Circulating Fluidized Bed Boiler (CFBB) is an important part of thermal power plants. The plant’s control system is a complex multivariable system with severe nonlinearities, uncertainty and strong coupling. It is not accurate to use traditional analysis methods to build mathematical models of the system. This paper introduces the modelling method of 330MW circulating fluidized bed boiler coordinated control system based on deep belief network (DBN), using the in-situ data of Inner Mongolia Jinghai Power Plant. Compared with the BP neural network modelling method, the effectiveness of the DBN method in the modelling of 330MW circulating fluidized coordinated control system is proved.

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