The Application Of BP Network On The Optimization Of Boiler Operation

In this paper, a Boiler Operation Optimizing model is built by using BP (Back-Propagation) Neural Network. The factors that contribute to the boiler efficiency are used as the inputs of the model, and economic parameters such as the boiler efficiency and the coal consumption of electricity are used as outputs. Data collected from MengDa power plant have been used to train the model. Unlike normal direct-method/indirect-method of heat balance, this model computes the boiler efficiency and main parameters needed for control in the boiler's operation efficiently by taking the advantage of Neural Network's inherited powerful co-relating ability, memorizing ability and the ability of mapping with nonlinear variables. The model trained successfully can be used to compute the real-time boiler's efficiency and other concerned operating parameters of the 300MW generating unit in MengDa power plant in NeiMengGu Autonomous Region. The model can analyze the real-time boiler efficiency to some degree. At the same time, it can lead to the advanced methods for optimizing the boiler operation.In this paper BP network Optimizing System is built with Delphi. Using the inherited database of Delphi, the system has strong data store ability and is easy to use.Ye Hong(Power Plant Thermal Engineering)Directed by Liu Tong...