Study And Application Of Artificial Neural Network To Modeling Combustion Process Of The Boiler In Power Plants

Boilers are important components in power systems. Boiler is quite complex and huge in size. The process happened in it is of multi-variables and the parameters are heavily coupled together. So its control and optimization are targeted as one of the most key problems by researchers.In this paper, RBF Neural Network was selected as a tool for modeling according to the characteristics of boiler systems. Introducing 'Data-Preprocessing' method and 'Improved Nearest Neighbor-Clustering' algorithm to enhance the generalizing ability of RBF Neural Networks and thus improving its applicability.The boiler system was modeled through its static operation data. 'Multi-Complex' Method was selected as the implementation of multi-goal optimization, and was used in optimization of the process based on the model gained, searching for the optimal input parameters.In the end of this paper, the software of Boiler Combustion System Operation Optimization was development.