Dynamic prediction of in-situ SO2 emission and operation optimization of combined desulfurization system of 300 MW CFB boiler

Abstract

As the emission regulation becomes more stringent, in-situ desulfurization and wet flue gas desulfurization have been widely used for circulating fluidized bed (CFB) boilers. However, few studies focus on real-time operation optimization of combined desulfurization system (CDS) in wide-load range based on in-situ SO2 emission prediction. In this work, according to mechanism analysis, a dynamic prediction model of in-situ SO2 emission was developed. Then, closed-loop and step response experiments were conducted to validate the established model, combined with measured data from a 300 MW CFB boiler. Validation results show that the model has satisfactory prediction accuracy in different load conditions and it can capture special dynamic characteristics of in-situ SO2 desulfurization. More importantly, the model can be feasible for building an economical operation strategy of CDS. Thus, a novel control strategy based on dynamic prediction model was designed, which contributes to decrease the SO2 emission fluctuation and operation costs by correcting the limestone-feed rate in advance. The proposed control strategy was applied to actual operation of the 300 MW CFB boiler. In the long-term operation of CDS after optimization, it was easier to reach ultra-low SO2 emission standard and limestone consumption reduces 15.14% compared with before the operation optimization.