Numerical and Experimental Analysis of SNCR Installation Performance in a Power Stoker Boiler
Abstract
:1. Introduction
- The method of reagent distribution, specifically the design and operational parameters of the reagent injection lances;
- The levels at which the reagent is introduced into the boiler furnace chamber;
- The number of installed lances and their spacing on the boiler walls;
- The molar ratio of the reagent to the incoming NOx;
- The concentration of the reagent solution.
Installation Type | Main Parameters | Aim of the Study | Ref. |
---|---|---|---|
Stoker boiler, coal, compressed urea-air injection | Injection velocity: 70 m/s | Innovative injector assesment | [6] |
Cement industry, ammonia-based SNCR | 0.265 kg/s of ammonia water (concentration not given) | Ammonia slip assesment | [11] |
16 t/h waste incineration plant | Granular urea (1.5–2.2 mm), 3–6 injection points, 25 m/s | Innovative injection device testing | [12] |
Circulating fluidized bed boiler, 140–200 MW, urea solution SNCR | Reagent concentration: 40%, mass flow rate: 310–330 kg/h | Particle swarm optimization algorithm development to model the SNCR | [13] |
Circulating fluidized bed boiler, ammonia-based SNCR | Reduction rate: 30–75%, liquid pressure: 39.7–46.8 psi, flow rate: 0.14–0.25 gpm, air flow rate: 5.5–6.7 scfm | Spraying system optimization | [14] |
- The molar ratio of the reagent to the incoming NOx;
- The concentration of the reagent solution.
2. Methods
2.1. Boiler Characteristics
2.2. Mathematical Model
Solver Type | Pressure-Based |
Solver settings | Coupled, Pseudo Transient |
Spatial Discretization Schemes | Gradient: Least Squares Cell-Based, Pressure: Standard; Density, Momentum, Turbulence: First Order Upwind, Species, Energy, DO: Second Order Upwind |
Simulation type | Steady state |
General models | Mass, heat, and momentum balance equations and energy equation |
Turbulence model | RNG k-ε, Scalable Wall Functions, Differential Viscosity Model, Swirl Dominated Flow [16] |
Radiation model | Discrete Ordinates, Theta Divisions 2, Phi Divisions 2, Theta Pixels 5, Phi Pixels 5 [18] |
Gas model | Mixture Species: N2, O2, CO2, H2O; density: ideal gas; Cp: mixing law; thermal conductivity: ideal gas mixing law; Viscosity: Sutherland; Absorption Coefficient: WSGGM-user-specified; Scattering Coefficient: 0; Refractive Index: 1 [7,19]. |
Droplets model | DPM, SSD breakup model [20,21], heat transfer between droplet and flue gases, evaporation |
NOx reduction | Urea, 2-step decomposition, 7-step mechanism for SNCR [6] |
Grate Zone | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
---|---|---|---|---|---|---|---|
Emitted flue gases mass flow [kg/s] | 0.60 | 1.79 | 4.18 | 4.18 | 1.19 | 0.00 | 0.00 |
Temperature [K] | 1620 | 1620 | 1620 | 1620 | 1620 | 773 | 773 |
Mass fraction of O2 | 0.187 | 0.00 | 0.007 | 0.022 | 0.066 | 0.000 | 0.000 |
Mass fraction of CO2 | 0.000 | 0.156 | 0.257 | 0.263 | 0.208 | 0.000 | 0.000 |
Mass fraction of H2O | 0.188 | 0.180 | 0.030 | 0.000 | 0.000 | 0.000 | 0.000 |
Mass fraction of NOx | 0.000134 | 0.00146 | 0.001415 | 0.000708 | 0.000114 | 0.000000 | 0.000000 |
Overfire air mass flow [kg/s]; temperature [K] | OFA1/OFA2—0.75/0.75; 300 | ||||||
Ignition vault temperature [K] | 970 | ||||||
Ignition vault emissivity | 0.9 | ||||||
Grate emissivity | 0.9 | ||||||
Screen temperature [K] | 373 | ||||||
Screen emissivity | 0.9 |
2.3. Bench Tests
2.3.1. Equipment Specification
- Reagent preparation unit;
- Feed and distribution module;
- Injection lances.
2.3.2. Measurement Procedure
- In the first step, the background was measured to determine the boiler’s steady operating conditions. The analyzer measured the concentration of NOx and other flue gas components for approximately half an hour. The measurement was averaged over time.
- In the second step, reagent injection was initiated. NOx concentration measurement started after a transition period from the reagent injection start. The plant operator observed the NOx rate of change in the flue gas in response to the reagent injection and decided whether steady-state conditions had already occurred.
- In the third step, the actual measurement period followed. The reagent injection at fixed set points (injection lance configuration, insertion points, and operating parameters) and the NOx concentration measurement in the exhaust gas took about 20–30 min.
- In the following steps, the operational parameters of the injection lances were changed (e.g., pressure, reagent output, and urea concentration). Re-measurement with the exhaust gas analyzer started each time after a transition period in which the operator had to confirm the steady-state conditions.
- In the final measurement stage, the background level of NOx concentration in the flue gas was again verified after stopping the reagent injection. This measurement was started when steady conditions were reached. The duration of the measurement was approximately 0.5 h.
3. Results
3.1. Mathematical Modeling Results
3.2. Tests Results
4. Discussion
5. Outcomes
- Increasing NSR significantly enhances NOx reduction efficiency, especially between NSR 1 and 2, but further increases show diminishing returns.
- NOx reduction efficiency decreases with higher boiler power, likely due to shorter reagent residence time and difficulties maintaining optimal temperature conditions.
- Multi-hole nozzles (two- and three-holes) provide better NOx reduction compared to single-hole nozzles due to improved reagent distribution.
- Lower urea concentration (12%) in the reagent improves NOx reduction efficiency compared to higher concentrations (32.5%), as better mixing and droplet penetration are achieved.
- Optimal reagent injection should avoid the flame zone, ensuring it occurs in the correct temperature window for effective NOx reduction.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Carbon (C) | 0.550 |
Hydrogen (H) | 0.035 |
Oxygen (O) | 0.115 |
Nitrogen (N) | 0.020 |
Sulphur (S) | 0.010 |
Ash | 0.135 |
Moisture (H2O) | 0.135 |
Volatile matter | 0.32 |
Fixed carbon | 0.41 |
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Krawczyk, P.; Kurkus-Gruszecka, M.; Dzido, A. Numerical and Experimental Analysis of SNCR Installation Performance in a Power Stoker Boiler. Appl. Sci. 2024, 14, 8508. https://doi.org/10.3390/app14188508
Krawczyk P, Kurkus-Gruszecka M, Dzido A. Numerical and Experimental Analysis of SNCR Installation Performance in a Power Stoker Boiler. Applied Sciences. 2024; 14(18):8508. https://doi.org/10.3390/app14188508
Chicago/Turabian StyleKrawczyk, Piotr, Michalina Kurkus-Gruszecka, and Aleksandra Dzido. 2024. "Numerical and Experimental Analysis of SNCR Installation Performance in a Power Stoker Boiler" Applied Sciences 14, no. 18: 8508. https://doi.org/10.3390/app14188508
APA StyleKrawczyk, P., Kurkus-Gruszecka, M., & Dzido, A. (2024). Numerical and Experimental Analysis of SNCR Installation Performance in a Power Stoker Boiler. Applied Sciences, 14(18), 8508. https://doi.org/10.3390/app14188508