Research Of Air Distribution Mode On 300mw Coal-fired Boiler

As the development of the social and economic, the demand of power industry to auto control system is more and high. It can not meet the needs of power stations, which protect security and stability production. Energy efficiency has become the target of the reform orientation of power stations. But the boiler operating conditions are very complex in most of power stations now, actual operation conditions are significant differences with the original. It can not satisfy the requirements of economic management in modern power plants, which rely on traditional operating procedures and controls only.The paper research 300MW coal-fired boiler. It analysis the sensitivity influence of the carbon of fly ash as the changing of primary air pressure, on the Analysis of equipment characteristics and Principles, the use of combustion theory. The paper proposes that the change of Primary Air Pressure impacts the boiler combustion efficiency greatly in 300MW coal-fired boiler. It is difficult to build combustion model of the mechanism method, because coal combustion process is extremely complex in the furnace, with the large boiler equipment, large delay and nonlinear and multivariate. The paper established the optimal model of fly ash carbon content, which use historical data of boiler combustion and nonlinear dynamic characteristics and self-learning function of artificial intelligence (support vector machines). It obtain the best parameters of primary air in different conditions on using genetic algorithms. The outcome can be used to guide the adjustment of boiler combustion, reduce carbon content of boiler fly ash and improve the combustion economy.