DU Genwang, YIN Wei, WANG Yanhai, REN Yannan, ZHANG Liankui, LI Qiansheng, LI Zhengxi, WANG Yongfu
For the issues that current coal blending in power plant bunkers, which relies on manual experience, is non-optimal and fails to deeply consider the optimization of mill operation combinations, a dynamic process of progressive coal blending for bunkers and mills based on a cascade optimization strategy is proposed. Firstly, to address the suboptimal nature of traditional manual experience-based bunker coal blending, an automated primary coal blending optimization model for bunkers is established, significantly improving blending efficiency and reducing costs. Then, to further tackle the drawback that bunker coal blending does not consider mill operation combination optimization, a secondary optimization coal blending method is proposed. This method selects reasonable mill operation combinations and optimal output points based on an optimization model, thereby optimizing the simple functional relationship between coal feed rate and load within the DCS system. Simultaneously, based on the practical need for mill vibration prevention, a linear fuzzy programming optimization model with flexible constraints and its solution method are established. Finally, experiments are conducted to validate the proposed method. The results demonstrate that the cascade optimization model-based strategy for the dynamic process of bunker-mill progressive coal blending and combustion further optimizes mill combinations and output to adapt to variable loads on the basis of primary coal blending.
