Optimal Combustion Control Research On A Sub-critical Coal-fired Boiler-turbine Unit Under Low Load

With the peak of short time and the normal operation of long time low load,the overall efficiency of the steam turbine unit decrease greatly,and the economic benefit of the power plant reduce greatly.Analyzing and researching the 330MW coal-fired boilers of the main power plant of our country's power plants,and conducting modeling and combustion optimization studies for them,is of great significance for improving boiler thermal efficiency and improving economical efficiency and safety.Based on the research and application of combustion optimization with current coal-fired units,with a 330MW coal-fired unit as the object,the thesis research on the dynamic characteristics and mathematical modeling of subcritical drum type boiler under low load condition of the evaporation system,superheated system and combustion system in the first.Then,based on the parameters of the air preheater inlet air temperature,NO_X and other effective parameters under low load,the genetic algorithm is used to derive the corresponding adjustment instructions to optimize the combustion of the boiler.In the process of modeling the boiler,the evaporation model is obtained by using dynamic equation of drum pressure mechanism analysis method,the function of related parameters is obtained by using saturated water and steam properties and mathematical fitting method,and the expression of CDt after the thermal inertia of boiler design parameter correction.The modeling of overheating system is obtained by the method of reducing temperature water disturbance test and system identification.Finally,the MATLAB/SIMULINK tool is used to build the simulation model.Compared with the measured data,it is found that the model output is in good agreement with the actual operation data of the unit.Aiming at the boiler combustion system,by studying the dynamic characteristics of each component and establishing the model,the dynamic characteristics of the pulverized coal,such as the pulverized coal content,the oxygen content of the flue gas and the negative pressure of the furnace,are analyzed.Problems of combustion in low load section of boiler:smoke discharge temperature is high,fly ash contains carbon,NOx excess emissions for a long time.The influence factors are analyzed,the characteristics of NOx emission and smoke emission temperature of large four-angle tangential pulverized coal combustion boiler are studied by experiment.The artificial neural network is used to establish the neural network model of the relationship between operating parameters and NOx emission characteristics and inlet smoke temperature of the air preheater.Combined with the genetic algorithm,the optimal operating parameters can be found,and the efficiency of boiler can be improved by optimizing the collocation of the adjustable parameters(second windscreen and burnout windscreen,first wind pressure,and second wind).At the end of the thesis,the research of this subject is summarized,and the further optimization space is forecasted.It points out the direction for future research and practical application.