Wet Industrial Flue Gas Desulfurization Unit: Model Development and Validation on Industrial Data

Simulation and experimental study of gas-phase diffusion coefficient of selenium dioxide

Improving the removal effect of selenium in wet flue gas desulfurization system is a key way to reduce the emission of selenium pollutants from coal-fired power plants. In order to clarify the removal mechanism of selenium pollutants in the desulfurization tower, it is necessary to obtain accurate selenium gas-phase diffusion coefficient. In this paper, molecular dynamics simulations were used to carry out theoretical calculations of gas-phase diffusion coefficients of SeO2 (the main form of selenium in coal combustion flue gas). The gas-phase diffusion coefficients of SeO2 in the range of 393 K-433 K were measured by a self-developed heavy metal gas diffusion coefficient testing device to verify the accuracy of the molecular dynamics calculations. Furthermore, the calculated gas-phase diffusion coefficients of SeO2 under typical binary and ternary components were obtained by correcting on the basis of Fuller's formula. Finally, a single-droplet absorption model for SeO2 was constructed and experiments were carried out to compare the effect of the gas-phase diffusion coefficient on the accuracy of the model calculations. The error of the model calculations was reduced from 8.09 % to 1.96 % after the correction. In this study, the gas-phase diffusion coefficient of SeO2 in the low-temperature range of coal-fired flue gas was obtained. This study can provide basic data for the development of selenium migration mechanism and control technology.

Simulation of a Multistaggered Baffle Scrubber to Enhance the Efficiency of Simultaneous Desulfurization and Denitrification

In this study, we conduct simulation research on simultaneous desulfurization and denitrification in a multistaggered baffle spray scrubber. By employing two-phase flow simulations within the Euler-Lagrange framework and calculating the gas-liquid mass transfer rate with user-defined functions, we comprehensively analyzed the effects of various operational parameters. Initially, we validated our simulation model by comparing the simulation results with experimental data. Under conditions of a 0.2 mm droplet diameter, a liquid-to-gas ratio (L/G) of 12 L/m3, and a gas flow rate of 5 CMM using a full cone nozzle, the simulation indicated a desulfurization efficiency of 99.90 versus 99.84% obtained experimentally and a denitrification efficiency of 92.01 versus 90.67% obtained experimentally. This comparison confirmed the reliability of the simulation model. Our findings indicate that a droplet size of 2 mm is optimal, enhancing the desulfurization efficiency from 99.90 to 99.98% and the denitrification efficiency from 92.01 to 99.76%. However, when the droplet size exceeds 2 mm, efficiencies marginally decrease. Increasing the liquid-to-gas ratio to 16 L/m3 further improves desulfurization and denitrification efficiencies to 99.98 and 99.80%, respectively. In contrast, higher inlet flue gas flow rates reduce these efficiencies, with a decline observed from 100% to as low as 93.90% for denitrification with 2 mm droplets. Additionally, the use of a swirl cone nozzle, compared to full or hollow cone nozzles, better disperses droplets, enhancing the gas-liquid contact and achieving efficiencies of 99.99% for desulfurization and 99.81% for denitrification with 2 mm droplets. These insights are valuable for optimizing operational conditions in industrial-scale spray scrubbers, significantly contributing to mitigating the environmental impacts of industrial emissions.

Modeling Study of Selenium Migration Behavior in Wet Flue Gas Desulfurization Spray Towers

Wet flue gas desulfurization (WFGD) system is the core equipment for removing SO₂ from coal-fired power plants, and it also has an important synergistic effect on the removal of selenium. However, the removal efficiency of Se across WFGD systems is not as expected, and it varies greatly in different coal-fired units (12.5-96%). In this study, a mathematical model was established to quantitatively describe the selenium migration behavior in WFGD spray towers, including the conversion of gaseous selenium to particulate selenium and the capture of gaseous SeO₂ and particles by droplets. The calculation results show that the behavior of selenium in the spray tower can be divided into three stages: preparation, condensation, and removal. The condensation stage significantly affected the selenium distribution and its total removal efficiency. Furthermore, five factors which may affect the selenium behavior were investigated. Among them, the inlet particle size distribution and the droplet temperature had great impacts on the outlet selenium concentration, which may be the reason for the unstable selenium removal efficiencies. This study can help in understanding the migration process of selenium in WFGD spray towers and provide some guidance for the development of specific selenium control technologies.

Modeling and optimization of wet flue gas desulfurization system based on a hybrid modeling method

Sulfur dioxide (SO₂) is one of the main air pollutants from many industries. Most coal-fired power plants in China use wet flue gas desulfurization (WFGD) as the main method for SO₂ removal. Presently, the operating of WFGD lacks accurate modeling method to predict outlet concentration, let alone optimization method. As a result, operating parameters and running status of WFGD are adjusted based on the experience of the experts, which brings about the possibility of material waste and excessive emissions. In this paper, a novel WFGD model combining a mathematical model and an artificial neural network (ANN) was developed to forecast SO₂ emissions. Operation data from a 1000-MW coal-fired unit was collected and divided into two separated sets for model training and validation. The hybrid model consisting a mechanism model and a 9-input ANN had the best performance on both training and validation sets in terms of RMSE (root mean square error) and MRE (mean relative error) and was chosen as the model used in optimization. A comprehensive cost model of WFGD was also constructed to estimate real-time operation cost. Based on the hybrid WFGD model and cost model, a particle swarm optimization (PSO)-based solver was designed to derive the cost-effective set points under different operation conditions. The optimization results demonstrated that the optimized operating parameters could effectively keep the SO₂ emissions within the standard, whereas the SO₂ emissions was decreased by 30.79% with less than 2% increase of total operating cost. Implications: Sulfur dioxide (SO₂) is one of the main pollutants generated during coal combustion in power plants, and wet flue gas desulfurization (WFGD) is the main facility for SO₂ removal. A hybrid model combining SO₂ removal mathematical model with data-driven model achieves more accurate prediction of outlet concentration. Particle swarm optimization with a penalty function efficiently solves the optimization problem of WFGD subject to operation cost under multiple operation conditions. The proposed model and optimization method is able to direct the optimized operation of WFGD with enhanced emission and economic performance.