A mean flow velocity estimation scheme based on flow field characteristics and distribution point optimization for carbon monitoring in coal-fired power plants: A numerical study

Abstract

CO2 online monitoring provides a method to obtain carbon emissions by directly quantifying the flue gas flow rate and CO2 concentration. However, significant flow rate measurement errors arise due to the complexity of turbulence in large-diameter stacks. To address the issue, this study utilizes turbulence numerical simulation combined with mean velocity estimation error analysis to investigate the flow field of typical stacks in coal-fired power plants. The simulation results demonstrated that the evolution of turbulence exaggerates velocities. The flow field exhibits stable turbulence characteristics in a single-introduced stack, while in the double-introduced stack, the flow field dynamically evolves due to asymmetric collisions and abrupt expansions. Furthermore, the effects of load and temperature on the estimation error of flow velocity are established. The optimum monitoring height, the ideal chord angle and the stepped number of deployment points based on the log-linear method are determined. Within the single-introduced stack, a correction factor is introduced and a corresponding formula is established that links estimation errors with monitoring heights. This resulted in a dramatic reduction of the maximum estimation error from 14% to 0.3%. Finally, the systematic and simplified optimization scheme for estimating mean flow velocity is summarised, which provides a powerful reference for flow rate measurement for online CO2 monitoring in coal-fired power plants.