Research On Modeling And Control Method Of Combustion System For 1000MW Thermal Power Unit

With the rapid development of society,the issue of energy and environment have become increasingly severe in recent years,moreover,the ultra super-critical thermal power generating units got preference because of its high efficiency and energy saving,low-pollutant emissions advantages,which become development trend in the future.As an important system of thermal power units,combustion system has the characteristics of large delay,large inertia,strong coupling nonlinearity and so on.In order to improve the level of control in large thermal power plant,the primary task was understanding the characteristics of combustion system of ultra super-critical unit boiler,then designing appropriate control strategy for it.In this paper,a power plant in Taizhou,Jiangsu 1000 MW ultra-supercritical thermal power unit's combustion system was taken as the research object,we conducted its model and carried on research and analysis of its control strategy,focusing on the following work in this paper:(1)Excavating the operating data of the combustion system of this ultra-supercritical thermal power plant,summarizing the historical data selection experience and data pre-processing method,we used the Quantum-Particle Swarm Optimization(QPSO)respectively establishing the model for the main steam pressure,oxygen content and furnace pressure three subsystems,so establishing the transfer function model of the combustion system.we used the historical data under the same working condition and different time to test the mathematical model of system identification,the feasibility and accuracy of the system modeling based on the field operation data was obtained.(2)On the basis of identifying the mathematical model of combustion system,the two control methods of conventional PID and fuzzy self-tuning PID were respectively used to control the combustion control system of the ultra-supercritical units and the control effects of the two control methods were carried out,the comparison analysis showed that the control quality of fuzzy self-tuning PID control would be better than conventional PID control.