Optimized control on model of unburned carbon content in fly ash of station boilers

Fly ash unburned carbon content is an important factor affect the boiler thermal's efficiency. Least squares support vector machine is more suitable for real-boiler test conditions with fewer small sample study,We introduced this method into power plant boiler fly ash carbon content prediction model, established complex models relationship between the boiler fly ash carbon content characteristics and operating parameters, through experiments shown that the accuracy of simulation can meet the actual needs of engineering. Combined with genetic algorithm optimization techniques, to the adjustable parameters of the boiler's secondary throttle opening value andoptimize the carbon content of fly ash results, has achieved good results. As a result, parameters can be optimized to guide operating personnel, improve power plant boiler combustion economy.