Abstract: To address the increasingly severe energy situation and environmental pressure, biomass co-firing in coal-fired power plants has garnered significant attention as a viable emission reduction measure. Attention was focused on the changes in the pulverizing system, a key aspect of retrofitting coal-fired units for biomass co-firing, and in particular on the optimization of coal mill configuration and operating strategies, so that efficient co-combustion of pulverized coal and biomass could be achieved and the overall generation cost reduced. Accordingly, an economic optimization model was developed. The model, aiming to minimize power generation costs, conducts a comparative analysis of the retrofitted unit under three typical operating modes: full co-firing, dedicated co-firing, and flexible co-firing. The formulated mixed-integer nonlinear programming model was solved using the commercial solver Gurobi to obtain optimal fuel allocation schemes for different modes under varying load demands, and to determine the optimal output and start-stop timing for each pulverizer. Compared to the pure coal combustion mode (without co-firing), under typical daily load conditions, the optimized feeding schemes for the different co-firing modes reduced both power generation costs and carbon emissions: the full co-firing mode by 0.6% and 7.0%, respectively; the dedicated co-firing mode by 1.0% and 12.6%, respectively; and the flexible co-firing mode by 1.1% and 14.4%, respectively. The results indicate that the flexible co-firing mode effectively overcomes the inherent limitations of the other two modes concerning biomass co-firing ratios, demonstrating superior operational flexibility, economic benefits, and carbon emission reduction potential. Furthermore, the study simplified pulverizer operation and validated the effectiveness of the solution algorithm. Finally, case studies on key influencing factors (fuel prices, biomass calorific value, biomass supply) revealed their impact on the economics of co-firing and the selection of optimal operating modes.