A Study Of Thermal Economical Optimization Of Boiler Operation In Major Power Stations

In this paper, with the new concept of the oxygen heat-converting value introduced, on-line calculation of boiler efficiency is deduced by means of applying both direct and indirect balance methods. Based on boiler thermodynamic test under different load conditions, the neural-networks model of the coal content in fly ash of the corner tangential circle firing 300MW boiler unit is built up on the basis of the understanding of the nonlinear dynamic features and self-learning function of the artificial neural-networks, and this model is being tested in the selected power plant. In this process, the genetic algorithms (GAs) are studied to optimize the boiler thermal efficiency and find out the optimal operational parameters of the boiler. In a result, the boiler thermal economical efficiency is realized, which can be utilized to direct the optimal operation of the boiler unit.