Abstract With the large-scale integration of renewable energy into the power system, its inherent volatility and uncertainty pose severe challenges to the scheduling and operation of the power system, which puts higher demands on the peak shaving response performance of thermal power generation units. This article uses the computational particle fluid dynamics method to numerically simulate the coupled combustion process of biomass-blended coal in a 90 kW circulating fluidized bed experimental device. Dynamic response characteristics of three typical biomass-coal co-firing systems (corn stalk, sawdust, and rice husk) were investigated. The results indicate that: (1) In terms of temperature response characteristics of CFB combustion of corn stalk blended coal with increasing feeding rate, the temperature response rate is relatively slow, but the stability is good. The temperature response rate during the combustion of sawdust-blended coal is the fastest, but the temperature stability is relatively weak. The temperature fluctuation during the combustion of rice husk blended coal is the greatest. (2) In terms of heat transfer rate, the combustion of corn stalk blended coal is the fastest, becoming stable first after the end of changing operating conditions, and has the maximum heat transfer rate. The heat transfer response rate during the combustion of rice husk blended coal is the slowest, and due to its low volatile matter content, the heat transfer rate fluctuates greatly after changing operating conditions. The combustion of sawdust-blended coal exhibits the most stable heat transfer characteristics due to its highest volatile matter content. (3) In terms of fluidization characteristics, the gas-solid flow velocity in the furnace increases with the increase of feed rate and fluidized air flow rate. Corn stalk blended coal exhibits the best performance in terms of combustion stability and flow rate. (4) Using thermal response rate and temperature response rate as evaluation criteria, the optimal biomass-to-coal blending ratio under varying operating conditions is determined to be 9:1.
Duan et al. (Mon,) studied this question.
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