Dynamic Optimization Method for Active Coal Blending and Co Firing Based on Improved Greedy Algorithm
The traditional optimization method of coal blending and CO combustion is lack of dynamic adjustment ability,which leads to the poor effect of boiler in the actual combustion process.Therefore,a dynamic optimization method of active coal blending and CO combustion based on improved greedy algorithm is proposed.This method aims to predict the combustion efficiency and emission environmental protection.These two key indicators are the important combustion characteristics in the process of boiler active coal blending.In order to minimize the heat loss and smoke emission of the boiler,a multi-objective dynamic optimization model of active coal blending and CO combustion is constructed.The model is solved by using the improved greedy algorithm,so as to obtain the best optimization scheme.The experimental results show that after the optimization of the design method,the soot emission of the boiler is reduced by 69.82%compared with that before the optimization,which shows that the method can effectively find the best coal blending ratio,so as to significantly improve the combustion efficiency and environmental protection performance of the boiler.
improving greedy algorithmsactive coal blending and co firingoptimization of co firingdynamic optimization methods
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维普
