Multivariable constrained predictive control of main steam temperature in ultra-supercritical coal-fired power unit

2015 ◽  
Vol 88 (2) ◽  
pp. 181-187 ◽  
Author(s):  
Guo-Liang Wang ◽  
Wei-Wu Yan ◽  
Shi-He Chen ◽  
Xi Zhang ◽  
Hui-He Shao
Keyword(s):  
Power Unit ◽  
Predictive Control ◽  
Steam Temperature ◽  
Main Steam

Multivariable Predictive Control of the Main Steam Temperature in Power Plant

2013 ◽  
Vol 11 (4) ◽  
Author(s):  
Wang Ting ◽  
Feng Xiaolu ◽  
Chen Jiangtao ◽  
Zhang Rong ◽  
Xu Wei
Keyword(s):  
Power Plant ◽  
Predictive Control ◽  
Steam Temperature ◽  
Main Steam

scholarly journals Performance Analysis of Reheat Steam Temperature Control System of Thermal Power Unit Based on Constrained Predictive Control

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoli Li ◽  
Jian Liu ◽  
Kang Wang ◽  
Fuqiang Wang ◽  
Yang Li
Keyword(s):  
Control System ◽  
Steady State ◽  
Power Unit ◽  
Predictive Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Thermal Power ◽  
Temperature Control System ◽  
Steam Temperature ◽  
Reheat Steam

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.

A Study of Fixed Steam Pressure Control of Ultra-Supercritical Unit

2013 ◽  
Vol 291-294 ◽  
pp. 2178-2181
Author(s):  
Shi He Chen ◽  
Xi Zhang ◽  
Guo Liang Wang ◽  
Wei Wu Yan ◽  
Heng Feng Tian ◽  
...  
Keyword(s):  
Predictive Control ◽  
Tracking Control ◽  
Pressure Control ◽  
Steam Pressure ◽  
Steam Temperature ◽  
Load Demand ◽  
Valve Opening ◽  
Simulation Results ◽  
Coal Flow ◽  
Main Steam

Ultra-supercritical (USC) unit is more and more popular these years for its advantages. In this paper, a model predictive control (MPC) method is introduced for coordinated control of USC unit running in fixed pressure mode. Three inputs (i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs (i.e. load, main steam temperature and main steam pressure). Piecewise models of the USC unit are obtained using the three inputs and the three outputs. In simulation, the output power follows load demand quickly and main steam temperature can be controlled around the setpoint closely in load tracking control. The simulation results show the effeteness of the proposed methods.

scholarly journals An Efficient Robust Predictive Control of Main Steam Temperature of Coal-Fired Power Plant

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3775
Author(s):  
Di Wang ◽  
Xiao Wu ◽  
Jiong Shen
Keyword(s):  
Power Plant ◽  
Predictive Control ◽  
Operating Conditions ◽  
Steam Temperature ◽  
Robust Model Predictive Control ◽  
Online Computation ◽  
Computation Efficiency ◽  
Robust Model ◽  
Main Steam ◽  
Two Stages

Regulating performance of the main steam temperature (MST) system concerns the economy and safety of the coal-fired power plant (CFPP). This paper develops an offset-free offline robust model predictive control (RMPC) strategy for the MST system of CFPP. Zonotope-type uncertain model is utilized as the prediction model in the proposed RMPC design owing to its features of higher accuracy, compactness of representation and less complexity. An offline RMPC aiming at the system robustness and computational efficiency is then developed to maintain the desired steam temperature in case of wide operating condition change. The proposed RMPC is realized by two stages: in the first stage, the RMPC law set, which is the piecewise affine (PWA) of the MST system state is designed offline; then in the second stage, the explicit control law is selected online according to the current state. To achieve an offset-free tracking performance, a manipulated variable target observer is employed to update the chosen RMPC law. The control simulations using on-site operating data of a 1000 MW ultra-supercritical power plant show that the proposed approach can achieve satisfactory control performance and online computation efficiency even under complicated operating conditions.

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