Study Of Dynamic Modeling And Optimization Control Method For Boiler Combustion System

In recent years,the power plant coal combustion process produces a large amount of NOx emissions,resulting in serious damage to the atmospheric environment such as severe greenhouse effect and acid rain.For the purpose of energy saving and emission reduction,boiler combustion optimization technology is widely utilized in our country.In this paper,based on the online adaptive dynamic model of boiler,a novel boiler combustion optimization method is proposed,and the nonlinear model predictive control scheme of boiler combustion is investigated.The combustion optimization control system is developed according to aforementioned methods.The DCS control logic is adjusted,which makes a solid foundation for its application.The main research contents include:1.This article proposes an improved online adaptive least squares support vector machine dynamic modeling algorithm.The algorithm for support vector first be screened to ensure the accuracy of the model but also improve the efficiency of online operation.Besides,Online update algorithm using the replacement,add,delete three strategies,in order to better deal with the coal quality,equipment characteristics caused by the combustion system control characteristics of the change.Nowadays,most combustion optimization methods are based on the steady-state model of the boiler combustion system,making it difficult to achieve dynamic optimization under variable load conditions.The modeling and Simulation of a 1000MW coal fired boiler shows that the proposed model can accurately reflect the dynamic characteristics of the boiler with the load change,and has a higher precision and forecasting ability.Compared with the traditional online adaptive least squares support vector machine algorithm,Simplified model of the structure was built,a small amount of calculation,which is the basis for further research on the dynamic optimization control strategy of boiler combustion.2.In this paper,a nonlinear predictive control algorithm for boiler combustion is proposed.The algorithm combines the boiler combustion optimization problem with the nonlinear predictive control,which not only meets the NOx emission standard,but also improves the boiler combustion efficiency.At the same time,In this paper,an improved adaptive parallel genetic algorithm is used to optimize the nonlinear optimization problem of combustion optimization.In summary,the boiler combustion optimization predictive control scheme proposed in this paper has a significant importance in engineering practice.3.A nonlinear predictive control system for boiler combustion is developed.In order to ensure that the combustion optimization control software can run normally,the corresponding DCS control logic is modified.