Study on Performance Optimization of Bag Filter Based on Big Data Analysis

The dust removal system of coal-fired power plants often cannot operate under the optimal and most economical conditions when meeting emission indicators. In this paper, by coupling the environmental protection indicators and energy-saving indicators of the dust removal system for analysis, based on real-time monitoring big data of 660MW generator unit operation, a model of unit dust removal energy consumption index and dust removal efficiency index are established. Further analyzing the effect of factors directly related to the bag filter on the dust removal energy consumption and efficiency of dust removal, which are the excess air coefficient, the pressure of reverse-air, and dispersion degree of pressure differential in the dust chambers. The results show that as the excess air coefficient increases, the average performance of dust removal becomes worse, and the unit energy consumption increases linearly with the excess air coefficient; the unit energy consumption and dust removal efficiency are maintained at a better level when the reverse-air pressure is 74-78kPa; the increase of the dispersion degree of differential pressure of the dust chambers can improve the dust removal performance, and the optimal value of dispersion degree is between 0.25 and 0.35.