Design And Implementation Of Optimizing Combustion Based On GA

The ever-increasing development of the economy gives the imperative demand to the rapid development of the electrical power;however,this induces the increase of the coal consumption.The amount of coal shared for a individual people in China was only half of that in the world,despite the abundance of the coal storage in China.Accordingly, decreasing the emission and increasing the economics are deserved research.The boiler system is one of the most important parts in the Power-Plant.As for it,optimizing the operation of the boiler system is highly desirable for decreasing the coal consumption.In present study,the analysis of the combustion was performed by using BP neural network based on the input of the main factors,which were obtained by POD.The optimizing control parameters were calculated by using GA.The preset study in the thesis was given as follows,1.Based on the POD,presenting the method to obtain the main factors for calculating Boiler Efficiency.Giving the experiemental index on the basis of POD,setting the level of the factors and selecting the orthogonal table to perform the analysis.2.Presenting the preconditioning method of the measured data to further identity the correction of online calculation of the Boiler Efficiency,which can illuminate the correction of the combustion.3.Researching the BP to well know the application of neural network in modeling combustion;furthermore,the method of increasing the result of convergence was presented.4.Incorporating the GA based on the code of real quantity,round of betting algorithm and BP to find the optimizing control parameters.Data analysis by using this method was performed for some Power-Plant and agreement results were obtained.