LAPSE:2023.0073
Published Article
LAPSE:2023.0073
Numerical Simulation and Optimization of SCR-DeNOx Systems for Coal-Fired Power Plants Based on a CFD Method
Huifu Wang, Jian Sun, Yong Li, Zhen Cao
February 17, 2023
Abstract
In order to solve the problem of the uneven distribution of the flow and ammonia concentration field in the selective catalytic reduction (SCR) denitrification system of a 660 MW coal-fired power plant, a three-dimensional computational fluid dynamics (CFD) model was established at a scale of 1:1. The existing flow guide and ammonia fume mixing device were then calibrated and optimized. The relative standard deviation of the velocity field distribution upstream of the ammonia injection grid (AIG) was optimized from 15.4% to 9.9%, with a reasonable radius of the deflector at the inlet flue elbows, and the relative standard deviation of the velocity field distribution above the inlet surface of the first catalyst layer in the reactor was optimized from 25.4% to 10.2% by adjusting the angle between the deflector and the wall plate of the inlet hood. Additionally, with the use of a double-layer spoiler ammonia fume mixing device, the relative standard deviation of the ammonia mass concentration distribution above the inlet surface of the first catalyst layer in the reactor was optimized from 12.9% to 5.3%. This paper can provide a valuable reference with practical implications for subsequent research.
Keywords
Computational Fluid Dynamics, concentration field, flow field, optimal design, SCR
Suggested Citation
Wang H, Sun J, Li Y, Cao Z. Numerical Simulation and Optimization of SCR-DeNOx Systems for Coal-Fired Power Plants Based on a CFD Method. (2023). LAPSE:2023.0073
Author Affiliations
Wang H: Datang Environmental Industry Group Co., Ltd., Beijing 100097, China
Sun J: Datang Environmental Industry Group Co., Ltd., Beijing 100097, China
Li Y: College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China [ORCID]
Cao Z: Department of Energy Sciences, Lund University, SE-22100 Lund, Sweden
Journal Name
Processes
Volume
11
Issue
1
First Page
41
Year
2022
Publication Date
2022-12-24
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr11010041, Publication Type: Journal Article
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LAPSE:2023.0073
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https://doi.org/10.3390/pr11010041
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