Research On Optimization Operation Control Technology Of Combustion System

In order to optimize the control technology of the combustion system of Supercritical Units, we must understand the thermal characteristics, and then we build a mathematical model which is easy to control. The facilities of thermal power combustion system are numerous, and its internal structure is complex. Therefore, the combustion process is a multi-input and multi-output controlled object which is mutual influence of each parameter. This paper analyzes the thermal properties, working principle and control tasks of combustion systems of Supercritical Unit, and describes the operations specifications of 600 MW Supercritical Units in Guizhou. In recent years, with the continuous improvement of control theory and the continuous development of computing technology, system identification technology and system modeling approach has formed a mature theoretical system. However, the modeling and optimization of the combustion system of Supercritical Unit is not yet perfect, and more in-depth study is needed.With distributed control system(DCS) and real-time monitoring system(SIS) of thermal power plant units widely used in the power industry, we can use intelligent algorithms to identify the model based on field historical data in a run condition, and we can get the mathematical model which is relatively close to the actual. This paper presents the characteristics analysis of the chamber negative pressure system, the flue gas oxygen system and main steam pressure system of 600 MW Supercritical Unit, and this paper uses particle swarm algorithm to identify the model of the three subsystems based on field historical data. By comparing the identification results with the original data, we can verify the feasibility of the system model based on field performance data.In this paper, we know the process characteristics of combustion system are large inertia, strong coupling, time-varying, nonlinear, and so on. So we introduce fractional PI~λD~μ controller, which has better tracking ability, faster response rate, more strong anti-interference ability and better robustness than the PID controller. By comparing the effect curves of fractional order controller and integer order controller, it is fully validated that fractional PI~λD~μ controller has better control quality for complex dynamic process of combustion system. Research and application of fractional PI~λD~μ controller will provide a strong reference for the design and improvement of thermal power plant process control system.