Abstract
High carbon content in fly ash seriously affects boiler's economical operation. Due to supercritical boiler's high thermal capacity, the inertia of thermal parameter reflecting combustion is bigger. It is especially important to well control carbon content in fly ash during operation. In this article, based on the analyzing influence factors to the carbon content in Fly Ash, the Least Square Support Vector Machine (LSSVM) is applied to build the Control model of carbon content in fly ash. Also Genetic Algorithm (GA) is used to optimize the model under different operating conditions. The optimized secondary air distribution opening adjustment is obtained, which have guiding function in boiler's site operation.
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