Boiler Combustion Optimization Based On Neural Network And Genetic Algorithm

To improve the boiler efficiency and reduce NO_X emissions is the main goals of the power plant flue gas boiler combustion optimization. Combustion characteristics model is the core of combustion optimization. Through the analysis of the development, characteristics, structure of BP neural network and the the theory of the neural network model ,structure and the rules of learning, artificial neural network model can fit any nonlinear function and has good generalization ability and has the self-learning of the complex issues.It has been widely studied and applied in nonlinear system identification. Based on the steady-state test data of a power plant boiler combustion system and through the analysis of boiler system model structure,the thesis applys the artificial neural network method to build the prediction model of NO_x emissions and boiler efficiency.The model achieves the soft sensor of its carbon content in fly ash, flue gas temperature, furnace temperature, NO_x emissions and the prediction and boiler efficiency, and then lays the foundation for the boiler combustion optimization. Genetic algorithms has the characteristics of the implicit parallelism global search of solution space,and it don't has constraints of problems form. This article describes the basic principles and operations of genetic algorithms and compares the difference between the binary coding and real coding.It also improves the crossover and mutation operation and selection of the initial population of Genetic algorithm. Based on the established model of boiler combustion characteristics, genetic algorithm is applied to solve the high efficiency and low emission combustion optimization problem. According to the difference of optimization goals,it was introduced that the optimization of low NO_x emissions under efficiency constrained and the optimization of boiler efficiency under NO_x emissions constrained.It provides the best setting of the operating parameters of boiler for DCS based control layer of the power station. The example shows that the algorithm can achieve high efficiency and low emission operation.