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

Hindawi Complexity Volume 2019, Article ID 9361723, 12 pages https://doi.org/10.1155/2019/9361723 Research Article Performance Analysis of Reheat Steam Temperature Control System of Thermal Power Unit Based on Constrained Predictive Control Xiaoli Li ,1,2,3 Jian Liu ,1 Kang Wang ,1 Fuqiang Wang,4 and Yang Li5 1 Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China Beijing Key Laboratory of Computational Intelligence and Intelligent System, Engineering Research Center of Digital Community, Ministry of Education, Beijing 100124, China 3 Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing 100124, China 4 Technology Research Center, Shenhua Guohua Electric Power Research Institute Corporation, Beijing 100025, China 5 School of International Studies, Communication University of China, Beijing 100024, China 2 Correspondence should be addressed to Xiaoli Li; Received 17 April 2019; Revised 28 June 2019; Accepted 8 July 2019; Published 5 August 2019 Guest Editor: Xiaoqing Bai Copyright © 2019 Xiaoli Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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. 1. Introduction In recent years, China’s electric power industry has developed rapidly. Ultra-supercritical thermal power unit, which has the characteristics of nonlinear, uncertain parameters and time-variation, has become the main unit in coal-fired power generation industry. Thus higher requirements for automatic control of coal-fired power plants are put forward. At the same time, China’s clean energy industry has made great progress, and a variety of clean energy sources have entered the electricity market, which has a certain impact on the traditional coal-fired plants. In order to improve the market competitiveness of coal-fired plants, it is necessary to improve the efficiency of unit continuously. Increasing the pressure and temperature of steam is an effective means to improve competitiveness, but, due to the design requirement of the unit’s infrastructure design and the limitation of metal material of boiler, the upgrading and transformation of operating parameters of unit require a large amount of investment of funds. Therefore, it is very important to improve the control effect of steam temperature on the existing basis. In thermal power unit, reheat steam temperature is an important parameter that affects the economic value of unit. The reheat steam temperature control system is a complex object with the characteristics of large inertia and hysteresis, and the dynamic characteristics of the system are different during the load variation of generator unit, which make the control of reheat steam temperature extremely difficult. If the reheat steam temperature is too high, it may increase the corrosion of the metal material of pipeline and the heating surface of the boiler through which the steam flows, so 2 that the service life of unit may be reduced. If the steam temperature is too low, the humidity of steam will be very high, which not only makes the last turbine blades more vulnerable to damage, but also reduces the thermal efficiency of unit. The large variation of reheat steam temperature will also cause unit fatigue and reduce the service life of unit. Therefore, understanding the regulating law of the control quantities and the constraint range of the control quantities of the reheat steam temperature control system can not only ensure the safety of thermal equipment, but also have important significance to the stability of reheat steam temperature. In order to improve the control effect of steam temperature, a large number of scholars have adopted a variety of advanced control strategies to study it. A new cascade feedback control system with load feed-forward of reheat steam temperature is proposed in [1]. Single-Neuron Selfadaptive PSD algorithm controller applied to outer loop and double-degree PID controller is applied to inner loop, which achieves good control effect. In [2], based on the characteristics of superheated steam temperature of a boiler, a new cascade control system is designed. The main regulator adopts multimodel observer control, and the secondary controller adopts weighted synthesizing proportional control. The system integrates the characteristics of the multimodel control with those of the state variable control with observer. The results show that the control system has strong robustness. In [3], an adaptive predictive control algorithm is designed for the reference model, and two compensators are introduced; one is two-order compensator for process; the other one is time delay compensator for the reference model. The algorithm has been applied in a 200MW peak regulating drum boiler for reheating temperature process, and high control accuracy is obtained. As the superheated steam temperature has large inertia, time-delay, and nonlinearity and its dynamic characteristics change with the operating conditions, a self-tuning PID controller based on fuzzy-RBF neural networks is presented for its control in [4], which has the advantages of traditional PID control, neutral networks control, and fuzzy control and optimizes online PID parameters. In [5], a new intelligent control algorithm of cloud models is proposed. The variant dimension cloud model intelligent controller, which contains a one-dimension cloud model controller to eliminate steadystate error, is designed, and it is used for superheated steam temperature control of a supercritical once-through 600MW boiler. In [6], a multimodel internal mode control strategy is proposed, and it has been successfully applied to a 1024 t (...truncated)