 25 (6 Part A) ◽  
pp. 4083-4090
Author(s):  
Xuan Tu ◽  
Jiakui Shi ◽  
Kun Yao ◽  
Jie Wan ◽  
Fei Qiao
Keyword(s):  
State Feedback ◽  
Superheated Steam ◽  
Thermal Power ◽  
The State ◽  
Feedback Controller ◽  
Steam Temperature ◽  
State Feedback Controller ◽  
State Variable ◽  
Superheated Steam Temperature ◽  
Fuzzy State

With the large-scale grid connection of new energy power, the random fluctuation existing in the power system is intensified, which leads to frequent fluctuation of load instructions of thermal power units. It is of great significance to improve the variable load performance of the coal-fired units. It is more difficult to control the superheated steam temperature (SST). In order to improve the control performance of SST, a state variable fuzzy predictive control method is proposed in this paper. Firstly, Takagi-Sugeno fuzzy state observer is used to approximate the non-linear plant of the SST. At the same time, based on the state observer, a fuzzy state feedback controller is designed to improve its dynamic characteristics. Thirdly, based on the extended predictive model of the state feedback controller, a model predictive controller is designed to realize the SST tracking control. Dynamic simulation shows the effectiveness of the strategy.

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